Effects of Erythrocyte Aggregation on Blood Rheology in Regard to Future Sepsis Diagnosis Application

Darren Burley Courtney Campagna Aislinn Harte Samantha Kelly Max Spiegelhoff

Advisors:

Prof Raymond Page

Prof Ahmet Can Sabuncu

May 7th, 2020

Contents

Authorship ...... 1 Acknowledgements ...... 2 Abstract ...... 3 Chapter 1: Introduction ...... 4 Chapter 2: Background ...... 5 2.1 Sepsis Overview ...... 5 2.2 Current Diagnostic Methods ...... 7 2.2.1 Blood Culture ...... 7

2.2.2 Protein Analysis ...... 8

2.2.3 Prothrombin and Partial Thromboplastin Time/Platelet Counts ...... 8

2.3 Potential Biological Tests for Sepsis Diagnosis ...... 9 2.3.1 Biomarkers ...... 9

2.4 Potential Mechanical Tests for Sepsis Diagnosis ...... 16 2.4.1 Red Blood Cell Deformability ...... 16

2.4.2 RBC Aggregation ...... 20

2.4.3 White Blood Cells ...... 23

Chapter 3: Project Strategy ...... 26 3.1 Client Statement ...... 26 3.2 Design Requirements ...... 27 3.2.1 Standards ...... 27

3.3 Revised Project Statement ...... 29 Chapter 4: Design Process ...... 30 4.1 Needs Analysis ...... 30 4.2 Conceptual Designs and Prototype Testing ...... 31 4.2.1 Erythrocyte Sedimentation Rate ...... 32

4.2.2 Capillary Fill ...... 34

4.2.3 Vibration Syllectometry ...... 36

4.3 Alternative Designs ...... 37

4.4 Final Design Selection ...... 38 4.4.1 Blood Preparation ...... 38

4.4.2 Micro-ESR Methodology & Materials ...... 39

4.4.3 Capillary Fill Methodology & Materials...... 40

4.4.4 Laser Syllectometry Methodology & Materials ...... 42

Chapter 5: Design Verification ...... 44 5.1 Micro-ESR Results ...... 44 5.2 Capillary Fill Results...... 46 5.3 Laser Syllectometry Results ...... 47 Chapter 6: Final Design and Validation ...... 55 6.1 Final Design CAD Prototype ...... 55 6.2 Standards ...... 56 6.3 Economics ...... 57 6.4 Environmental Impact ...... 58 6.5 Societal Influence ...... 58 6.6 Political Ramifications ...... 59 6.7 Ethical Concerns ...... 59 6.8 Health and Safety ...... 59 6.9 Manufacturability ...... 60 6.10 Sustainability ...... 61 Chapter 7: Discussion/Future ...... 62 7.1 Micro-ESR ...... 62 7.1.1 Implications ...... 62

7.1.2 Limitations ...... 62

7.1.3 Future ...... 63

7.2 Capillary Fill ...... 64 7.2.1 Implications ...... 64

7.2.2 Limitations ...... 64

7.2.3 Future ...... 65

7.3 Syllectometry ...... 66

7.3.1 Implications ...... 66

7.3.2 Limitations ...... 67

7.3.3 Future ...... 68

7.4 Device Discussion ...... 69 Chapter 8: Conclusions and Recommendations ...... 70 8.1 Conclusions ...... 70 8.2 Recommendations ...... 70 References ...... 72 Appendix A – Interviews ...... 80 Appendix B – Pros and Cons of Different Testing Methods ...... 85 Appendix C – Pairwise Analysis ...... 86 Appendix D – Lab Gantt Chart ...... 87 Appendix E – Micro-ESR Data and Analysis ...... 88 Appendix F – Capillary Fill Data and Analysis ...... 94 Appendix G – Laser Syllectometry Data and Analysis ...... 99

Authorship

The five project team members, Courtney Campagna, Darren Burley, Aislinn Harte,

Samantha Kelly, and Max Spiegelhoff, contributed equally to the content found in this report.

Extensive collaboration was demonstrated within each section while writing, revising, compiling, correcting, and finalizing the report.

Acknowledgements

The project team would like to thank the following group of individuals and organizations for their assistance in completing this project:

 Lisa Wall, Laboratory Manager, for her training and support of all lab-based activities  Dr. Michael Puskarich, Dr. Kate Madden, and the doctors at Brigham/Faulkner hospital for helping the team to better understand sepsis from a certified medical perspective as well as inform us of current sepsis diagnostic methods used within the field today  Funding from the Biomedical Engineering Department at WPI  WPI Tinkerbox I & E Program for the additional monetary support

Most importantly, the team would like to thank our MQP advisors Professor Raymond Page, PhD and Professor Ahmet Can Sabuncu, PhD. Their guidance and expertise over the past academic year have not only helped enhance the quality of our work but also provided invaluable professional engineering experience and education that will serve us for years to come.

Abstract

Sepsis is a condition resulting from the overreaction of the body to an infectious agent and results in millions of deaths worldwide each year. Sepsis has a very short infection-to- mortality time and can be hard to detect and treat before related afflictions become permanent. A device that could quickly and effectively diagnose sepsis could be incredibly beneficial to ensuring proper treatment is given to septic patients. Furthermore, providing alternative methods of testing than the currently used standard would allow for additional in-depth analysis and the possibility of increased diagnostic success. This paper works to therefore describe the design of a prototype, the included tests, and the reason for use in regard to future septic diagnosis.

Chapter 1: Introduction

Every year, at least 1.7 million adults develop sepsis within the United States of America and almost 270,000 die as a result [1]. Across the globe, almost 30 million people are diagnosed with sepsis which leads to approximately 6 million deaths per year, averaging a mortality rate between 15-30%. In severe cases of sepsis, the mortality rate can jump up to anywhere between 40-60%, mainly amongst infants and those in intensive care units [2]. Despite such jarring death rates, there are currently no methods to effectively treat patients who have developed severe cases of sepsis; if the disease isn’t treated within the first few days of diagnosis, sepsis can lead to kidney failure, immune system disruption, and permanent organ damage [1]. Currently, many methods of testing sepsis are based around clinical observations rather than a direct diagnosis. According to Dr. Kate Madden, a doctor in critical care medicine at Boston Children’s Hospital:

We have many patients whom we may suspect [have] sepsis, but a large proportion do not end up having a clear diagnosis. For research and quality improvement purposes, we use the judgement of the clinical team, usually the attending physician, as well as specific treatments that go along with sepsis. [Appendix A]

This inability to accurately test for sepsis can make it incredibly difficult to ensure the patient is getting the proper treatment they need; the quick-acting nature of the disease makes early diagnosis critical for survival. Therefore, the goal of our project is to create a device that allows for an accurate and specific diagnosis of sepsis that can be used by the medical community. To do so, we plan on designing a small device capable of using a sample of the patient’s blood and performing a series of quick turnaround and low-cost tests that can provide better clarity for a sepsis-positive prognosis to a physician. Our developed device will be inexpensive and require little-to-no user training to successfully perform a test. It is our hope that production and distribution of the device will help medical centers worldwide to better support patients who could potentially be battling this life-threatening disease.

Chapter 2: Background

2.1 Sepsis Overview

Sepsis is a serious medical condition commonly characterized as an overwhelming immune response to an infection and is a common complication of medical surgery or poor treatment of a wound. In many cases, the first stage of sepsis is presented by Systemic Inflammatory Response Syndrome, or SIRS, in which the body begins to overcompensate for an infectious agent. According to the America College of Physicians/Society of Critical Care, SIRS often presents itself through “extreme increases or decreases in body temperature, expedited heartrate, and increased respiratory rate usually greater than 20 breaths/minute” [3]. Early treatment of SIRS is a necessity to minimize further medical complications that can occur.

However, while almost all septic patients have SIRS, the presence of SIRS does not indicate that a person will automatically have sepsis. Sepsis is primarily characterized by the presence of an infectious agent entering the blood stream, commonly referred to as “blood poisoning” [4]. In the instances of surgery, or in the event of an open wound occurring on the body, improper cleaning and management of the wound will increase the probability of an infectious agent entering the body. Once the agent begins to disperse throughout the blood stream - and it becomes harder for the immune system to combat the pathogen - is when SIRS begins to transition to officially being declared as “sepsis”. This usually occurs around 3-5 days after the initial wound or infection occurs. A timeline of sepsis stages can be seen with Figure 1.

Figure 1: SIRS-sepsis patient timeline

Once immunosuppression begins and the body starts being unable to fight back the increased concentration of pathogens in the blood, the severity of sepsis increases dramatically. During this stage, colloquially referred to as “severe sepsis”, the natural physiology of the body becomes incredibly hampered. From the period of approximately five to fifteen days after the initial point of infection, patients diagnosed with sepsis can see decreased levels of urination, more prevalent respiratory issues like pneumonia or shortness of breath, chills or fevers, and patches of discolored skin [5]. Internally, sepsis can be categorized through decreased blood platelet count, increased formation of blood clots, abnormal heart pumping, and drops in blood pressure. Proper treatment of sepsis using antibiotics and vasoactive medications during this phase is critical; if left unchecked for too long, the mortality rate of sepsis jumps up to almost 50% as many patients become afflicted with “septic shock” [6]. At this stage of the disease, organ failure is incredibly common. Lactate levels begin to rise within the body and the combination of decreased blood pressure and blood clotting leads to gangrene within body tissue.

The disease becomes almost untreatable at this point. While “severe sepsis” commonly produces a negative blood culture (due to the delicacy of the test and blood sensitivity during immunization), “septic shock” commonly results in a renewal of positive blood cultures [7]. This is assumed to be because the body develops an inability to overcome infection at this point as total immune system shutdown occurs, allowing microorganisms to once again prevalently exist in the blood [8]. Around approximately 28 days from the starting point of infection - or 20 days from the diagnosis of severe sepsis - the body begins total shutdown and patient death occurs. According to the UK Sepsis Trust, if a patient is able to recover from sepsis, it can take “up to 18 months before the survivor starts to feel like their normal self” with “around 50 percent of survivors dealing with post-sepsis syndrome (PPS)” that can include insomnia, fatigue, damaged organs and a severely hampered mental state [9]. Patients who recover from sepsis also have an increased chance of becoming affected again due to their previously weakened immune system.

2.2 Current Diagnostic Methods

2.2.1 Blood Culture

Currently, there are no truly effective methods for diagnosing sepsis; the primary method for sepsis evaluation lies within blood cultures. Being that sepsis primarily spawns from bacteria entering and dispersing itself throughout the blood stream, samples of blood taken can commonly be tested for bacteremia that might be present within the blood. In many instances surrounding blood cultures, tests can take anywhere from 2-5 days to develop and don’t always guarantee positive outcomes [10]. Furthermore, testing for blood cultures does not directly signify the specific bacteria or fungi that exists within the body. In the case of sepsis, where the dispersion of bacteria throughout the blood occurs rapidly from the point of infection, patients may already be in the stage of severe sepsis before positive blood culture results occur [11]. As mentioned, blood cultures only work for testing bacteremia found in the blood; in the event that a fungi or virus was the cause of sepsis, these tests would be completely ineffective. Therefore, while certainly fundamental for the most part, it is the rather long testing periods coupled with the delicate specificity that hinder blood cultures from being the superior diagnostic method.

2.2.2 Protein Analysis

Since sepsis starts with a massive inflammation of the body, it is common for increased concentration of inflammation proteins like C-reactive protein (or CRP) to be present. In many instances, the increased concentration of C-reactive proteins allows for medical doctors to catch sepsis during the earlier stages of testing. The problem lies in the fact that protein increases are not always consistent. In a case study performed at Westminster Hospital in London, 43 out of 49 patients exhibited increased concentration of C-reactive protein but only by a maximum of about 25%, a relatively small change that could be attributed to other factors like age and gender [12].

According to Dr. Michael Puskarich, an associate professor at the University of Minnesota medical school:

Clinically SIRS, "sepsis-3", [and] procalcitonin occasionally have all been tried and they are not consistently successful. These tools are primarily ways for clinicians to make sure they are "getting the points" for treatment of sepsis patients and meeting CMS [Centers for Medicare and Medicaid Services] core measure success but suffers from terrible usability. For true patient care, good clinicians rely on gestalt and experience combined with overall lab and diagnostic test results to diagnose sepsis more than any single tool, which in and of itself is also problematic due to the highly variable nature and clinical presentation of the disease. Sepsis is also confusing because it exists on a spectrum - it's not a "yes / no" despite many people wanting it to be. You don't go from routine flu to "sepsis," it exists on a spectrum with other infectious diseases that the body does or does not control on its own. [Appendix A] 2.2.3 Prothrombin and Partial Thromboplastin Time/Platelet Counts

Sepsis can have a major impact on the ability of blood to clot within the body. “Prothrombin” and “Partial Thromboplastin Time” refer to how long it takes for clotting within the body to form, usually measured within seconds [13]. More specifically, “Prothrombin time” measures the integrity of the extrinsic system as well as factors common to both systems while “Partial Thromboplastin Time” measures the integrity of the intrinsic system and the common components. On average, clotting time generally takes about 20 to 35 seconds for a healthy person but can be significantly lower within patients who have sepsis, indicating excess blood clotting [10, 14]. In contrast, another common symptom of sepsis is a decrease in the number of

platelets that enter the body. Platelets are smaller cells that are instrumental in the formation of clotting blood; if platelet counts are low, red blood cells are less likely to clot at the presence of an open wound [10]. This vicious contradictory cycle therefore causes increased blood clotting internally within the body amongst red blood cells rather than at the presence of an open wound or injury. This is further elaborated on in section “2.4.2 RBC Aggregation”. While such testing via a d-dimer test (which indicates clot levels in the blood) can be done as early as the starting stages of SIRS, there is currently not enough evidence to determine if testing for clots is an effective method for properly diagnosing sepsis. These challenges are once again further elaborated on within section 2.4.2.

2.3 Potential Biological Tests for Sepsis Diagnosis

2.3.1 Biomarkers

In regard to all possible diagnostic methods for sepsis, biomarkers have found prevalence for their diversity and adaptability. Biomarkers, as defined by the National Cancer Institute, are “biological molecule[s] found in blood, other bodily fluids, or tissues that [are] a sign of a normal or abnormal process, or of a condition or disease” [15]. Of all the possible biomarkers, the three that emerged to have the most promise in the diagnosis of sepsis (based off extensive literature review) include procalcitonin, Interleukin- 6 and presepsin.

2.3.1.1 Procalcitonin

Procalcitonin is currently the most studied of the three biomarkers and has been recognized for its potential in diagnosing sepsis within patients. Procalcitonin (PCT) is a propetide of calcitonin consisting of 116 amino acids and produced by the parafollicular cells of the thyroid and parenchymal cells found in the lungs, liver, kidney, adipocytes and muscle during normal production [16, 17]. Normally, PCT does not make it into the bloodstream because it is converted to calcitonin leaving the blood concentration at about 0.05 ng/mL [18]. The levels of PCT released in the bloodstream are induced by bacterial endotoxins, cytokines, lipopolysaccharides and other inflammatory signals. PCT production is reduced when interferon - signaling proteins produced and released by host cells in the presence of viruses and other pathogens - are present meaning that, during viral infections, the concentration levels do not

increase significantly or at all [19]. Therefore, PCT can only be used for sepsis brought upon by bacterial infections and to differentiate between bacterial and viral sepsis [20].

