DOCSLIB.ORG

Performance of the Maximum Modified Early Warning Score to Predict The

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Performance of the Maximum Modified Early Warning Score to Predict The ORIGINAL RESEARCH Performance of the Maximum Modified Early Warning Score to Predict the Need for Higher Care Utilization Among Admitted Emergency Department Patients 1 1 Corey R. Heitz, MD Department of Emergency Medicine, Wake Forest University School of Medicine, Winston-Salem, 1 John P. Gaillard, MD North Carolina. 1 Howard Blumstein, MD 2 2 Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, Doug Case, PhD 3 North Carolina. Catherine Messick, MD 1 3 Chadwick D. Miller, MD Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina. This study was supported in part by the Division of Healthcare Research and Quality of Wake Forest University Baptist Medical Center. Financial support for Dr. Miller is provided by a research scholar award from the Wake Forest University Translational Science Institute. Disclosure: Nothing to report. BACKGROUND: It is uncertain whether ED-calculated risk scores can predict required intensity of care upon hospital admission. This investigation examines whether versions of the Modified Early Warning Score (MEWS) predict high level of care utilization among patients admitted from the ED. METHODS: A retrospective chart review of 299 admissions was implemented. Exclusions prior to abstraction included pediatrics, cardiology, or trauma admissions. Using a data-gathering instrument, abstractors recorded physiologic parameters and clinical variables. Risk scores were calculated electronically. In contrast to the original MEWS, the MEWS Max was calculated using data from the entire ED visit. The primary outcome composite included all-cause mortality and higher care utilization within 24 hours. RESULTS: The final analysis contained 280 participants. 76 (27%) met the composite endpoint of death (n ¼ 1) or higher care utilization (n ¼ 76). The MEWS Max was associated with the composite outcome (OR¼l.6 [95% CI 1.3-1.8] for each one point increase). The MEWS Max had moderate predictive ability (C statistic: MEWS Max 0.73 [0.66-0.79]) but classified 82% of participants as intermediate (10-40%) risk. Inclusion of additional variables slightly improved the predictive ability (C statistic 0.76 [0.69–0.82]) and correctly reclassified 17% of patients as <10% risk. CONCLUSIONS: The MEWS Max has moderate ability to predict the need for higher level of care. Addition of ED length of stay and other variables to MEWS Max may identify patients at both low and high risk of requiring a higher level of care. Journal of Hospital Medicine 2010;5:E46–E52. VC 2010 Society of Hospital Medicine. KEYWORDS: care standardization, early warning scores, emergency department, level of care, patient safety, risk scores. Matching the severity of illness to the appropriate intensity are at risk for deterioration. Such tools for identification of of care is important for the effective delivery of medical inpatients at risk generally use ‘‘single threshold’’ models care. Overtriage to critical care units results in unnecessary triggered by a single abnormal physiologic value, or models resource consumption. Undertriage to the wards may result that combine multiple parameters into a summative in worsening of physiologic parameters1,2 that often go score.6,7 The performance of previously described risk strati- unnoticed or unaddressed for more than 24 hours.3 There- fication tools has generally been to exhibit high sensitivity fore, it is important for emergency department (ED) admis- at the sacrifice of low specificity and discriminatory value.8 sion decisions to be accurate with respect to the level of The value of these models as they apply in the emer- care. Because of the importance of this decision, objective gency department is less well characterized. Because criteria to aid in this decision process, if accurate, would derangements in physiologic parameters are common improve medical care delivery. among ED patients, one might expect that ‘‘single-thresh- Physiologic measurements and procedural interventions old’’ systems would exhibit high sensitivity at the expense of appear to predict the need for a higher level of care among specificity when applied to this population. In contrast, a inpatients.2,4,5 This knowledge has led to the development summative risk score may be better suited for the complex- of tools meant to identify inpatients on general wards who ities of illness in undifferentiated ED patients and offer 2010 Society of Hospital Medicine DOI 10.1002/jhm.552 Published online in wiley InterScience (www.interscience.wiley.com). E46 Journal of Hospital Medicine Vol 5 No 1 January 2010 better discriminatory value in this population. Summative domly selected for further review. Additional criteria were scoring systems have been shown to retain a higher speci- applied at the time the charts were reviewed to exclude ficity as the score increases compared to single-threshold those: without an ED record matching the date of admis- systems.8 sion, without 1 complete set of ED vitals, receiving mechan- The Modified Early Warning Score (MEWS)9 is a predic- ical ventilation at the time of presentation, or patients cur- tive tool for higher level of care that has been tested in the rently receiving hospice or ‘‘comfort care.’’ Charts from the ED setting. This tool produces a summative score using list of 500 were reviewed sequentially until the goal number temperature, respiratory rate, heart rate, level of conscious- of charts had been completed. The number of charts ness, and systolic blood pressure. In a single-site study from reviewed was selected to allow relatively precise 95% confi- the United Kingdom, MEWS, when calculated at the time of dence intervals [CIs] around sensitivity (Æ10%) based on the ED presentation, did not improve decision making over a assumptions of 80% sensitivity and a 20% incidence of the commonly used triage system, exhibiting inadequate sensi- primary outcome. Based on this, the intent was to abstract tivity in identifying patients who would be admitted to the information from 300 patient charts. intensive care unit (ICU).10 However, as a result of the care delivered in the ED, patients’ conditions can change signifi- Study Protocol cantly throughout their stay. Therefore we postulate that the A standardized data abstraction template was created. Data MEWS calculated at a single time in the ED (eg, at the time abstractors included 2 physicians and 2 nurses. Group train- of admission) is not the most accurate predictor of care ing for the abstractors was provided by the primary investi- intensity requirements. gator and included performance review and feedback until The primary objective of this research was to add to the competence was demonstrated. Data abstractors used the 10 literature provided by Subbe et al. by describing the per- paper copy of the ED nursing notes (and physician notes if formance characteristics and discriminatory ability of the clarification required) to abstract data from the medical most abnormal MEWS (MEWS Max) score during the entire record. Abstractors were not aware of the patient’s outcome ED stay in predicting the need for higher levels of care at the time of data abstraction as this information was con- among ED patients presenting to a tertiary care facility in tained in a separate database. During the chart review, and North America. blinded to the abstractors, 25 charts were selected for abstraction by all data abstractors to allow calculation of Patients and Methods interobserver agreement. Study Design Clinical outcomes were determined by referencing hospi- To determine the performance characteristics of the MEWS tal databases and the medical record if clarification was in ED patients, we used a structured explicit retrospective needed. The admission bed location and changes in patient chart review on a random sample of ED patients being location throughout the hospital stay were used to track the admitted to the hospital. need for a higher level of care. The outcome of death was determined by cross-referencing study participants with Study Setting hospital mortality data, and the medical record, if needed. The study was conducted at 1 tertiary care academic medi- cal center in the United States, consisting of 830 beds, Predictor Score Calculation approximately 125 of which provide a higher level of care, Abstracted data were used to calculate the MEWS score defined as intensive care, intermediate care, or acute care. according to the criteria specified in Table 1 at the initial The ED volume in 2005 was 75,000 with an admission rate ED presentation (MEWS Initial), the maximum during the of 20%. In the ED, patients are primarily seen by residents ED stay (MEWS Max), and prior to admission (MEWS who are supervised by board-certified or board-eligible Admit). Parameters not repeated after arrival were carried emergency medicine attendings. forward from the most recent recording. An adaptation of the MEWS score was required by replacing the alert/verbal/ Study Population painful/unresponsive (AVPU) scale to determine the level of All patients presenting to the ED of Wake Forest University consciousness with the Glascow Coma Scale (GCS), a con- 13,14 Baptist Medical Center in 2005 were considered for inclu- version that has been previously described. sion. From these patients, a listing was created of all hospi- tal admissions through the ED in 2005. Because trauma and Clinical Endpoint Definitions and Outcomes cardiology patients have disease-specific risk stratification ‘‘Need for higher level of care’’ was defined as initial admis- tools that are used to guide admission,11,12 they were then sion from the ED or transfer within 24 hours to a nonfloor removed from this list and excluded. Additionally, pediatric bed (acute care, intermediate care unit, or critical care unit). patients were excluded from this listing as the MEWS score Acute care beds at the study hospital have a lower bed-to- relies on vital sign abnormalities, which have varying ranges nurse ratio and more intensive monitoring (beside vs.