The current methods to measure PCT concentrations in blood use immunoassays. PCT is the only one of the three biomarkers discussed with an FDA approved assay for sepsis risk assessment in the ICU. The VIDAS BRAHMS PCT test is an automated test that measures the procalcitonin concentrations from a patient’s blood sample. It performs enzyme-linked fluorescent immunoassay (ELFA) on 200 μl samples of whole human blood with a limit of detection of 0.03ng/mL and a range of 0.05-200ng/mL [21]. ELFA is a newer version of the enzyme-linked immunosorbent assay (ELISA). The main difference is that it allows for a much shorter testing time. All steps can be completed, and results are produced in about twenty minutes, though it is noted that this test should be used in conjunction with other laboratory tests for more accurate results [20]. Currently, this device is being sold as a kit including all the reagents needed and the machine needed to carry out the tests [21].

Many research studies have found that PCT allows for the early detection of sepsis. PCT level changes are detectable between two to four hours after inflammation begins and will reach their peak concentration at about fourteen hours, remaining elevated for about twenty-four hours after the inflammatory stimulus [17]. This allows for quick testing of the patient which is a necessity due to the rapid attack of sepsis on the body. According to a study published by the American Thoracic Journal, there were significant differences between the varying severities (SIRS, sepsis, severe sepsis and septic shock) and the concentration of PCT in the plasma of those patients. The study was conducted with 78 patients -18 of whom were diagnosed with SIRS, 14 with sepsis, 21 with “severe sepsis”, and 25 with “septic shock” [22]. The study found that the PCT concentrations for SIR, sepsis, “severe sepsis”, and “septic shock” “(ng/mL) were 0.6 (0 to 5.3) for SIRS; 3.5 (0.4 to 6.7) for sepsis, 6.2 (2.2 to 85) for severe sepsis; and 21.3 (1.2 to 654) for septic shock (p < 0.001)” [22]. By being able to determine the severity of the patient’s condition, a recommendation on treatment will be more accurate. As seen in Figure 2, based off of the PCT concentration in the blood sample, antibiotics use is either encouraged or discouraged. Antibiotics, if prescribed when unnecessary, may cause additional harm, delaying proper treatment and simultaneously increasing resistance of antibiotics among present bacteria [23]. The same study found that procalcitonin had a specificity of 78%, a sensitivity (the

proportion of people who test positive relative to those who have the disease) of 97%, and a positive and negative accuracy predictive value (which determines how accurate positive and negative tests outcomes are) of 94% and 88% respectively [22]. This reliability to differentiate between severities allows doctors to decide on the type and aggressiveness of their treatment, hopefully saving those patients.

Figure 2: Shows the different severities of illness related to sepsis and the associated PCT blood concentration values. Also illustrates what values signify the use of antibiotic treatment [18].

Though many studies show the reliability of PCT, concentrations can be increased in the absence of sepsis. According to a study done by the Journal of Applied Laboratory Medicine, PCT concentrations can increase in the blood:

In many clinical settings in the absence of infection, including after major surgery, transplant, trauma, and severe burns, prolonged or severe cardiogenic shock, severe organ perfusion anomalies, autoimmune disorders, malignancies and metastasis, noninfectious systemic inflammation, chronic kidney disease (CKD), and physiologically in the neonate [24].

Fungal and malarial infections (along with certain medications) can also increase PCT concentrations by simulating the release of cytokines [25]. A meta-analysis study in 2007 found that the mean values of sensitivity and specificity were around 71% meaning that the diagnostic value of sepsis was low and that it cannot reliably differentiate sepsis from other conditions [22]. Not only can different diseases increase PCT concentrations but so can the age of patients; neonates’ baseline PCT levels are higher than that of adults during the first 48 hours of life [25]. These differences in PCT concentrations must be studied further to determine how much of a difference they make in patients’ PCT blood concentrations and how this affects their sepsis diagnosis.

2.3.1.2 Interleukin-6

Interleukin-6 (IL-6) has garnered attention from scientists and researchers as one of the next best sepsis diagnostic tools. IL-6 is one of the most commonly used cytokines in diagnosing bacterial infections and is produced by T cells, macrophages, fibroblasts, endothelial cells and more in response to infection/tissue trauma [26]. IL-6 helps to defend the host by stimulating acute phase responses, hematopoiesis and immune reactions and “is strictly controlled by transcriptional and posttranscriptional mechanisms, dysregulated continual synthesis of IL-6 plays a pathological effect on chronic inflammation and autoimmunity” [27]. IL-6 plays an important part in homeostasis of the body; these molecules regulate serum, iron, and zinc concentrations through control of their transporters, promote platelet creation in the bone marrow, induce the production of phase proteins, reduce production of fibronectin, albumin and

transferrin (other proteins with important regulatory functions), promote differentiation of T- cells, and other effects that occur in many chronic diseases [27].

IL-6 has been found to be a reliable biomarker for diagnosing, determining severity, and predicting the outcome of patients with sepsis. IL-6 concentration increases within two hours from point of infection and can continue increasing for up to twenty-four hours after [28]. This means that sepsis can be diagnosed early and allows for a longer testing window after the initial infection. According to a meta-data analysis of 21 studies, IL-6 was found to have a sensitivity of 68% and a specificity of 73% [30]. This provides moderately accurate results for the diagnosis of sepsis. Though not as helpful in differentiating severities of sepsis as PCT, IL-6 is an effective alternative in diagnosing different stages of sepsis [28]. This can be seen below in Figure 3:

Figure 3: IL-6 concentrations as severities of sepsis increase [28].

2.3.1.3 Presepsin

Presepin, also known as CD14, is another biomarker that shows great promise in diagnosing sepsis. Presepsin is a glycoprotein that is a receptor of the lipopolysaccharide- lipopoly-saccharide (LSP-LBP) binding protein [31]. This receptor can activate signal transduction pathways which trigger systemic inflammatory responses. Presepsin has two forms - mCD14 and sCD14 - which are membrane and soluble forms respectively. Membrane bound

presepsin is found on the surfaces of monocytes and macrophages and sometimes on neutrophils. Likewise, sCD14 is created from mCD14 falling-off or secretion by these cells [32]. When used in diagnosing sepsis, sCD14 is the preferred form of measurement [31].

Immunoassays are primarily used to measure the concentration of presepsin in the blood. Most studies use chemiluminescent immunoassays, which combine chemiluminescence and immunochemical reactions to produce variable light emission, to measure the presepsin concentration in whole blood samples [33]. When performed in a test setting, the blood sample is collected and mixed with a reagent before being diluted. Afterwards, a luminescent substrate is added and automatically processed with an immunoassay analyzer to measure how vibrant the given light is, showing overall presepsin concentration [34]. Currently, there is an immunoassay analyzer called PATHFAST created by the Mitsubishi Chemical Medicine Corporation of Japan that can analyze samples in just seventeen minutes and costs anywhere from $800 to $1,200 [35].

Presepsin is a fast-appearing and reliable biomarker for diagnosing severity of sepsis and estimating 28-day mortality for patients. Presepsin concentrations rise in the first two hours after infection, peak at 4 hours, and decrease between 4-8 hours after infection [32]. This quick timeframe allows for early diagnosis of sepsis but can also be deemed too quick to effectively work. A study conducted by Ma et. al, with 41 patients found significance between the presepsin concentrations between different severities of infection [34]. The study identified ranges for normal, SIRS, local infection sepsis and “severe sepsis” at 294.2±121.4 pg/mL, 721±611pg/mL, 333.5±130.130.6 pg/mL, 817.9±572.7 pg/mL and 1992.9± 1509.2 pg/mL respectively [34]. As seen in Figure 4, all of the values are significantly different from one another, allowing analysis of severity. The same study found that presepsin has a sensitivity of 91.9% and another study found that presepsin has a sensitivity of 85.7% in predicting sepsis [31, 34].

Figure 4: Comparison of presepsin concentrations in different severities of sepsis and infection [34].

Although presepsin does have lots of promise, there are some limitations with its use as a biomarker for sepsis. Though many studies found a high sensitivity and specificity, a meta-data analysis conducted by Zhang et al., of eight studies with 1757 patients found that it may not be as useful as once thought [36]. This meta-analysis found that the pooled sensitivity was 0.77 and the sensitivity was 0.73 meaning that, from these eight studies, there was only a moderate diagnostic capacity for diagnosing sepsis [36]. As LPS, the binding protein, is a component of gram-positive bacteria, presepsin is much more sensitive to gram-positive bacterial infections than gram-negative bacterial infections with a sensitivity of 95.5% versus 77.8% [32]. Presepsin, as it is produced in response to bacterial infection, will therefore not be a successful predictor of viral infection which can also lead to sepsis. Lastly, in patients with renal failure compared to those without, there was no significance between the presepsin concentration values [32]. This may create false results if the patient has any disease which caused kidney failure and needs to be considered when deciding upon which test is the best.

2.4 Potential Mechanical Tests for Sepsis Diagnosis

2.4.1 Red Blood Cell Deformability

Analyzing red blood cell deformability could be helpful as a means of indirectly detecting sepsis. A technique known as laser diffraction, a relatively recent development, offers a way to detect the shape and size of cells.

Laser diffraction is based upon the basic principles of the way light interacts with surfaces. There are four ways in which light interacts when it strikes the surface of an object: the light could be diffracted, refracted, reflected, or absorbed (as seen in Figure 5). Reflected light is light that hits the object and gets “reflected” back directly along the path that the light traveled to the object on, making analysis for this purpose nonexistent. Diffraction makes relatively acute angles in reference to the horizontal plane. In contrast, higher intensities caused by refraction makes wider angles along the positive x axis [37]. As “intensity of light” is easier to measure from a fundamental standpoint, it is the recommended to use diffraction when analyzing smaller particles.

Figure 5: Schematic of refracted, reflected, and absorbed light [37].

Fundamentally, information can be obtained about a particle by observing the intensity of scattered light and the angle of the diffracted light.

Figure 6: Scattering of light from particles of different sizes [38].

Scattered light is essentially a bunch of randomly directed light rays whereas diffraction is used to delineate how the light rays are spread out by passing across an edge at a certain angle. An image of the shape of a cell can be extrapolated from the pattern that the diffracted light rays form [39]. The pattern that is generated by the scattered light is analogous to how a shadow can be formed on a wall when you shine a light on an object. The shadow could be seen as the pattern being made by the scattered light except for in laser diffraction, the actual light (laser) is the pattern. Figure 7 is a simple diagram of a diffraction pattern.

Figure 7: Schematic of laser passing through a sample to form a light pattern [39].

Here, the blue arrow is a suspension of particles, the red arrow is a laser beam, and the red circles are simplified diffraction patterns from the diffracted scattering of the laser. As the pattern is from a sample of particles as opposed to a single particle, it is therefore possible to calculate each particle’ size based on the projected light pattern. From there, it is then possible to distinguish the amount of particles that exist of a specific size based on the particle’s respective light intensity. Similarly, once raw data has been collected from the scattered laser light through means of sensors, the data can then be analyzed to derive a particle size. The data is analyzed using software such as LA-960 software from HORIBA. The general theory for how particle size can be derived is depicted in the schematic below in Figure 8. In Figure 8 a circular aperture is cut into a thin 2D medium, as shown by the grey square. In the equations, “theta” is the angle relative to the positive x axis that a given laser beam ray makes from the aperture to the point that the ray hits on the projecting screen behind the aperture, “d” is the diameter of the circular aperture, “lambda” is the wavelength of the laser light, “D” is the distance between the aperture and the projecting screen (the black square), “y” is the distance between the center of the projecting screen and each point of contact on the projecting screen by the laser from the diffracted rays, and “m” is the refractive index. “d” which is the diameter of the circular aperture, would be representative of the particle diameter and therefore the diameter of the particle could be found from calculating “d” using the equations below.

Here, the blue arrow is a suspension of particles, the red arrow a laser beam, and the red circles are simplified diffraction patterns from the diffracted scattering of the laser. As the resulting pattern is from a sample of particles as opposed to a single particle, it is therefore possible to calculate each particle’s size based on the projected light pattern. From this calculation, one can then calculate the quantity of particles of a set size based on the intensity of light within the pattern. In summary, the pattern itself indicates the size of the particles and the intensity of light in the pattern indicates how many particles there are.

Once raw data has been collected from the scattered laser light through means of sensors, the data can then be analyzed to derive a particle size. Commonly, the data is analyzed using software such as LA-960 software from HORIBA. In Figure 8, a circular aperture is cut into a thin 2D medium as shown by the grey square. In the presented equations, “theta” is the angle relative to the horizontal plane that a given laser beam ray makes from the aperture to the point

that the ray hits on the projecting screen behind the aperture. “d” is the diameter of the circular aperture, “lambda” is the wavelength of the laser light, “D” is the distance between the aperture and the projecting screen (the black square), “y” is the distance between the center of the projecting screen and each point of contact on the projecting screen by the laser from the diffracted rays, and “m” is the refractive index. As “d” would also be representative of the particle diameter, the diameter of the calculated particle could be found from calculating “d” using the equations below:

Figure 8: Fraunhofer circular aperture diffraction theory [40].

The basic concept of how a “particle size analyzer” or a laser diffraction device works is that it first measures scattered light intensity and angle and then secondly it transforms the scattered data into a particle size distribution [41]. Figure 9 shows an example plot of raw data from different particle sizes. In Figure 9 the vertical axis, “I”, is intensity and the horizontal axis, “alpha”, is the distance from the center of the diffraction pattern. The “y” shown in Figure 8 above is a good representation of “alpha”.

The basic components of how a “particle size analyzer” or a laser diffraction device works is that it first measures scattered light intensity and angle and then secondly it transforms the scattered data into a particle size distribution [41]. Figure 9 shows an example plot of raw data from different particle sizes. In figure 9, the vertical axis, “I”, is intensity and the horizontal axis, “alpha”, is the distance from the center of the diffraction pattern. The “y” shown in figure 8 above is seen as a good representation of “alpha”.

Figure 9: Intensity plot: Overlapping diffraction patterns of a sample containing particles of different sizes (left), and a sum of diffraction patterns, i.e. intensities measured by the detector (right) [39].

Laser diffraction is useful in detecting deformability or non-deformability of red blood cells. Normal red blood cells in healthy humans will readily deform when under shear stress. In sepsis, red blood cell deformability has been observed to decrease significantly [42]. Red blood cell deformability has also been known to be the cause of surprisingly low viscosity at high shear rates [43]. For this reason, an effort can be made to study both the deformability of red blood cells and its correlation to viscosity.

2.4.2 RBC Aggregation

RBC aggregation is promoted when inflammation, infection, or trauma occur in the body. In low shear conditions, RBCs tend to aggregate into stacks resembling a roll of coins. These stacks, called rouleaux, can further aggregate parallel to one another to create larger aggregates. In normal blood, shear rates of 7-10 s-1 are sufficient to disperse these aggregates [44]. Aggregate formation is also resisted by RBC surface charge since cells are electrostatically repelled. RBC aggregation is largely a result of macromolecules in plasma, especially fibrinogen [43]. The University of Southern California Medical School conducted a study of experimental sepsis in rats that examined the differences in RBC aggregation between healthy rats, rats who had undergone a cecum ligation/puncture to induce sepsis, and rats who experienced sham operations to cause inflammation without infection [42]. Blood samples were collected from each group, with sham-operated and septic samples collected 18 hours after the operation. Fibrinogen levels and RBC aggregation were found to be significantly higher in the sham operated and septic rats, compared to control. When blood plasma was replaced by a 3% dextran 70 solution, RBC aggregation in the septic rats was again found to be significantly higher than

the control, as seen in Figure 11. Furthermore, aggregation was found to be significantly higher in the septic group than the sham-operated group. Without the effects of fibrinogen from the plasma, this difference must be the result of cellular properties such as RBC surface charge [42]. This experiment displays potential towards differentiating between patients with sepsis compared to those with non-septic inflammation.

Figure 11: RBC aggregation indexes (M1) measured using a Myrenne aggregometer [42]

A similar study of experimentally induced sepsis in pigs at the University of Debrecen by Nemeth et. al. found more controversial results [45]. Five pigs were administered Escherichia coli intravenously in increasing amounts over three hours while four pigs were given a similar volume of an isotonic saline solution. Blood samples were collected from all pigs at the beginning of the experiment and every second hour afterwards for eight hours. The intravenous administration of E. coli initially caused bacteremia. This then developed into fulminant (sudden or severe) sepsis. Of the five pigs in the septic group, two died in 3-4 hours and the remaining three died in 6-7 hours. Instead of the expected increase in RBC aggregation in the sepsis group, RBC aggregation decreased over time. Nemeth et. al. speculated this result may have been due to the experiment investigating the early hours of fulminant sepsis rather than a study of a slower- developing sepsis over a longer period of time, or from the effects of the specific E. coli strain used, which contained hemolysin. This hemolysin affects the RBC membrane and causes swelling, which could affect its aggregability [45]. The results may also have been affected by the deaths of pigs in the septic group. If some factors contributed both towards pigs surviving

longer and towards decreased RBC aggregation, the early deaths of some pigs would skew results towards traits of the pigs that survived longer.

RBC aggregation can be measured in a variety of ways. The erythrocyte sedimentation rate (ESR) is a widely used test in which a sample of blood is placed in a vertical glass tube and the rate at which RBCs, also known as erythrocytes, settle to the bottom of the tube is observed. The greater the aggregation, the faster the RBCs will sediment. This test takes about an hour to perform [43]. Another test uses low shear viscometry to measure the viscosity of blood, which increases with RBC aggregation, but is also affected by hematocrit. RBCs can also be observed directly using a microscope and can be used in conjunction with an image analysis program to track aggregation over time [44]. Finally, a test called “syllectometry” analyzes the light scattering of RBC suspensions; as light is shone through a thin layer of blood, the resultant rays impact a photodetector on the other side that records the light intensity. If blood is disaggregated, each RBC scatters light and the intensity that reaches the photodetector will be low. As RBCs aggregate, the light will be able to shine more directly through to the photodetector. Therefore, the intensity of light measured by the photodetector can be used to determine RBC aggregation [46].

These two experiments embody the challenge in developing a conclusive diagnostic test for sepsis. As sepsis is very broad, it may develop suddenly or slowly. Furthermore, whether it is bacterial or viral, as well as specifics of the infection and the patient, can all have effects on blood. While results may seem promising in one experiment, a similar experiment may have entirely different results. In a hospital setting, patients will be of different ages and backgrounds, with different comorbidities to consider. For example, patients with diabetes mellitus are likely to have increased RBC aggregation in the absence of infections or inflammation [42]. There is also the question of how well experiments on animal models translate to humans. Further studies focused on humans are therefore required.

2.4.3 White Blood Cells

White blood cells have been recognized for their use as indicators in the diagnosis of sepsis. The primary function of white blood cells is to “fight bacteria, viruses, and other organisms your body identifies as a danger” [10]. A high white blood cell count is generally an indication of infection as a greater amount of white blood cells are needed to keep the body healthy.

Neutrophil to lymphocyte ratio (NLR) is a specific method based on white blood cells that may be used for early sepsis diagnosis. Neutrophils, a type of granulocyte, are the first white blood cells to respond and travel to sites of acute inflammation in the body [47]. Due to this fast response time, neutrophils act as the first line of defense, “directly phagocytosing and killing microorganisms” while lymphocytes “determine the specificity of the immune response to infectious microorganisms and other foreign substances” [48, 49]. The primary function of lymphocytes is to bind to receptors to detected antigens and aid in their removal from the patient’s body. Lymphocytes undergo cloning to produce multiple identical cells and to fight against the detected infection. Sepsis generally causes an increase in neutrophil count; this is due in part to neutrophil dysfunction, “a hallmark of sepsis, contributing to weak immune responses to the causative infections, as well as additional off-target organ damage” [50]. This dysfunction affects neutrophil response to the chemical stimulus of infection and negatively affects antimicrobial activity. Since preliminary neutrophils cannot properly fulfill their functions, more neutrophils are therefore needed to quell the spread of pathogens, weakening the stopping power of the body in fighting off newer infections. The lifespan of these neutrophils thereby increases, increasing the number of immature neutrophils circulating in the body [51]. On the contrary, sepsis generally causes a decrease in lymphocyte count. As sepsis progresses and neutrophils cannot properly control responses against infection, lymphocyte apoptosis occurs. This induces “a state of 'immune paralysis' that renders the host vulnerable to invading pathogens” [52]. The death of these lymphocyte cells causes a lower lymphocyte count.

NLR is calculated as the ratio of neutrophil count to lymphocyte count in a blood sample. This blood sample is collected from a simple blood differential test, which is relatively easy to perform and inexpensive compared to other methods of diagnosis. Normal NLR values for an adult in good health are between 0.78 and 3.53 [53]. A higher NLR value corresponds to a

greater amount of physiological stress and systemic inflammation within the patient's body. However, there is currently no standardized level of measurement demonstrating the significance of a value when it is higher than that of the average healthy patient. Greater physiological stress and systemic inflammation may be a result of sepsis, coronary interventions, coronary artery bypass grafting, inflammatory conditions, etc. Therefore, utilizing only NLR as the primary method of diagnosis for sepsis is not ideal as NLR cannot currently diagnose a specific condition. However, NLR in combination with another method of diagnosis may be more promising.

Designing a microfluidic device based on spontaneous neutrophil motility may also be a promising strategy in the diagnosis of sepsis. Motility can be described as the ability of an organism to move by itself, utilizing its own metabolic energy [54]. Patients with sepsis generally have high spontaneous motility when compared to healthy patients. Along with motility, the effectiveness of neutrophils in attacking pathogens is important to observe as sepsis negatively affects the ability of neutrophils to respond properly to chemotactic signals. In one specific study, Dr. Muldur of Harvard Medical School and Massachusetts General Hospital and his team created a microfluidic device to measure spontaneous neutrophil migration from a single drop of diluted blood [55]. The device contained eight migration mazes with each maze consisting of several migration channels and a red blood cell (RBC) filter. An image of this microfluidic device is shown below in Figure 12 [55].

Figure 12: The microfluidic device with a detailed view of the maze [55]

Spontaneous neutrophil motility is then detected through microscopy techniques and tracked through ImageJ/Fiji analysis software. The “Sepsis Score” can then be calculated using the equation below:

Sepsis Score=N*(O+P+R+AD)/103 Eq. 1

In this equation, “… N, is the total number of migrated neutrophils, O, the total number of oscillation phenotype, defined as ‘the total number of cells that switch direction twice in a channel and migrate for more than 15μm in each segment’, P, the total number of arrest phenotype, defined as ‘a cell with zero velocity’, R, the total number of retrotaxis phenotype, defined as ‘any cell that leaves the maze back into the central chamber’, and AD, average distance of all neutrophils traveled in the two mazes, divided by four” [55]. A patient is considered septic if their “Sepsis Score” is greater than 30. This microfluidic device proved to be very specific to sepsis with 98% specificity and 97% sensitivity [55]. This device also proves to be simple to use as an operator would only need to be trained for preparing and loading the patient’s blood sample, as data analysis and the “Sepsis Score” results are automated [50].

Chapter 3: Project Strategy

3.1 Client Statement

While the scope of the project is vast, the initial client statement from Professor Sabuncu, a project advisor, is as follows:

Red Blood Cell (RBC) aggregation is central to the study and diagnosis of sepsis. At low shear rates and during hemostasis, RBCs pile together to form a “rouleau”. At high shear rates, these aggregates are dispersed, whereas, in the microcirculation, shear forces are not strong enough to dissociate the aggregates. In infectious diseases, where the RBC aggregation is elevated, the local viscosity increases in the microvasculature and this increase contributes to low perfusion and tissue ischemia. Therefore, knowledge of the amount of RBC aggregation at low shear rates could allow early diagnosis of septic shock and organ failure. Currently, the gold standard clinical methods to identify sepsis rely on microbiological techniques that require 2-3 days to complete. However, a point of care technology that can diagnose sepsis from the RBC physical properties does not exist. In addition, the current techniques do not allow for comprehensive characterization of RBC aggregation. For a complete analysis of RBC aggregation, RBC aggregate size distribution, aggregate resistance to disaggregation (shear stress), aggregate morphology, and aggregation kinetics need to be quantified. Also, a comprehensive technique should be able to distinguish between plasmatic and cellular factors that lead to aggregation.

Shortly after the initial client statement was provided, a decision was made between the team and the project advisors, Professor Sabuncu and Professor Page, to examine the issue of diagnosing sepsis more broadly. The team is to determine the most important criteria for a sepsis diagnostic test, devise a test/series of tests that best meets those criteria, and design a device to conduct said test(s).

3.2 Design Requirements

3.2.1 Standards Throughout the design process, the team must ensure that all requirements from relevant industry standards are met.

ISO 13485:2016 specifies requirements for a quality management system where an organization needs to demonstrate its ability to provide medical devices and related services that consistently meet customer and applicable regulatory requirements. Such organizations can be involved in one or more stages of the lifecycle, including design and development, production, storage and distribution, installation, or servicing of a medical device and design and development or provision of associated activities (e.g. technical support). ISO 13485:2016 can also be used by suppliers or external parties that provide product, including quality management system-related services to such organizations [56].

Another important standard that is relevant to our design is ISO 11737-2:2009 which addresses standard requirements for the sterilization of medical devices. ISO 11737-2:2009 “specifies the general criteria for tests of sterility on medical devices that have been exposed to a treatment with the sterilizing agent reduced relative to that anticipated to be used in routine sterilization processing” [57]. Sterilization is used to kill bacteria and other biological agents that may have been in contact with the device in order to protect the user. ISO 11737-2:2009 further defines a medical device as an “instrument, apparatus, implement, machine, appliance, implant, in vitro reagent or calibrator, software, material or other related article, intended by the manufacturer to be used, … for human beings for one or more of the specific purpose(s) of: - diagnosis, prevention, monitoring, treatment or alleviation of disease …” [57]. The team’s design will therefore fall under the definition of medical device provided in this and the prior standard. As the team will be trying to diagnosis sepsis using an instrument, the design will be considered a medical device. As the device will be interacting with human patients and blood, the device must be sterilized as to keep all patients safe.

ISO 10993-1 is based on biocompatibility and biological evaluations of medical devices. The major goal of this standard is to protect humans from biological risks associated with medical devices. This standard provides requirements on how to develop a risk management

process and assess all potential biological hazards in order to keep all users safe [58]. ISO 10993-1 will be incorporated into the design as it will be interacting with human patients and blood and the team will need to perform biocompatibility evaluations in order to guarantee safety to all users.

ISO/TC 76 is another relevant standard that is centered around blood processing equipment. ISO/TC 76 is a “standardization of containers (such as infusion bottles and bags, injection vials, ampoules, glass cylinders, cartridges, prefillable syringes, etc.) application systems (such as giving sets, non-electrically driven portable infusion devices, blood collection systems, etc.) and accessories for infusion, transfusion, injection and blood processing in blood banks, terms, definitions, requirements and test methods for these devices, specifications and test methods for quality and performance of their materials and components (such as elastomeric closures, caps and ports, pipettes, etc.)” [59]. This standard is relevant to the team’s design and will be incorporated into a system that will collect and process a human patient’s blood.

ISO 10993-11 is based upon biological evaluation of medical devices in regard to systemic toxicity and adverse systemic reactions. This standard provides requirements for developing a process to evaluate systemic toxicity of medical devices to determine whether the medical device is safe to use on humans [60]. ISO 10993-11 will be incorporated into the design as it will be utilized with human patients and blood and the team will need to perform biocompatibility and toxicity evaluations in order to guarantee the highest safety to all users.

In addition to these industry standards, the team will also adhere to all relevant standards related to ethics. One specific ethical standard is the HIPAA Privacy Rule. This rule “… establishes national standards to protect individuals’ medical records and other personal health information …” [61]. This rule preserves the privacy of personal health information obtained from patients. Information that is protected under this law includes “information your doctors, nurses, and other health care providers put in your medical record, conversations your doctor has about your care or treatment with nurses and others, information about you in your health insurer’s computer system, billing information about you at your clinic, and most other health information about you held by those who must follow these laws” [62]. The team will incorporate the HIPAA Privacy Rule by keeping all patient information safe and private unless given patient authorization.

3.3 Revised Project Statement

From our research on the methods and limitations of sepsis testing, a revised project statement was developed. The goal of this project is “to development a point-of-care device that prioritizes accuracy, a rapid testing time, and a low cost.” The device will be used when sepsis is suspected in patients in order to provide strong evidence towards or against a diagnosis of sepsis. By obtaining results in hours or minutes rather than days, sepsis can be treated earlier in order to increase chances of survival.

Chapter 4: Design Process

4.1 Needs Analysis

Table 1: Pairwise Analysis for Device Designs

When it comes to designing the final device, it is important to consider what both the client and the team find valuable in terms of design elements and overall purpose. If the team focuses on elements that emphasize different components from the client, the device would be considered a failure regardless of its effectiveness in tackling the problem. As a result, we decided to create a pairwise analysis of the different components that the client desired to determine which aspects of the device should be more focused on than others. A pairwise analysis matrix works by comparing and ranking a design element (low cost, easy to manufacture, etc.) and comparing it against the following columns of the same criteria. If the former characteristic is more important than its column counterpart, it is given a value of “1”. If equal, it is assigned a value of “1/2” and if less important, a value of “0”. All values are then totaled following the end of the process and those with the highest total score are therefore the most important traits to focus on when designing our device.