Load more

Recommended publications
  • The Inclusion of Delirium in Version 2 of the National Early
    ORIGINAL ORIGINAL RESEARCH RESEARCH ClinicalClinical Medicine Medicine 2019 2017 Vol Vol 19, 17, No No 2: 6:104–8 104–8 CORE Metadata, citation and similar papers at core.ac.uk Provided by Bradford Scholars The inclusion of delirium in version 2 of the National Early Warning Score will substantially increase the alerts for escalating levels of care: findings from a retrospective database study of emergency medical admissions in two hospitals Authors: M o h a m m e d A M o h a m m e d , A M u h a m m a d F a i s a l , B D o n a l d R i c h a r d s o n ,C A n d y S c a l l y , D R o b i n H o w e s , E K e v i n B e a t s o n , F S a l l y I r w i n G a n d K e v i n S p e e d H B a c k g r o u n d emergency medical patients. Rigorous evaluation of NEWS2 The National Early Warning Score (NEWS) is being replaced is required before widespread implementation because the with NEWS2 which adds 3 points for new confusion or delirium. extent to which staff can cope with this increase without We estimated the impact of adding delirium on the number of adverse consequences remains unknown. medium/high level alerts that are triggers to escalate care.
    [Show full text]
  • The Impact of Early Warning Scoring Systems
    General care Insights The impact of Early Warning Scoring systems: Better health outcomes, lower cost of care, and improved staff, patient and family experience Unmet needs and solutions: Response to the burden of patient deterioration Sizing the problem of patient deterioration Patient deterioration is a significant clinical and financial Patient deterioration may also result in a significant direct burden for patients, providers, and healthcare systems.2 economic burden for providers. Patients experiencing (Figure 1) Clinicians are increasingly treating older, sicker adverse events are associated with higher direct populations at risk for complications and in-hospital healthcare costs.9 adverse events.3 As the volume of hospitalizations for these patients continues to rise, providers are challenged A review of the literature highlights this trend, especially to manage more acute, resource intensive populations in among potentially preventable conditions: a resource-constrained environment.3 • Surgical complications were associated with a nearly $20K increase in hospital costs and a pronounced Compounded with a scarcity of beds in higher acuity decrease in contribution margin10 care areas, patient status may be underestimated, and • Median costs associated with sepsis are markedly patients may be admitted or transferred to lower acuity higher than in non-septic patients per case ($10K care areas while still at risk for deterioration and resulting United Kingdom, $23K Germany)11 serious adverse events. • $3,580 average cost per day of hospitalization for This scenario may be attributable to a relative lack of recipients of cardio pulmonary resuscitation12 resources in lower acuity settings, a significant decrease in nurse to patient ratios, and/or a lack of care coordination.
    [Show full text]
  • Modified Early Warning Scoring (MEWS) Tools Including Sepsis Screening Criteria
    Modified Early Warning Scoring (MEWS) Tools Including Sepsis Screening Criteria Literature Review Jamie K. Roney, MSN, RN-BC, CCRN-K Evaluating the Evidence for Use in Adult Medical-Surgical & Telemetry Patients Authors Jamie K. Roney, MSN, RN-BC, CCRN-K Erin Whitley, BSN, RN Jessica Maples, BSN, RN-BC Kimberley A. Stunkard, BSN, RN JoAnn D. Long, PhD, RN, NEA-BC Authors have no conflicts of interest, sponsorship, or commercial support to disclose Learning Objectives The learner will be able to: 1. Identify discoveries from a review of literature regarding combining sepsis screening criteria with MEWS tools. 2. Identify gaps in available published research linking MEWS usage with decreased failure to rescue events. Sepsis Outcomes MEWS Tools Screening Aims of Literature Review 1. Explore impact of MEWS tool usage on patient mortality & failure to rescue events in hospitalized adult medical- surgical/telemetry patients as reported in the literature 2. Validate MEWS physiologic screening parameters for incorporation of international sepsis identification standard values Provides foundation for MEWS tool adaptation recommendations for institutional use. Evaluating literature reporting MEWS tools impact & included screening criteria Background MEWS Tools Few studies have tested Patient Condition reliability & Subtle validity changes may go undetected Evidence Paucity of Patient Outcome data supports Screening outcome may decrease claims cardiopulmon ary arrests A review and evaluation of the MEWS literature was conducted Methods Objective Objective Sought to 5 Reviewers Sought to determine validate level of MEWS evidence & instruments’ examine impact on impact of use Literature significant of existing PRISMA* Evidence Table clinical tools in patient concluding Review outcomes what prior to physiologic making parameters recommendat should be Synthesis ions for included in incorporation the MEWS into clinical tool.