In this instance, comparing the qualities found in Table 1 to those desired by the client, it was determined that “effectiveness in diagnosing” sepsis within the patients was the most important task for our device to accomplish, followed closely by a “low cost” solution and the ability to provide a “quick testing time”. The ability to effectively diagnose the disease captures the highest position since the device’s primary function is to help characterize those with sepsis as accurately as possible. The concept of a low cost yet quick testing design also plays into the notion that sepsis has a very small window in which the disease can be properly monitored

before negative effects begin hampering the body. If a procedure takes too long to perform or costs too much that it might propose doubt in the mind of a doctor to use, it would also serve as an ineffective diagnostic method.

Keeping in mind what is important in the device design, it is now possible for our team to test and adapt methods that focus on achieving these three aspects. Possible methods used in conjunction with the device are discussed in detail in the next section “4.2 Conceptual Designs and Prototype Testing”.

4.2 Conceptual Designs and Prototype Testing Following the pairwise analysis, a concept map was created to allow deeper analysis into potential methods for sepsis diagnosis. Based on the concept map seen in Figure 13, the team then narrowed our focus to RBC aggregation due to its variable testing methods, speed of testing time, and for being the most specific in relation to a septic diagnosis than all other methods. In choosing RBC aggregation, we are further ensuring that we meet the criteria set by our pairwise analysis. Methods to measure RBC aggregation in relation to sepsis are discussed in further detail in the following sections.

Figure 13: Concept map

4.2.1 Erythrocyte Sedimentation Rate

4.2.1.1 ESR

One diagnostic blood test that can be used to compare septic and non-septic blood is the erythrocyte sedimentation rate (ESR), first mentioned in section “2.4.2 RBC Aggregation”. ESR measures the rate at which erythrocytes in an anti-coagulated whole blood sample settle in a test tube within the time frame of one hour, expressed in units of millimeters [63]. Throughout the test, the test tube must remain perfectly vertical as the resultant values are determined by the height of plasma at the top of the tube after the set one-hour period [64]. Primarily, ESR can be used as an indicator of inflammation; patients with inflammation have an increase in the amount of proteins in their blood, which causes red blood cells to clump together [64]. Due to this clumping, red blood cell aggregates within the patient’s blood will settle at the bottom of the tube at a faster rate than those that remain independent. Therefore, a patient with inflammation will have a greater ESR level. Figure 14 shows how red blood cells aggregate when introduced to inflammation. Sepsis involves widespread inflammation in the body so it can be assumed that septic patients will have high ESR levels.

Figure 14: Normal erythrocyte sedimentation compared to inflamed [64]

The Westergren method is considered the gold standard for ESR. Materials required for the Westergren method include anti-coagulated blood, sodium citrate solution, a tube support

rack, and “standardized colorless, circular glass or plastic tubes, with an inner diameter of at least 2.55 mm and sufficient length to include a 200 mm sedimentation scale” [63]. A representation of three different situations is shown in Figure 15 below. Sample A shows the whole blood sample mixed with sodium citrate at the start of the ESR test. Sample B shows normal results for ESR at the end of the 60-minute test time. Sample C shows results for a higher ESR level at the end of the 60-minute test time.

Figure 15: Three possible ESR situations [63]

When using the Westergren method, normal ESR values are ≤15 mm/hr for men and ≤20 mm/hr for women [63]. ESR may increase with age and the highest ESR values generally come from people between 65-74 years of age [63]. Although ESR is a non-specific marker, it will be beneficial to study as there may be a distinguishing feature between septic and non-septic blood that can be measured using this method.

4.2.1.2 Micro-ESR

Micro-ESR is another diagnostic blood test that can be used to compare septic and non- septic blood and, similar to its full-sized companion, Micro-ESR requires capillary blood samples, micro hematocrit capillary tubes, a lancet, laboratory slides, sodium citrate, antiseptic solution, and a rack to hold all of the tubes [65].

The biggest comparison between ESR and micro-ESR tests are their testing timeframes. During a specific procedure performed by Reza Hashemi, a scientist of the Department of Internal Medicine at Shohadaye Tajrish Hospital in Iran, a patient’s fingertip was carefully punctured with a lancet after properly cleaning with antiseptic solution [65]. Four drops of blood were collected and added to a laboratory slide with a single drop of sodium citrate. The blood and sodium citrate would then be gently mixed on the slide. Next, “a 7.5-centimeter capillary tube was placed on the slide immediately with a 30 to 45-degree angle” [65]. The blood sample would then rise through the capillary tube. When the blood sample would reach the 7-centimeter mark, the tube would be placed vertically and placed into a tube rack to ensure all tubes would be vertical [65]. Based on the statistical analysis of Hashemi’s results, a correlation was made between micro-ESR and traditional ESR. Hashemi’s results proved that micro-ESR results can be successfully interrupted at 20 minutes [65]. Therefore, micro-ESR is faster than traditional ESR, which requires 60 minutes to complete, while still using less materials to perform. However, like ESR, micro-ESR is still a non-specific marker of inflammation. Therefore, this teams feels it will be beneficial to study as there may be a distinguishing feature between septic and non-septic blood that can be measured using this method.

4.2.2 Capillary Fill

Capillary action is “the tendency of a polar liquid to rise against gravity into a small- diameter tube” [66]. There are two opposing forces that drive capillary action – cohesion and adhesion. Cohesion results from intermolecular forces, and there is a correlation between these intermolecular forces and a liquid’s viscosity. Adhesion results from attractive forces between the liquid and another surface. In capillary action, adhesion seeks to maximize the amount of capillary surface the liquid touches, while cohesion seeks to minimize the liquid’s surface area [66].

For a capillary tube placed into a liquid at an angle, the liquid will rise along the tube to a specific height. As it does so, it experiences a force that is described by the following equation, illustrated in Figure 16 [67]:

퐹 = 2휋푟훾 cos 휃 − 휌푔휋푟 cos 훽 푠(푡), Eq. 2 where

 F is the force the liquid exerts on the capillary tube  γ is the surface tension of the liquid  θ is the contact angle between the liquid and the capillary  ρ is the density of the liquid  r is the radius of the capillary tube  β is the angle of the capillary tube with respect to the vertical  s(t) is the distance traveled by the liquid along the capillary as a function of time t

Figure 16: Liquid rising in a capillary tube [66]

The first term in this equation describes the force upward due to surface tension, and the second term describes the force downward as a result of gravity. The upward force features two properties of the liquid – surface tension γ and contact angle θ. Surface tension increases with larger intermolecular forces. The contact angle is determined by the balance between cohesive and adhesive forces, with a smaller contact angle contributing to a larger upward force [68].

As red blood cells aggregate, blood viscosity increases [43]. It is suspected that, as red blood cells aggregate, cohesive forces in the blood will also increase [68]. Since there is a correlation between viscosity and the intermolecular forces that affect capillary action, it is possible that different levels of aggregation will cause differences in the speed at which blood will fill a capillary tube [66]. Measurements of this speed can be made and compared to the relative aggregation of these blood samples to investigate a potential relationship between aggregation and capillary fill speeds.

4.2.3 Vibration Syllectometry

Most commercial aggregometers today disaggregate RBCs using a shearing system which can be very expensive. In order to simplify aggregometer design, reduce costs, and allow for simpler cleaning between tests, a team at Kyungpook National University developed an instrument that disaggregates blood through vibrations, then measures aggregation through syllectometry, as seen in Figure 17 [69]. The disaggregation mechanism consists of a function generator, amplifier and speaker. A jig is attached to the speaker diagram such that the jig will vibrate when the speaker is turned on. A glass test slide to hold a small amount (around 10 μl) of blood is then fixed to the jig [69]. This slide has a cavity for the blood and can be easily disposed of after use [69, 70].

Figure 17: Vibration syllectometry device using backscattered light [69]

The syllectometry is conducted using a laser diode (650 nm, 1.5-5mW) that emits a laser beam through the blood sample. A photo diode then measures the intensity of light transmitted through or backscattered by the blood [69, 70]. Measurements from the photo diode are recorded to a computer and the resultant intensity is then used to describe the degree of aggregation in the RBCs. For measurements of transmitted light, a higher intensity indicates a higher degree of aggregation [70]. In backscattered light measurements, a lower intensity indicates a higher degree of aggregation [69].

Following the procedure laid out by Shin et. al, a blood sample is vibrated for 40 seconds at a frequency and amplitude of 150 Hz and 0.5 mm, respectively [69]. The exact timing, frequency, and amplitude can be varied based on the results observed in order to refine the resultant values. The duration should be long enough that the RBCs completely disaggregate while the vibration frequency and amplitude should be mild enough to avoid damaging the cells. Once the blood is fully disaggregated, measurements of the variation in light intensity over time are collected and the application of a curve-fitting program is used to quantify aggregation [69]. For collection of research data, especially when comparing septic and healthy blood, it is helpful to use samples with a similar hematocrit since this affects light intensity.

4.3 Alternative Designs

As RBC aggregation is our main focus, any additional methods need to also focus on RBC aggregation as the main conditional testing criteria. Referring back to our concept map from section “4.2 Concept Map”, our main alternative methods would be incorporating either a standard ESR test or the use of image tracking. Standard ESR tests, while requiring more blood and a longer testing time, are still effective at looking at erythrocyte sedimentation rate. In regard to image tracking, red blood cells can be analyzed over a set period of time to determine how long it takes for rouleaux to form. Specific RBCs can be placed with a virtual marker and tracked as aggregation occurs through a series of photos, making use of continual time periods to detail rouleaux formation.

4.4 Final Design Selection

4.4.1 Blood Preparation

The preparation of the blood dextran solutions for the micro-ESR, capillary fill, and vibration syllectometry were all done as one big batch. Blood was obtained from AllCells, LLC, a reputable blood and marrow cell supplier from Quincy, Massachusetts. The blood was fresh whole blood shipped in a small vial, mixed with an anti-coagulant (Citrate Dextrose Solution – A), and placed in a climate-controlled shipping container before being stored in a fridge. To make our dextran-blood solutions, we used dextran with a 50k molecular weight (MW), whole human blood, and phosphate-buffered saline (PBS). To create the concentrations, five different masses of Dextran 50k MW, obtained from Sigma-Aldrich, were measured using an automated scale. The actual masses of dextran, in comparison to the desired thresholds, can be seen in Table 2. These masses were measured on an electronic scale with an accuracy of +0.1mg:

Table 2: Shows the nominal and actual masses of dextran used in blood sample preparation

Mass of Dextran (grams) Actual Mass of Dextran (grams) 0.025 0.025 0.05 0.051 0.10 0.099 0.15 0.152 0.20 0.201

These measured dextran amounts were each placed in their own 15mL conical tube and labelled with the dextran mass added. Using a graduated cylinder, 10mL of PBS were measured and added to each conical tube. The PBS-dextran solutions were then stirred until all the dextran dissolved in the PBS. To sterilize the PBS-dextran solutions, each solution was passed through a sterile vacuum pump filter inside of a laminar hood. These solutions were then placed in a new sterile 15mL conical tube and labelled by the amount of dextran they contained. Next, inside the same laminar hood, 4mL of 40% hematocrit blood obtained from All Cells was measured with a serological pipette and placed into a separate15mL conical tube. This was repeated for six conical tubes total. Those conical tubes filled with 4mL of blood were then placed inside a centrifuge and spun at 200xg for 10 minutes to allow the full separation of plasma from the

blood cells. After centrifuging, the plasma was then aspirated from each of the conical tubes until there was about 1.6mL of hematocrit left inside the conical tubes. To maintain a 40% hematocrit and produce 4mL of each test, 2.4mL of the dextran-PBS solutions were added to five of the conical tubes containing blood and appropriately labelled. For the sixth tube, 2.4mL of pure PBS was added for a control of 0 grams of dextran. These dextran-blood solutions were then mixed. All solutions were stored in a refrigerator at four degrees Celsius for the duration of the experiment.

4.4.2 Micro-ESR Methodology & Materials

This set-up included a clay capillary tube sealer stand, a blank backdrop made from paper towels, and a sterile cover placed far above the tubes. To begin the Micro-ESR test, a capillary tube filled with blood was placed vertically within a clay-sealant stand, as seen in Figure 18. The capillary tubes were previously sterilized by leaving them in 70% isopropanol for 10 minutes and then allowing them to dry for an hour, until no more isopropanol was present. The cover was used to prevent the downward air of the laminar hood from evaporating or drying out the plasma layer.

Figure 18: Capillary tubes in a clay stand for micro-ESR Throughout the experiment, pictures were taken every thirty minutes for four hours, starting at time zero, using the phone’s camera. Each timer was started immediately after the capillary tube was placed into the clay sealing stand and ended after the test was completed. Once all pictures had been collected, the blood inside the capillary tube was aspirated and the capillary tube was disposed of inside the bio-sharps container while the images were prepped to

be analyzed using the ImageJ software. Using the backdrop in conjunction with ImageJ, the known length of the stand was used to determine the height of the plasma layer in mm. The plasma was measured from the bloodline to the horizontal height between the two sides of the meniscus. This was done to prevent confusion between shadows and the line of the meniscus. This experiment was then repeated three times for each different dextran-blood mixture concentration. The trials were then averaged to find the average aggregation rate of the blood- dextran solution.

4.4.3 Capillary Fill Methodology & Materials

Figure 19: A capillary fill test in progress In order to complete the capillary fill tests, a stand for the experiment was constructed using two conical tube stands of known dimensions, a piece of cardboard, and a large latex glove, shown in Figure 19. The cardboard was cut to be the same size as the top of the stand. It was then placed on the top of the stand and covered with the large latex glove, which acted as a hydrophobic layer during the testing period. This layer was further controlled by sterilization using 70% isopropanol before it was placed in the laminar hood. A second sterile stand of the same size was placed in the laminar hood directly in front of the stand with the glove. A phone, which was used to record the experiment, was then set-up in a way that allowed for both stands to be fully in view outside the laminar hood. The rest of the experiment was then conducted inside the hood. The blood solutions that were to be tested were then removed from the fridge and given time to rise to room temperature, which was about 30 minutes. The conical tube with the blood-dextran sample was then lightly shaken to breakup any rouleaux that had formed while resting.

Using a similar method as before, a capillary was sterilized with 70% isopropanol. Using a P2000 pipette, 500 microliters of the blood sample were then removed and placed on the latex glove covered stand. The tube was filled by manually laying it between the two stands, which created a slope of negative five degrees from the plane (cardboard) the blood sample laid on. The capillary tube was then pushed into the blood droplet and allowed to fill from one end to another. Prior to completion, the tube was then plugged with the experimenter's gloved thumb and removed from between the stands. The filled capillary tube was then placed vertically into the clay stand for the micro-ESR experiment. The purpose of joining these experiments was done to conserve blood.

The video of the experiment, taken on the phone, was then uploaded to a computer. The video was cut into four frames where the blood had flowed to different locations. These frame images were then analyzed using the prior ImageJ software to determine how far the blood had flowed from the opening of the tube that was inserted into the blood droplet. The length was determined by finding the conversion from pixels to mm from the known length of the stand. The flow rate was then calculated by using the frames/second of the video to convert each frame to seconds before timed relative to each other. For example, if the video had a frame rate of two seconds, and frame one was the tenth frame of the video and frame two was the twentieth frame of the video, frame one would be converted to zero seconds and frame two would be at time ten seconds. This time, and the length travelled, was then used to determine flow rate of the blood sample. The flow rates of all three trials were averaged to determine the average flow rate for each dextran-blood solution. This was repeated for each additional dextran-blood mixture.

It is important to note that the capillary tubes were placed at a negative angle, unlike the positive angles described in section “4.2.2 Capillary Fill Test”. This angle was chosen because initial trials found that the dextran-blood solutions did not rise far enough into the capillary tubes. Suitable measurements could not be made at a positive angle. This is likely a result of replacing blood plasma with PBS, which has different properties. For example, PBS has a lower viscosity, which suggests weaker intermolecular forces [71]. From equation (2), increasing the surface tension but maintaining the same contact angle allows a liquid to rise further in a tube [67]. These different properties of PBS meant that angles typically used to draw whole blood into a capillary tube were not viable for this test.

4.4.4 Laser Syllectometry Methodology & Materials

Unlike the micro-ESR and capillary fill tests, the test for laser syllectometry required more personalized equipment than what was present within our laboratory. To begin, a 3D stand was modelled using SolidWorks, sitting 6 inches tall, 4.02 inches wide, and 2.42 inches deep. Three notches were made at 1.67, 2.18, and 3.17 inches respectively and served as holders for an attachment piece meant to house the slide within the device itself. Cut directly into the device’s top was a hole for the placement of a DZS Elec 650nm laser diode (part number 5VLD-R650- 5MW-12). This diode was aligned with a Texas Instruments OPT101P photodiode with an on- chip trans-impedance amplifier that sat within the middle of a breadboard holstered at the bottom of the device. The breadboard, photodiode, and laser diode were all connect to an Arduino Mega 2560 system at the back of the device that regulated voltage control, controlled the laser diode, and recorded output from the photodiode. The Arduino was attached directly to a laptop for power and data transfer. The 3D drawing of our design can be seen below in Figure 20:

Figure 20: The stand designed for syllectometry

Using the prepared blood samples mentioned in section “4.4.1 Blood Preparation”, a small drop of about 100 µL was placed into the center of an AmScope BS-C12 deep-welled slide. The slide was then fixed with a glass cover and placed within the slide holder before being inserted into the device. Prior to activation, two BestTong vibrational coin motors (part number

A00000117) were placed on the left and right of the slide and ran at a frequency of 150hz for approximately 10 seconds. Once the blood had disaggregated, the laser was activated and the signal output from the photodiode was recorded for approximately 5-7 minutes. Following test completion, the slide was disposed of in the proper biohazard container and another was prepared. Five tests were performed for each dextran solution concentration using the same methods.

Chapter 5: Design Verification

The team tested the three separate methods of measuring RBC aggregation – micro-ESR, capillary fill, and syllectometry – to validate how effective they would be in achieving the project goal. The first test, micro-ESR, measured the plasma height of blood in a capillary tube as RBCs settled over a period of four hours. The capillary fill test measured the flow rate of blood in a capillary tube held at an angle. Finally, the syllectometry test measured the intensity of a laser shone through a few drops of blood as its RBCs aggregated.

5.1 Micro-ESR Results

Figure 21: Buffer height of all amounts of added Dextran 50K MW

Figure 22: Comparison of buffer heights of all Dextran 50K MW amounts

As seen in Figure 21 and 22, the slope of the linear trend lines increases with an increase in dextran. The only exception is 0.1 g/dL of dextran since it has a smaller slope than that of 0.05 g/dL of dextran. Otherwise, there is a positive correlation between the amount of dextran and plasma height. The R-squared value of all the linear trend lines for 0, 0.05, 0.1, 0.15 and 0.2 grams are above 0.94 meaning that there is very low variation between trials. For 0.025 grams, the R-squared value is 0.8252 which is still relatively high and gives confidence in the found trend.

5.2 Capillary Fill Results

Table 3: Average flow rate of different grams of Dextran Grams of Dextran Average Flow Velocity Standard Deviation (mm/s) (mm/s) +0.209 0.025 1.03 +0.497 0.05 2.73 +0.150 0.1 1.02 +0.486 0.15 2.40 +0.595 0.2 1.21

Table 3 shows all of the calculated flow rates of dextran amounts 0.025 g/dL to 0.2 g/dL. For all solutions, three trials were conducted except for 0.1 and 0.2 grams, where only two trials were usable due to angle differences. The data shows that the average flow rate for each trial varies from trial to trial. In this testing period, 0 g/dL of dextran was unable to be tested and is further elaborated on in section “7.2.2 Limitations”.

5.3 Laser Syllectometry Results

Figure 23: Laser Syllectometry Initial Setup

Our testing of aggregation via laser syllectometry yielded interesting results. The main notion of testing is that, for each blood sample at a different dextran concentration, there should be an increase in the rate of change and larger difference between the maximum and minimum values of the sampled values. These values can be seen in Table 4 below:

Table 4: Average Testing Values

Each row of Table 4 represents the average value as a result of all tests performed at the noted dextran concentration (g/dL of PBS) with the “Control” row referring to directly extracted whole blood with plasma still intact. After the tests were conducted, the resulting values were imported into an Excel spreadsheet and individually calculated for the same values as shown above. As the input into the system was originally a 1024-ADC byte count, each byte was converted to a voltage resolution before being processed. From the newly acquired voltage, the minimum and maximum values were taken immediately following the start of the test until the final recorded value, ignoring the starting values from before the sample was properly situated within the system (these pre-test values are more clearly show in the data presented in Appendix H). After the minimum and maximum for each of the five tests per data set were recorded, the difference was taken between the two values. From there, the rate of change for each test was taken using Excel’s SLOPE() function with the y-values corresponding to the voltage and the x- values corresponding to time.

The range of initial and ending voltage values were different depending on how precisely the laser was interacting with the blood; samples that were not aligned exactly the same as others

might see increased or decreased voltage values, hence why it was essential to look at the change in voltages over the time period. When looking at the dextran solutions ranging from 0.025g/dL to 0.05g/dL, there is a slight increase between the average min-max voltage difference (a change of ~0.001 volts or 1 mV) and a similar change between the rates of change (~0.000025V/s or 0.025mV/s). This trend continues with each increase in dextran concentration for both the min- max difference and rate of change. It is important to note that, while these trends increase with each concentration, the number of tests within each dextran sample isn’t the same. This limitation is further discussed in section “7.3.1 Limitations”.

The individual values for each test, as well as graphs displaying their rates of change, can be seen in the Figures 24 to 29 and Table 5 to 10 below:

Table 5: Control Tests Information

Figure 24: Control Tests Rate of Change

Table 6: 0.025g/dL Tests

Figure 25: 0.025g/dL Tests Rate of Change

Table 7: 0.05g/10mL Tests

Figure 26: 0.05g/dL Tests Rate of Change

Table 8: 0.1g/dL Tests

Figure 27: 0.1g/dL Tests Rate of Change

Table 9: 0.15g/dL Tests

Figure 28: 0.15g/dL Tests Rate of Change

Table 10: 0.2g/dL Tests

Figure 29: 0.2g/dL Tests Rate of Change

Chapter 6: Final Design and Validation

6.1 Final Design CAD Prototype

The development of the final device design was in large part a combination of what was initially used for testing and awareness of the problems that were faced when performing said tests for the first time. With reference to the syllectometry test, issues with the voltage reading at which to start recording data, the ability to watch the test in action while minimizing the amount of excess light on the photodiode, and wiring were all present. Keeping these aspects in mind, as well as other smaller additional features, we developed our final design shown in Figure 30 below:

Figure 30: Final Design Front (L) and Back (R)

As a comparison to the initial design, it is clear that both the width, height, and depth of the device has been increased. That said, the device was still kept relatively small to minimize production cost and increase portability, having a new width of 7.87 inches, height of 11 inches, and depth of 4.72 inches. One of the most prominent new features is the attached 5-inch LCD touchscreen display at the top of the device. Connecting directly to the Arduino, the touchscreen allows control of the device and its parameters without the need of a computer such as modifying

testing parameters or displaying live data during a testing period. To further this notion of a “stand-alone device”, an additional opening has been created in the back of the device to allow the connection of a USB drive for data storage.

On both the front and back of the device, there exists a one-way acrylic pane. This allows the user to ensure that, during syllectometry testing, the laser is properly aligned with the blood sample without increasing ambient light to the photodiode. This notion is further supported by a voltage-recording threshold where data won’t be recorded until a proper starting voltage is achieved. Additional holes have also been cut in both the top and back paneling for better wire management.

On the side of the device sits an opening attachment to a brushless DC stepper motor. Stepper motors allow for a high degree of modular control when it comes to angular analysis and can be easily adjusted when attached to our main Arduino control system. This motor, when connected to a small capillary holder, allows easy modulation in controlling the starting angle during a capillary fill test. Furthermore, this same motor can be used in our micro-ESR testing. By plugging the capillary tube with clay, the motor can rotate the tube to ensure it is perfectly vertical during the recording period. Beside the stepper motor also exists a small spot for holding an internal battery in the event the device cannot be connected to a continuous power source.

6.2 Standards

Our design incorporated many engineering, industry, and manufacturing standards. Our team incorporated SolidWorks drafting standards when creating the stand for vibration syllectometry testing and our final design using computer-aided design. Our team also incorporated IEEE standards for computer and electronic equipment, such as the 1641-2010 IEEE standard for signal and test definition. Our team incorporated this standard when performing vibration syllectometry experiments, which involved electrical signals.

However, as the team was not able to fully manufacture our final design due to time constraints and issues regarding the pandemic, most of the other applicable standards would only be incorporated if the design were to be manufactured and marketed in the industry. For example, the HIPAA Privacy Rule would only be fully incorporated when patients are actually using our device. ISO 10993-11 also would not be fully incorporated until the final design is

manufactured and patients are using the device since it requires biocompatibility and toxicity evaluation on the device. These evaluations cannot be conducted until the device is fabricated. ISO 13485:2016 focuses on quality management systems of medical devices, with the goal of continuously meeting customer and regulatory requirements, and would not be fully incorporated until device manufacturing. ISO 11737-2:2009 also would not be fully incorporated until the final design is manufactured and is put into use in a hospital setting since this standard involves the sterilization of medical devices. ISO/TC 76 also would not be fully incorporated until the final design is being used with patient blood samples since this standard is centered around blood processing equipment.

6.3 Economics

As sepsis is a serious condition requiring a hospital stay, it can be very costly. According to the Agency for Healthcare Research and Quality, sepsis is “the most expensive condition treated in U.S. hospitals, costing nearly $24 billion in 2013” [1]. The lasting effects and chances of reoccurrence of sepsis can lead to expensive re-hospitalization of patients two to three times as frequently as other conditions (such as pneumonia or heart failure). The sooner a patient receives treatment, the more likely they will be to recover without lasting symptoms or requiring readmission. Since current tests can take time, patients are treated when sepsis is suspected, while awaiting test results.

There are also issues with false positive tests, with one study finding that “a single false- positive blood culture event results in an additional 2.4 days stay in the hospital for the patient” [72]. This is estimated to cost the U.S. healthcare system $7.5 billion per year. The short time required for our tests to achieve results, and the ability for them and other tests to validate one another, can help reduce delays in treatment or extended hospital stays, providing significant savings for patients and hospitals.

6.4 Environmental Impact

The final design will have environmental impacts due to the materials our team has chosen to utilize. The final design includes an LCD touchscreen display. LCD screens contain toxic substances that could have negative effects on ecosystems if they are not disposed of properly. Additionally, the manufacturing process of LCD screens “requires sulfur hexafluoride, a chemical substance that is believed to be responsible for 29 percent of all global warming” [73]. The final design also contains acrylic panels. Acrylic plastic material is not easy to recycle. In some cases, “large pieces can be reformed into other useful objects if they have not suffered too much stress, crazing, or cracking, but this accounts for only a very small portion of the acrylic plastic waste” [74]. Acrylic plastic is also not easily biodegradable. Considering these factors, the final design’s use of acrylic may have a negative impact on the environment. However, the final design will also contain PLA, which is recyclable and biodegradable. PLA would not have any negative impacts on the environment.

6.5 Societal Influence

As a service, being able to diagnose sepsis with any form of confidence can certainly be beneficial to helping save the lives of millions of people and would, therefore, be an incredibly helpful addition to the world of healthcare. While not directly revolutionizing the global market, our device certainly can help in furthering the investigation in sepsis diagnosis, laying the groundwork for devices of similar nature. Furthermore, the limited amount of blood needed for testing samples ensures that the risk of increased infection remains limited in an already immuno-compromised patient.

The effect on the individual should also not be ignored. Awaiting a diagnosis can be stressful for patients and loved ones. Faster results lessen the time spent fearing the unknown, and ensure proper treatment is provided to increase chances of recovery. Currently, when sepsis is suspected, treatment is provided before testing is completed. This is due to the fast-acting nature of sepsis, where every hour of delayed treatment may increase the odds of a poor outcome by 3-7% [75]. Receiving faster results will prevent unnecessary treatment for non-septic patients, allowing hospital resources to be used for other patients, positively influencing others’ outcomes when resources are limited.

6.6 Political Ramifications

While sepsis can affect anyone, diagnosis and treatment largely depends on one’s socioeconomic status. A recent study from January 2020 estimated the global deaths from sepsis to be 11 million – twice the previously-believed amount. This revised estimate accounts for new data from areas with a lower socio-demographic index (SDI), while previous estimates were based on hospital data from high-income countries. The burden of sepsis is higher in areas with a lower SDI, where many cases occur outside of hospitals and are unrecorded [76]. In areas of poverty or with limited resources, our device can help in reducing the amount of sepsis-based fatilities and can decrease the cost and turnaround time of septic tests.

6.7 Ethical Concerns

The major goal of our product is to help give patients a good and satisfying life by accurately diagnosing sepsis in a safe and efficient way. Diagnosing sepsis early on could save many patient lives. Although there may be concerns regarding the ethics of our product since it is a medical device, our team followed ethical guidelines and moral principles to make sure our product was centered around meeting the needs of patients. Our underlying motivation was to do what was morally right and good for patients. Another important goal was to prevent harm. Our team made sure that our product met technical standards and safety standards so that our product was completely safe for patient use. Our product was also designed to respect the autonomy of patients. Patients will have the right to deny using our product. Patient data will never be released and will always remain protected under the HIPAA Privacy Rule.

6.8 Health and Safety

One of the most important tasks of our device is to help better diagnose sepsis within a potential patient. Through the usage of the tests incorporated into our device, we can say that such an achievement is possible in a variety of ways. As a septic patient might already be in a weakened state, avoiding as much additional stress as possible on a person is essential. As our system requires a relatively small blood sample size to perform tests and has a fast turnaround time, we can ensure that no additional harm would come to a patient during the testing period.

6.9 Manufacturability

If the device we are designing were to be marketed, we recommend that a good way to manufacture it would be through injection molding and/or compression molding. Injection molding is a fast manufacturing process and when mass producing a product in this manner, the cost per item produced is relatively low. Initially the cost of the machines and the creation of molds for startup companies is high, but once the right investments have been made, products can be produced at a quick rate. Compression molding is another manufacturing option which could potentially be used. One benefit of compression molding is that tooling costs are cheap, making it good for small production runs. Also, compression molding can produce very durable products. However, compression molding is slow and cannot be used for intricate geometry. The device does not need to be highly durable as it will only be required to withstand small force loads. Therefore, the most advisable method for manufacturing would be injection molding. In order to produce the device inexpensively but also meet the design requirements, we would advise that the device be made of plastic. Injection molding is primarily used with plastics and thus our device could easily be made from plastic. For the initial prototyping of our device, we would use an additive manufacturing method such as 3D printing. 3D printing can produce the prototype model that we need, and the cost of a 3D printer is small compared to the machinery required for mass producing. The material we would use would be PLA (Polylactic acid- biodegradable filament) or ABS (Acrylonitrile Butadiene Styrene). These are basic and common 3D printing materials that are low cost and would be sufficient for producing a working model of our device. We would probably opt to use PLA for prototyping as PLA tends to be more precise because it prints at lower temperatures making it less likely to warp. The electronic hardware involved with our device such as the vibration syllectometry circuitry and laser diodes, the 5- inch LCD touchscreen display, and the brushless DC stepper motor, are things that have already been produced and thus we do not need to worry about manufacturing the electronic hardware ourselves.

6.10 Sustainability

A great benefit of making our device primarily out of PLA is that PLA, which is a plastic, is easily recyclable, so our product could be made at least in part from recycled material. Another benefit of making our device primarily out of PLA is that it is biodegradable, so it is safe for the environment. The energy costs associated with our device are very low. For one, the tests that require electrical power can be performed relatively quickly. Secondly, the power usage required during that time is negligible. Therefore, it is unlikely that any piece of electrical machinery will burn out within a short period of time.

Chapter 7: Discussion/Future

7.1 Micro-ESR

7.1.1 Implications

The micro-ESR data shows a strong positive correlation between an increase in the amount of dextran and an increase in plasma height. Plasma height is representative of the amount of space where fluid is present, but blood cells are not. Therefore, the higher the plasma height the higher the aggregation. As a result of these tests, it can be concluded that an increase in dextran increases aggregation of the red blood cells and that the micro-ESR test is capable of recognizing this increased aggregation. For this reason, it is believed that micro-ESR is a beneficial method in determining aggregation rate for the potential diagnosis of sepsis.

7.1.2 Limitations

Errors and limitations in the micro-ESR testing could be results from bubbles within the dextran-blood sample, the placement of the capillary tubes within the clay stand, tools used to measure the plasma height, the amount of time and labor it took for each test, and lastly, the limited number of tests conducted. As the same tubes and samples used in the capillary fill test were used for the micro-ESR tests, the movement during filling caused some of the samples to include air bubbles. These air bubbles cause sections of the entire blood sample to aggregate separately. If the dextran were unevenly split between sections, this could have caused more aggregation in one section than the other.

After the capillary tubes were filled, they were pushed into a stand containing clay that would seal the bottom of the capillary tube. During placement into the clay, the capillary tubes were not always completely vertical. This angle could have caused the blood to aggregate at an angle that would not be reflected during measurements. The entire test itself took four hours with an individual taking images of the capillary tubes every thirty minutes. This always required someone to be present in the lab and to keep track of multiple timers at once. The juggling of trials and long hours is not ideal for someone who wants to run many trials at once. Furthermore, as we used a phone camera for all our image collection, the resolution was

not extremely high. This made it difficult to differentiate the top of the plasma and the start of the aggregated blood from reflections and shadows in the capillary tube. Similar to the capillary fill experiments, all measurements were made using ImageJ. As image length measurements were made manually, human error in choosing locations to start and stop measurements introduces a new area for error to be introduced. Lastly, although most results supported the trend that an increase in dextran amount increased aggregation, the 0.10 g/dL dextran test did not follow this trend. This anomaly could be due to any of the errors mentioned before or could be due to not properly mixing the dextran-blood sample before use. Lastly, as there were only three trials for all six tested dextran amounts (except for 0g/dL of dextran which only had two) there is a limited sample size to statistically determine the accuracy of this test.

7.1.3 Future

For the future, further testing and refinement of the tests should be completed to ensure the results of this study are reproducible. To decrease the inconsistencies between tests, the capillary tubes should be filled in a way that ensures little to no air bubbles get caught in the samples. This will allow for even aggregation throughout tube and more accurate measurements of aggregation. After using the clay stand to plug the end of the capillary tubes, the capillary tube should be placed on a stand that will ensure that the tube is held completely vertical for the duration of the experiment. This will make the blood aggregation flat within the tube which will allow for accurate measurements. Additionally, the camera used for tracking the height of plasma should have a resolution high enough to allow for minute detail changes within the tube to be tracked which will also allow for more accurate measurements. To reduce the amount of required labor time, either the dimension of the capillary tubes could be changed, or the collection periods could be changed. To change the collection period to every hour instead of every 30 minutes would allow fewer required hours in the lab. Otherwise, instead of frequent imaging, a time-lapse video recording of the capillary tube could be taken over the four hours. A software could then be used to autonomously track the aggregation of red blood cells within the tube. This would allow for more data points per trial and significantly reduce labor time. The inner diameter of the capillary tube could also be changed to require a smaller amount of blood and or to reduce the amount of blood in contact with the wall which reduces forces against aggregation. This would also decrease the amount of labor time required. Lastly, more tests

should be conducted. Currently, there are only three trials for each dextran-blood solution. By increasing the number of trials, this will increase the statistical significance of results and ensure the reliability of the findings.

7.2 Capillary Fill

7.2.1 Implications

The capillary fill tests had little to no correlation between the amount of dextran and the flow rate time. The results were inconclusive as there were increases and decreases between the flow rates as the amount of dextran increased. As an increase in the concentration of dextran in the blood increases aggregation of the red blood cells, it can be concluded that there is no relationship between aggregation and flow rate within our current setup. Therefore, it is recommended that further analysis into the angles involved in the capillary fill test be conducted using the final design prototype to determine the viability of this method in terms of RBC aggregation.

7.2.2 Limitations

As previously explained, the capillary fill tests cannot be applied to the final design as the results could not provide any correlation between aggregation and flow rate. This inability to find a correlation could be a result of inconsistencies due to the materials used, human error, and the limited number of tests conducted. For our tests, we intended to mechanically set the angle each tube was held at. The angle for testing was intended to be positive. But in preliminary tests, it was found that to keep the angle consistent between all tests, the angle had to be negative to allow for capillary flow. To create this negative testing angle, the capillary tube was held by hand between two stands. This did allow for an angle that was generally consistent, but variation was still present that could have been minimized with a mechanical device. This also introduced increased movement of the capillary tube as it was held by a human. This movement could have disrupted flow, changing the results of the study. The capillary tubes could have also had variation in their hydrophilic properties. Although each tube was sterilized, manufacturing of each tube could have been inconsistent in the coatings. Thus, different capillary tubes could have had different hydrophilic properties which would have helped or hindered capillary flow of the blood in the tube.

Placing the blood on a latex glove for a hydrophobic surface was also not ideal. The latex glove was originally hydrophobic, though it still has some pores. But after repeated use, the hydrophobicity of the gloves decreased, causing the contact angle of the blood droplet to decrease between tests. During some tests, bubbles were present in the blood that disrupted flow. For some other tests, the capillary tube had to be placed into the blood droplet multiple times before flow could be generated. In relation to the specific dextran tests, the 0 g/dL tests were unable to be conducted and, due to large differences in angles, only two tests, out of three, could be analyzed for 0.2g/dL and 0.1g/dL concentrations.

Lastly, there were only three trials for each tested dextran solution which is not a large enough study to provide statistically significant results. The measuring of each test was done by measuring the travelled distance of the blood in capillary tubes in four frames from the recorded video. The video of the trial’s resolution was too low to see minute changes thereby making the measuring of the blood’s location difficult. As the measuring was done using ImageJ, each line was drawn by a person. As people are not precise with any consistency, the exact measuring of the blood location was a variable to consider. These inconsistencies, and limited trials in testing the dextran-blood solutions, were mainly due to the shortened testing times resulting from the shutting of the lab because of the COVID-19 pandemic. Without this interruption, many changes to our testing protocol would have been made to improve reliability of the study.

7.2.3 Future

For future testing of the relationship between capillary fill and aggregation, many changes would be made to the materials and automation of testing would have been used. To address the inconsistent angle and location of the capillary tube, a mechanical stand could be built to introduce the capillary tube to the blood droplet at a set angle and then hold the capillary tube still for the entirety of the trial, similar to what is present in the final device prototype. This would eliminate the effect of movement of the capillary tube on the flow rate of the blood and ensure no air bubbles would be introduced to the samples. The tube itself could also be plasma cleaned to create consistent surfaces between capillary tubes. This would have ensured that the blood stuck to the tube to relatively the same degree between each test providing the same potential for each blood sample to flow. To increase hydrophobicity and consistency of the surface that the blood is placed on, a glass slide coated with Acryl-Glide or a similar agent that

creates a hydrophobic surface should also be used. Using this glass slide would ensure a flat surface for every test. The coating would also induce a consistent contact angle for the blood samples; by having a consistent contact angle, the pressure difference within the capillary tube would be the same for every test.

The measuring of the capillary fill should also be automated. This could be done by using a higher resolution camera, allowing for clearer pictures to be analyzed, and in conjunction with a software that could track the location of the blood in the tube throughout the video. This would also significantly reduce the amount of time to analyze each trial within each dextran-blood solution test. Therefore, more tests could be conducted and analyzed in a shorter amount of time. This would also reduce variation between test operators and allow the test to be conducted with less operator influence. In the future, the testing should encompass all the dextran-blood solutions. By including the 0 g/dL dextran-blood solution, there would be more comparable data. This would allow for any anomalies or trends to be spotted. Lastly, every dextran-blood solution should include more than three trials. A larger sample size would create statistically significant results. With these more accurate and precise tools, the inconsistencies between tests could be significantly decreased. With this new set of data, the usefulness of capillary fill in determining increased aggregation would be re-evaluated.

7.3 Syllectometry

7.3.1 Implications

The main focus of the laser syllectometry test was to develop a way of measuring blood aggregation via an experimental and unconventional method of RBC disaggregation and use of light scattering. The notion present was that, if blood aggregation was occurring at a faster rate, you would see the intensity of transmitted light increase at a faster rate and therefore a higher voltage climb would be recorded. Being that the resolution for capturing data was relatively low and, initially, very sensitive to outside light sources, the average min-max difference as well as the rate of change of volts over time was key for our analysis.

Referring back to Table 4 (which summarized the syllectometry results and can be found on pg. 48), it can clearly be seen that increasing the concentration of the dextran solution leads to an increase in the min-max voltage difference and in the rate of change. As dextran has been found to increase RBC aggregation, when the concentration of dextran increases, an expected increase in aggregation should also be present. If aggregation is occurring at a faster rate, an increase in rouleaux should also be expected, causing less light to be scattered through the sample and more directly hitting the photodiode. Therefore, based on the data present in Table 11, we can say that laser syllectometry is a valid method for testing blood aggregation.

It is important to note that, while informative, the “control” row isn’t accurately involved with the data present in the 0.025g/dL tests to the 0.2g/dL. Ideally, this data was meant to serve as a basis for confirmed septic blood; this will be further discussed in “7.3.2 Limitations” and “7.3.3 Future”.

7.3.2 Limitations

One of the largest limitations on the syllectometry tests, as with many of the other tests, was the inability to be present in the lab during the entirety of D-term due to the COVID-19 global pandemic. Given that lab time was hindered during the final term, limited testing data was recorded; this can be seen in Appendix H for all the test data, noting how some tested dextran concentrations have one- or two-sample tests. Another hindrance, in relation to the pandemic, was the inability to re-test data using the improved device design. Some of the flaws recognized within the design were corrected – as mentioned in section “6.1 Final Design CAD Prototype” – and would therefore allow for more precision with the produced results. An improved blackout system, threshold voltage control, and resolution adjustments would have made for significantly more stable outcomes with each dextran solution. Unfortunately, this could not be achieved and would certainly be a recommended point of continuation if possible.

Finally, in relation to the syllectometry test itself, while the data present does show an increase in blood aggregation as reflected by a change in voltage over time, it doesn’t speak to any certainty on whether a patient absolutely has sepsis. The blood sample used has the potential to display a variety of other conditions that a patient might be dealing with besides sepsis. This

test is meant to work in conjunction with the other tested methods to help improve the accuracy of a sepsis diagnosis and is therefore not recommended as a standalone test for diagnosis.

7.3.3 Future

When conducting additional tests using laser syllectometry, there are a few instances that the team would like to test. For one, the inability for the team to acquire valid samples of septic blood was a major hindrance and is what resorted to the use of dextran solutions. Being able to use clinically certified septic blood in conjunction with that received from AllCells would allow the team to speak with more certainty regarding the success of the laser syllectometry test. Furthermore, if testing were to continue, it would be ideal to use the updated device design for both increased precision and control of testing parameters, leading to fewer variables present in the data.

7.4 Device Discussion

As mentioned in chapter 4, a few of the tests carried out did not require extensive fabrication of a device or system. However, the final device design provides a platform to help carry out the tests in a more controlled fashion. For instance, the final design allows us to hold capillary tubes at desirable angles with increased precision than what someone would be able to perform manually. Furthermore, the increased parameters regarding the syllectometry test allow more control over the data being recorded. There are, however, some limitations to the amount of control the device has on certain things. One such limitation is that the device is subject to whatever external conditions are present within the testing environment. These include, but are not limited to, temperature, moisture, ambient light, and vibrations. Therefore, it is recommended that tests be conducted using the device in a controlled laboratory setting to minimize extraneous effects during the testing periods. Another limitation to the device is that it doesn’t have any features that guarantee keeping a person sterile from the blood they are working on. When conducting tests with our device, users would need to take the necessary precautions to make sure they are working safely with a blood sample. These precautions include wearing gloves and cleaning surfaces that may need to be cleaned. The single-use disposable nature of the glass slides and capillary tubes do help to reduce the cleaning required between tests, allowing for a faster testing turnabout than a device that needs a deep cleaning with each use.

Chapter 8: Conclusions and Recommendations

8.1 Conclusions

Sepsis is a life-threatening condition that kills millions each year. Many physicians consider diagnosis the most difficult aspect of sepsis, as due to its wide range of symptoms with high variability, there exists no conclusive test for the disease. Existing tests face the issues of low sensitivity and specificity, slow turnaround times, and uncertain results. Physicians must therefore rely on experience and a range of tests and symptoms when attempting to diagnose a patient. Backed by extensive literature review, the team investigated the possibility of measuring erythrocyte aggregation as a sepsis diagnosis tool.

Of the three aggregation measurement methods tested, micro-ESR and laser syllectometry were capable of differentiating levels of aggregation among blood samples containing various concentrations of dextran in PBS with a degree of confidence. The final design focused on building around laser syllectometry (as it was the most complex in terms of tools and equipment) while also featuring an attachment that would assist in further testing the methods of micro-ESR and capillary fill with greater precision. Therefore, using at least two of the three proposed testing methods, the final device design creates a system that allows for the possible diagnosis of sepsis via red blood cell aggregation.

8.2 Recommendations

The team was successful in identifying two methods capable of measuring blood aggregation, but these results could be further improved through recommended adjustments to the experimental procedures and direct validation with septic blood.

For the capillary fill tests, further testing had been planned using plasma-treated capillary tubes and drops of blood placed on glass slides coated in Acryl-Glide, a hydrophobic substance. These were expected to increase blood adhesion to the capillary tubes and drive capillary action more strongly, possibly allowing measurements to be made at a positive angle. This would allow for existing theory to quantitatively describe blood flow, and better differentiate the effects of

capillary action from gravity. This may lead to a correlation between RBC aggregation and flow rate whereas none was observed in the current tests.

The final design contained improvements to all three tests, allowing more accurate and precise control of capillary tube angles for the micro-ESR and capillary fill tests and improvements on laser alignment for the syllectometry test. The team was unable to fabricate and validate this design to assess its functionality or use it to conduct further trials. This, combined with the limited number of tests that could be performed, leads to our recommendation that further testing be conducted to validate the ability of each test to measure RBC aggregation using the newly created final design.

Finally, the team recommends validation of these tests with septic blood. The team could not obtain septic blood for testing within a reasonable time period and instead induced aggregation using dextran. Ideally, tests would be conducted with septic and non-septic blood samples from a variety of people, including those with non-septic inflammatory conditions, to determine the specificity and sensitivity of our tests.

References

[1] National Institute of General Medical Sciences. (2019, September 27). Sepsis. Retrieved October 11, 2019, from https://www.nigms.nih.gov/education/pages/factsheet_sepsis.aspx

[2] Davis, C. (2019, July 12). Sepsis (Septicemia) Diagnosis, Causes, Treatment & Symptoms. Retrieved from https://www.medicinenet.com/sepsis/article.htm

[3] Chakraborty, R. & Burns, B. (2020, March 28). Systemic Inflammatory Response Syndrome. StatPearls - PubMed-NCBI. Retrieved from https://www.ncbi.nlm.nih.gov/books/NBK547669/

[4] Cirino, E. (2017, July 18). Blood Poisoning: Symptoms, Signs, Causes, and Treatment. Retrieved from https://www.healthline.com/health/blood-poisoning

[5] O'Connell, K., & Higuera, V. (2018, August 31). Sepsis: Symptoms, Causes, Treatment, Risks & More. Retrieved from https://www.healthline.com/health/sepsis

[6] Leon, A. (2013). Clinical course of sepsis, severe sepsis, and septic shock in a cohort of infected patients from ten Colombian hospitals (doi: 10.1186/1471-2334-13-345). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727953/

[7] De Prost, N., Razazi, K., & Brun-Buisson, C. (2013). Unrevealing culture-negative severe sepsis. Critical Care, 17(5), 1001. doi:10.1186/cc13022/

[8] Bone, R.C. et al. (1992). Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee... - PubMed - NCBI (DOI: 10.1378/chest.101.6.1644). Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/1303622

[9] UK Sepsis Trust. (2018, June 17). Post Sepsis Syndrome. Retrieved from https://sepsistrust.org/get-support/support-for-survivors/post-sepsis-syndrome/

[10] "Testing For Sepsis," 2019. [Online]. Available: https://www.sepsis.org/sepsis- basics/testing-for-sepsis/

[11] Cantey, J. B., & Baird, S. D. (2017). Ending the Culture of Culture-Negative Sepsis in the Neonatal ICU. Pediatrics, 140(4), e20170044. doi:10.1542/peds.2017-0044

[12] Matson, A., Soni, N., & Sheldon, J. (1991). C-reactive Protein as a Diagnostic Test of Sepsis in the Critically Ill. Anaesthesia and Intensive Care, 19(2), 182-186. doi:10.1177/0310057x9101900204 [11]

[13] McGill Physiology Virtual Lab. (n.d.). Blood Laboratory: Hemostasis: PT and PTT tests. Retrieved from https://www.medicine.mcgill.ca/physio/vlab/bloodlab/PT_PTT.htm

[14] “Partial Thromboplastin Time (PTT) Test: Purpose and Procedure.” [Online]. Available: https://www.healthline.com/health/partial-thromboplastin-time-ptt. [Accessed: 06-May- 2020].

[15] National Institutes of Heath, U.S. Department of Health and Human Services, National Cancer Institute, USA.gov, Biomarker, National Cancer Institute.

[16] M. D. Gonsalves and Y. Sakr, “Early Identification of Sepsis,” Current Infectious Disease Reports, vol. 12, no. 5, pp. 329–335, Sep. 2010.

[17] M. Barati et al., "Comparison of WBC, ESR, CRP and PCT serum levels in septic and non-septic burn cases," in Burns, vol. 34, Tehran, Iran University of Medical Science, 2008, pp. 770-774.

[18] "Procalcitonin: a promising diagnostic marker for sepsis and antibiotic therapy," Journal of Intensive Care, pp. 5-51, 2017.

[19] Roche Diagnostics International Ltd., Biomarkers and Sepsis, Switzerland: COBAS, 2012.

[20] Biomerieux, "FDA.gov," 10 November 2016. [Online]. Available: https://www.fda.gov/media/100863/download. [Accessed 28 September 2019].

[21] "VIDAS B.R.A.H.M.S PCT," BioMerieux Diagnostics, 2019. [Online]. Available: https://www.biomerieux-diagnostics.com/vidasr-brahms-pct. [Accessed 28 September 2019].

[22] S. Harbarth et al., "Diagnostic Value of Procalcitonin, Interleukin-6, and Interleukin-8 in Critically Ill Patients Admitted with Suspected Sepsis," American Thoracic Society Journal, vol. 164, no. 3, pp. 396-402, 2001.

[23] K. MM, R. Kusters, I. MJ and S. LM, "A PCT algorithm for discontinuation of antibiotic therapy is a cost-effective way to reduce antibiotic exposure in adult intensive care patients with sepsis," Journal of Medical Economics, pp. 944-53, 2015.

[24] A. Farooq and J. M. Colon-Franco, "Procalcitonin and its Limitations: Why a Biomarker's Best Isn't Good Enough," The Journal of Applied Laboratory Medicine, January 2019.

[25] I. Samsudin and S. D. Vasikaran, "Clinical Utility and Measurement of Procalcitonin," The Clinical Biochemist Reviews, pp. 59-68, April 2017.

[26] R. Venkataraman and J. A. Kellum, "Sepsis: Update in Management," Advances in Chronic Kidney Disease, vol. 20, no. 1, pp. 6-13, 22 December 2012.

[27] ACRO Biosystems, "Il-Molecule Information," ACRO Biosystems, 2017. [Online]. Available: https://www.acrobiosystems.com/L-326-IL-6.html. [Accessed 5 October 2019].

[28] T. Tanaka, M. Narazaki and T. Kishimoto, "Il-6 in Inflammation, Immunity and Disease," Cold Spring Harbor Perspectives in Biology, vol. 6, no. 10, October 2014.

[29] Roche Diagnostics International Ltd., Biomarkers and Sepsis, Switzerland: COBAS, 2012.

[30] L. Ma et al., "Role of interleukin-6 to differentiate sepsis from non-infectious systemic inflammatory response syndrome," Cytokine, vol. 88, pp. 126-135, December 2016.

[31] L. Bo, C. Yun-Xia, Y. Qin, Z. Yun-Zhou and L. Chun-Sheng, "Diagnostic value and prognostic evaluation of Presepsin for sepsis in an emergency department," Critical Care, vol. 17, no. 5, 2013.

[32] Q. Zou, W. Wen and X.-c. Zhang, "Presepsin as a novel sepsis biomarker," World Journal of Emergency Medicine, vol. 5, no. 1, pp. 16-19, 2014.

[33] "Creative Diagnostics," Creative Diagnostics Inc, 2009. [Online]. Available: https://www.creative-diagnostics.com/Chemiluminescence-Immunoassay-guide.htm. [Accessed 29 September 2019].

[34] T. Shozushima, G. Takahashi, N. Matsumoto, M. Kojika, E. Shigeatsu and Y. Okamura, "Usefulness of presepsin (sCD14-ST) measurements as a marker for the diagnosis and severity of sepsis that satisfied diagnostic criteria of systemic inflammatory response syndrome," Journal of Infection and Chemotherapy, vol. 17, no. 6, pp. 764-769, 2011.

[35] LSI Medience Corporation, "The Sepsis Marker: PATHFAST Presepsin," Mitsubishi Chemical Europe, [Online]. Available: https://www.pathfast.eu/presepsin. [Accessed 29 September 2019].

[36] Z. Zheng, L. Jiang, L. Ye, Y. Gao, L. Tang and Z. Zhang, "The accuracy of presepsin for the diagnosis of sepsis from SIRS: a systemic review and meta-analysis," Annals of Intensive Care, pp. 5-48, 8 December 2015.

[37] 2020. [Online]. Available: https://www.researchgate.net/figure/Incident-light-on-a- particle-Scattering-occurs-by-refraction-diffraction-and-reflection_fig6_266890765. [Accessed: 14- May- 2020]

[38] "Membrane Characterisation Equipment | Particle Size Measurements > 100 nm | European Membrane Institute (EMI) - University of Twente", Universiteit Twente, 2020. [Online]. Available: https://www.utwente.nl/en/tnw/emi/characterisation/particle-size- large/. [Accessed: 08- May- 2020]

[39] “Laser diffraction for particle sizing :: Anton Paar Wiki,” Anton Paar. [Online]. Available: https://wiki.anton-paar.com/en/laser-diffraction-for-particle-sizing. [Accessed: 07-May-2020].

[40] "Circular Aperture Diffraction", Hyperphysics.phy-astr.gsu.edu, 2020. [Online]. Available: http://hyperphysics.phy-astr.gsu.edu/hbase/phyopt/cirapp2.html. [Accessed: 07- May- 2020]

[41] Horiba.com. (2019). Fundamental Principles of Laser Diffraction - HORIBA. [online] Available at: https://www.horiba.com/us/en/scientific/products/particle-

characterization/technology/laser-diffraction/fundamentals-of-diffraction/ [Accessed 6 Oct. 2019].

[42] O. Baskurt, A. Temiz Artmann, and H. Meiselman, “Red blood cell aggregation in experimental sepsis,” J. Lab. Clin. Med., vol. 130, pp. 183–90, Aug. 1997.

[43] O. K. Baskurt and H. J. Meiselman, “Blood Rheology and Hemodynamics,” Semin Thromb Hemost, vol. 29, no. 05, pp. 435–450, Nov. 2003.

[44] M. Piagnerelli, K. Z. Boudjeltia, M. Vanhaeverbeek, and J.-L. Vincent, “Red blood cell rheology in sepsis,” Intensive Care Med., vol. 29, no. 7, pp. 1052–1061, Jul. 2003.

[45] N. Németh et al., “Early hemorheological changes in a porcine model of intravenously given E. coli induced fulminant sepsis,” Clin. Hemorheol. Microcirc., vol. 61, no. 3, pp. 479–496, Jan. 2016.

[46] Z. Isiksacan, O. Erel, and C. Elbuken, “A portable microfluidic system for rapid measurement of the erythrocyte sedimentation rate,” Lab. Chip, vol. 16, no. 24, pp. 4682–4690, 2016.

[47] M. Eberl and M. Davey, "Neutrophils," 2019. [Online]. Available: https://www.immunology.org/public-information/bitesized- immunology/cells/neutrophils.

[48] J. Cavenagh, "White Blood Cells," Surgery, pp. 61-64, 2007.

[49] "Lymphocyte: Blood Cell," 2019. [Online]. Available: https://www.britannica.com/science/lymphocyte.

[50] F. Ellet et al., "Diagnosis of sepsis from a drop of blood by measurement of spontaneous neutrophil motility in a microfluidic assay," Nature Biomedical Engineering, 2018.

[51] X.-F. Shen, K. Cao, J.-p. Jiang, W.-X. Guan and J.-F. Du, "Neutrophil dysregulation during sepsis: an overview and update," Journal of Cellular and Molecular Medicine , pp. 1687-1697, 2017.

[52] J. D. Lang and G. Matute-Bello, "Lymphocytes, apoptosis and sepsis: making the jump from mice to humans," BioMed Central, 2009.

[53] P. Forget, C. Khalifa, J.-P. Defour, D. Latinne, M.-C. Van Pel and M. De Kock, "What is the normal value of the neutrophil-to-lymphocyte ratio?," BMC Research Notes, 2017.

[54] "Motility," Biology Dictionary , [Online]. Available: https://biologydictionary.net/motility/. [Accessed 5 October 2019].

[55] S. Muldur, A. L. Marand, F. Ellett and D. Irimia, "Measuring spontaneous neutrophil motility signatures from a drop of blood using microfluidics," Methods Cell Biology , vol. 147, pp. 93-107 , 2018.

[56] “ISO 13485:2016,” ISO, 21-Jan-2020. [Online]. Available: https://www.iso.org/standard/59752.html. [Accessed: 01-May-2020].

[57] International Organization for Standardization, "ISO 11737-2:2009 - Sterilization of medical devices — Microbiological methods — Part 2: Tests of sterility performed in the definition, validation and maintenance of a sterilization process," 2009. [Online]. Available: https://www.iso.org/obp/ui/#iso:std:iso:11737:-2:ed-2:v1:en.

[58] International Organization For Standardization, "ISO 10993-1:2018 - Biological evaluation of medical devices — Part 1: Evaluation and testing within a risk management process," 2018. [Online]. Available: https://www.iso.org/obp/ui/#iso:std:iso:10993:-1:ed- 5:v2:en.

[59] International Organization For Standardization, "ISO/TC 76 - Transfusion, infusion and injection, and blood processing equipment for medical and pharmaceutical use," [Online]. Available: https://www.iso.org/committee/50044.html.

[60] International Organization For Standardization, "ISO 10993-11:2017 - Biological evaluation of medical devices — Part 11: Tests for systemic toxicity," 2017. [Online]. Available: https://www.iso.org/obp/ui/#iso:std:iso:10993:-11:ed-3:v1:en.

[61] U.S. Department of Health & Human Services (HHS), "The HIPAA Privacy Rule," [Online]. Available: https://www.hhs.gov/hipaa/for-professionals/privacy/index.html.

[62] U.S. Department of Health & Human Services (HHS), "Your Rights Under HIPAA," [Online]. Available: https://www.hhs.gov/hipaa/for-individuals/guidance-materials-for- consumers/index.html.

[63] “A classic, gold standard: The Westergren method for ESR measurement,” RR Mechatronics, Aug. 2015.

[64] “Erythrocyte Sedimentation Rate (ESR),” Lab Tests Online. [Online]. Available: https://labtestsonline.org/tests/erythrocyte-sedimentation-rate-esr. [Accessed: 18-Nov- 2019].

[65] R. Hashemi, A. Majidi, H. Motamed, A. Amini, F. Najari, and A. Tabatabaey, “Erythrocyte Sedimentation Rate Measurement Using as a Rapid Alternative to the Westergren Method,” Emerg, vol. 3, no. 2, pp. 50–53, 2015.

[66] Libretexts, “Some Properties of Liquids,” Chemistry LibreTexts, 13-Apr-2020. [Online]. Available: https://chem.libretexts.org/Bookshelves/General_Chemistry/Map:_Chemistry_- _The_Central_Science_(Brown_et_al.)/11:_Liquids_and_Intermolecular_Forces/11.3:_S ome_Properties_of_Liquids. [Accessed: 06-May-2020].

[67] J. L. G. Santander and G. Castellano, “Determination of the kinematic viscosity by the liquid rise in a capillary tube,” Revista Brasileira de Ensino de Física, vol. 35, no. 3, 2013.

[68] D. J. Patel and R. N. Vaishnav, “Some elementary hemodynamic concepts,” in Basic hemodynamics and its role in disease processes. Baltimore: University Park Press, 1980, ch. 2, pp. 83–90.

[69] S. Shin, J. H. Jang, M. Park, Y. Ku, and J. S. Suh, “A noble RBC aggregometer with vibration-induced disaggregation mechanism,” 2005.

[70] S. Shin, J. H. Jang, M. S. Park, Y. H. Ku, and J. S. Suh, “Light-transmission aggregometer using a vibration-induced disaggregation mechanism,” Review of Scientific Instruments, vol. 76, no. 1, p. 016107, Dec. 2004.

[71] E. Yeom, Y. J. Kang, and S.-J. Lee, “Changes in velocity profile according to blood viscosity in a microchannel,” Biomicrofluidics, vol. 8, no. 3, 2014.

[72] BioSpace, “Reducing False Positive Results for Sepsis with Steripath Improves Economic and Clinical Outcomes, Study Reports,” BioSpace, 17-Apr-2019. [Online].

Available: https://www.biospace.com/article/releases/reducing-false-positive-results-for- sepsis-with-steripath-improves-economic-and-clinical-outcomes-study-reports/. [Accessed: 06-May-2020].

[73] Makandi, P. (2020). Negative Effects of LCD Monitors. Retrieved from https://itstillworks.com/negative-effects-lcd-monitors-7478611.html

[74] How Products Are Made (2020). Acrylic Plastic. Retrieved from http://www.madehow.com/Volume-2/Acrylic-Plastic.html

[75] C. W. Seymour et al., “Delays From First Medical Contact to Antibiotic Administration for Sepsis,” Critical Care Medicine, vol. 45, no. 5, pp. 759–765, 2017.

[76] K. E. Rudd et. al., “Global, regional, and national sepsis incidence and mortality, 1990– 2017: analysis for the Global Burden of Disease Study,” The Lancet, vol. 395, no. 10219, Jan. 2020.

Appendix A – Interviews

Dr. Kate Madden, MD, MMSc Associate in Critical Care Medicine Boston Children’s Hospital and Instructor in Anesthesia, Harvard Medical School What is your experience with sepsis or SIRS-related illnesses in? As an attending physician in a pediatric intensive care unit (PICU), I care for many patients with suspected or proven sepsis. I have also been involved in some multicenter initiatives to increase consistency of response to suspected sepsis in terms of the actions of doctors and nurses. Through these collaborative, we have instituted tools to help doctors and nurses identify sepsis, communicate about the plan for care, and make informed decisions about the management of suspected sepsis.

What has your work revolved around? Mostly covered above. PICU and hospital-wide education about sepsis and need for timely care, development of tools to help nurses and doctors identify sepsis and communicate about the plan.

Can you please explain what are how sepsis is currently diagnosed in the hospital? What steps are involved? And who makes the final call? Sepsis is a set of clinical signs, and not truly a diagnosis per se. We have many patients in whom we may suspect sepsis, but a large proportion do not end up having a clear diagnosis. Only a small proportion have a bacteria or virus grow from a lab test that confirms the diagnosis. For research and quality improvement purposes, we use the judgement of the clinical team, usually the attending physician, as well as the specific treatments that go along with sepsis.

Who performs these steps? What qualifications are required? Not sure if above answers this? What steps specifically?

How successful are these current protocols in diagnosing sepsis? It depends how you define success. We currently want to screen a large number of patients for a few that might really have sepsis, as we know it is a very morbid condition and we don’t want to miss any patients. As a result, we screen many patients who do not really have sepsis, just fever and maybe one other SIRS criteria, but in the end will not develop severe sepsis or septic shock.

What are the challenges with these current hospital protocols? As with any large hospital initiatives – getting engagement from all different disciplines involved, changing culture, the burden of documentation on nursing especially, communication challenges.

What are the limitations when working with patients when diagnosing sepsis? How do infants differ from adults (if any)? Not sure exactly what this refers to? Infants are certainly much more difficult to assess in terms of mental status, focal symptoms, etc. We tend to screen very broadly for all infants who might have sepsis, because it can be quite easy to miss in young infants.

What is the largest challenge when diagnosing sepsis in a hospital setting? Many challenges, but probably the biggest is distinguishing fever and tachycardia (very common) from true sepsis that might progress to severe sepsis or septic shock.

What would you like to see in future sepsis diagnostic tools? More objective tools to diagnose sepsis at the bedside – measures of oxygen delivery to the tissues, organ function, and rapid microbiologic diagnostics. In pediatrics, we have a lot of challenges assessing mental status and thus brain perfusion, especially in young patients, so some bedside objective measure would be very helpful. Folks are working on bedside tools to evaluate for response from fluid resuscitation, including ultrasound tools, which could be helpful as we see the side effects of excessive fluid resuscitation in these patients as well. Knowing specific microbiological data would help tailor therapy and anticipate outcomes.

How would patient care be changed with faster diagnostic methods? More accurate and timely management.

Dr. Jouha Min, PHD, Postdoctoral Fellow in Center for Systems Biology at Mass General Hospital What is your experience with sepsis or SIRS-related illnesses? Sepsis is an often-fatal condition that arises when the body launches an overwhelming immune response to an infection that causes more damage to the body than the infection itself. A critical unmet need in combating sepsis is the lack of accurate early biomarkers that can alert clinicians to this potential life-threatening situation and allow them to take preventative action.

Why did you choose to research sepsis? When I joined the Center for Systems Biology at MGH, I learned about the IL-3 work that just got published by another PI at the Center, Dr. Filip Swirski, and I as an engineer thought that it would be a straightforward project to design and develop a point-of-care device to measure IL-3 levels in the patient’s blood to “predict” sepsis.

How did you choose what biomarker to use in your diagnostic method? Did you consider IL-6,8 or 10? Or Procalcitonin? The IBS (integrated biosensor for sepsis) prototype measures levels of a protein called cytokine interleukin-3 (IL-3) in the blood. We (our collaborator at the center) have IL-3 as an independent predictor of septic shock and death being produced by innate response activator (IRA) B cells following TLR activation. IL-3 operates upstream of key cytokines including TNFα, IL-1β and IL-6; high IL-3 level and can trigger a detrimental cytokine storm. Measuring IL-3 thus can give an early window to monitor immune responses through minimally invasive blood testing.

Why did you choose Interleukin-3 as your diagnostic method? Refer to my answer to Question #3.

Where did you get your ideas for your Interleukin-3 device? How it works: Simply put, the platform uses magnetic beads to directly and quickly extract target protein IL-3 from blood samples. The beads are adorned with antibodies and

electron mediators, and through a series of reactions, generate an electrical current which provides an analytical readout of IL-3 levels. Why magnetic beads approach: We advanced a portable biosensor consisting of a disposable kit for blood processing and an electrical detection system. The kit is used to capture IL-3 on magnetic beads and label it for electrochemical reaction; the detector then measures electrical currents for IL-3 quantification. This strategy has practical advantages: i) target protein (IL-3) can be enriched directly from blood; ii) the assay achieves high detection sensitivity through magnetic enrichment and enzymatic signal amplification; iii) based on the electrical measurements, the sensor can be easily miniaturized and easy-to-use.

What skills sets are required to use your device and who was the intended user? It was originally intended to be used by doctors and/or nurse practitioners in the emergency room or intensive care unit. But with further improvement (i.e., full automation), any technician (or even a caregiver) would be able to use it.

Would you consider combining different methods (such as Procalcitonin and IL-3)? Yes, our next generation device will be able to measure multiple markers (e.g., IL-3, TNFα, IL-1β, PCT, IL-6) for even more robust characterization of host response, further improving diagnostic accuracy.

What do you feel are aspects of sepsis that get overlooked? Medical doctors, scientists, and engineers are working their best to overcome the unmet needs in combating sepsis. But its such complex pathophysiology of systemic nature hampers us from inventing new ways to diagnose and/or treat. Long story short, we need a better scientific understanding of sepsis (i.e., mechanisms/pathways, new biomarkers).

How did you decide what needs were to be fulfilled by your project? Based on discussions with some doctors specializing infectious diseases as well as literature research, it was so evident what the unmet need is for sepsis.

What is the goal for sepsis diagnostics in the future? The immediate need for sepsis diagnostics is to develop a reliable clinical tool that could be readily integrated into clinical workflows, enabling timely diagnosis and proactive treatment of sepsis.

Dr. Michael Puskarich, MD, Associate Professor, University of Minnesota What is your experience with sepsis or SIRS-related illnesses? Clinically I am an emergency physician, so I see these patients regularly and have to differentiate patients with sepsis from those with non-infectious etiologies on every one of my shifts. This has become an increasingly important problem not only for patient care, but also with the advent of the CMS Sepsis Core measure. I have been intimately involved in developing internal EMR-based screening and recognition tools for sepsis which are terribly un- specific. I have also published extensively on the relationship between SIRS, sepsis, and various consensus definitions of the disease. I have also been involved in many sepsis trials that use these criteria for inclusion in the study.

What has your work revolved around? I am most interested in the role of metabolism in sepsis as a therapeutic target, related to my work describing the prognostic value of lactate. With this, as well as clinical trial work in the field in general, I have observed (along with many in the field) that the clinical consensus definitions suffer from poor specificity and variable sensitivity for the disease. The clinical presentation of sepsis differs from animal models leading to failure to translate animal results to improvements in human health. Part of my work is involved in finding ways to disambiguate early sepsis presentations from non-infectious etiologies, so as to only select patients most likely to benefit from a therapy prior to enrollment in a clinical trial.

What are the current methods utilized to diagnose sepsis? Is it successful? Clinically SIRS, "sepsis-3", procalcitonin occasionally have all been tried and they are not consistently successful. These tools are primarily ways for clinicians to make sure they are "getting the points" for treatment of sepsis patients and meeting CMS core measure success, but suffers from terrible usability. For true patient care, good clinicians rely on gestalt and experience combined with overall lab and diagnostic test results to diagnose sepsis more than any single tool, which in and of itself is also problematic due to the highly variable nature and clinical presentation of the disease. Sepsis is also confusing because it exists on a spectrum - it's not a "yes / no" despite many people wanting it to be. You don't go from routine flu to "sepsis," it exists on a spectrum with other infectious diseases that the body does or does not control on its own.

Who carries out these sepsis diagnostic tests? What skills sets are required? Generally, the used tools are based on vital signs and laboratory tests, including white blood cell count, measure of organ failure (creatinine, bilirubin, platelets), mental status, lactate as an indicator of disease severity, and others. An astute clinician is needed for excellent diagnostic acumen. Sometimes labs and vitals outperform the clinician, sometimes vice versa. Set standardized criteria almost always suffer from a severe over sensitivity and poor specificity. The consequence of this if applied too broadly is that by diagnosing patients without sepsis with sepsis ("just to be safe"), it diverts attention and resources of the doctor towards these patients who do not necessarily have sepsis and diverts it from other sick patients being cared for simultaneously by the doctor. In the emergency department, we frequently managed 10-20 patients simultaneously, so poor specificity tests have a real cost to OTHER patients in the department that is not considered in sepsis care mandates. Meanwhile, poor sensitivity tests lead to potentially missing patients that can have consequences that include death, as we know sepsis is a time sensitive disease process.

What is the goal for sepsis diagnostics in the future? Tests with an excellent balance of both sensitivity and specificity to know who time sensitive treatment must be delivered to ASAP. Alternatively, diagnostic tests that reliably determine the causative organism and / or pathophysiologic process that predominates in the patient at any given time could lead to tailored / personalized therapies.

What is the largest issue when diagnosing sepsis in a hospital setting? What are the biggest challenges with the current hospital methods? See above.

What symptoms prompt initial sepsis testing? Fever (or hypothermia) with hypotension is the most obvious. Fever with other signs of hemodynamic instability (tachycardia, high respiratory rate, high or low white blood cell count) can increase clinical suspicion, particularly if it persists after giving IV fluids. In elderly patients and immunosuppressed patients there is not always a fever, and malaise or fatigue can be the first symptoms. Some patients have respiratory distress without fever. Most patients with a fever, however, do not have sepsis. In general, sepsis is considered in patients having: a) a fever, b) hypothermia, c) hemodynamic instability, and d) vague symptoms in an elderly or immunocompromised patient. Unfortunately, this means 1/4 to 1/3 of all patients in the emergency department (nearly 100 patients per day in my ED) received at least a superficial consideration of sepsis, while 95% of these likely will not have it.

What would you like to see in a sepsis diagnostic tool? What functions would be useful? Are there any variables that need to be considered when creating such as tool such as time or resources?

1. specificity 2. sensitivity 3. rapid (has to have results in 15-30 minutes at longest). A point of care bedside device would be ideal but not necessary 4. likely blood based 5. simplicity - need to be able to be run by a routine laboratory technician or nurse with minimal training. 6. ease of interpretation - generally a yes / no, or yes / maybe / no answer will be required to ensure clinical uptake by clinicians. This is a sticking point, as I had mentioned previously, sepsis is not a yes / no disease. However, a "go/no go" answer will be required for broad uptake by clinicians downstream.

Appendix B – Pros and Cons of Different Testing Methods

Appendix C – Pairwise Analysis

Appendix D – Lab Gantt Chart

Appendix E – Micro-ESR Data and Analysis

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Appendix F – Capillary Fill Data and Analysis

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Appendix G – Laser Syllectometry Data and Analysis

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