    [Show full text]
  • Using Early Warning Score in GE B105/B125 Patient Monitor for Covid-19 Patients
    Using Early Warning Score in GE B105/B125 Patient Monitor for Covid-19 patients gehealthcare.com ITALY Role of EWS for Covid-19 cases Recommendation report written by Emanuele Nicastri et all at As the COVID-19 pandemic spreads, it is straining the overall National lnstitttute for the Infectious Diseases "L. Spallanzani", healthcare infrastructure at all locations across the globe. The IRCCS, Rome, Italy, recommends course of treatment based on number of doctors and nurses are not sufficient compared to MEWS score for COVID-19 patients20 the inflow of patients. In such a resource constraint and highly Source: Emanuele Nicastri et al. Recommendations for COVID-19 Clinical contagious environment, it is even more important to monitor Management. National Institute for Infectious Diseases L. Spallanzani", IRCCS, Rome, the condition of the patient and take the right clinical decisions Italy. Infectious Disease Reports 2020; 12:8543 before it's too late. CLINICAL OBSERVATION EWS MONITORING FREQUENCY Based on Interim Clinical Guidance for Management of Patients Asymptomatic or mild with Confirmed Coronavirus Disease (COVID-19) by CDC NA 1-3 times a day infection Among patients who developed severe disease Stable patient presenting with respiratory/ systemic <3 Every 8 hours • Medium time to dyspnea: 5 to 8 days symptoms • Median time to ARDS (acute respiratory distress syndrome): Patient affected with 8 to 12 days respiratory symptoms, 3-4 Every 2 -4 hours • Median time to ICU admission ranged from 10 to 12 days. clinically unstable but not critical 26% to 32% of hospitalized patients need ICU Care Critical Patients >4 Continuous ARDS among COVID-19 Patients • 20% to 42% for hospitalized patients Swiss Society of Intensive Care Medicine • 67% to 85% of ICU Patients Inpatient management according to the Early Warning Score (EWS) Clinicians should be aware of the potential for some patients to rapidly deteriorate one week after illness onset.
    [Show full text]
  • National Early Warning Score Systems That Alert to Deteriorating Adult Patients in Hospital
    pat hways National Early Warning Score systems that alert to deteriorating adult patients in hospital Medtech innovation briefing Published: 18 February 2020 www.nice.org.uk/guidance/mib205 This advice replaces MIB79. Summary • The 5 technologies described in this briefing are integrated software systems that output the national early warning score for adult patients in hospital. • The innovative aspects are the potential for more accurate alerts and the greater availability of this information to identify a deteriorating adult patient, thereby reducing avoidable harm and making services more efficient. • The intended place in therapy would be replacing paper-based charts that record observations and manually calculate the national early warning score. • The main points from the evidence summarised in this briefing are from 2 prospective studies and 1 multicentre retrospective observational study in the NHS. This limited evidence base suggests that electronic systems that send out national early warning score-based alerts can release staff resources, reduce unplanned admissions to intensive care and reduce the frequency of cardiac arrests, compared with standard care. © NICE 2020. All rights reserved. Subject to Notice of rights (https://www.nice.org.uk/terms-and- Page 1 of conditions#notice-of-rights). 18 National Early Warning Score systems that alert to deteriorating adult patients in hospital (MIB205) • Key uncertainties are the lack of evidence for national early warning score-based alerts from these technologies in the NHS. Further research could improve understanding of how best to use them, and help determine the cost and resource impact. • The cost of early warning systems typically ranges from £30,000 to £90,000 for initial system installation, configuration and set up, with ongoing annual licence costs from £0.35 to £0.70 per acute bed, per day (exclusive of VAT).
    [Show full text]
  • Early Warning Systems
    HOSPITAL CHRONICLES 2012, VOLUME 7, SUPPLEMENT 1: 37–43 CARDIAC NURSING ROUNDTABLE Early Warning Systems Daphne Georgaka, RN, Maria Mparmparousi, RN, Michael Vitos, RN INTRODUCTION Coronary Care Unit, Evagelismos Currently, medical general wards tend to have a higher number of severely sick Hospital, Athens, Greece patients with a long period of critical illness. In addition, there is a growing recognition that several indicators of acute deterioration are being missed by both nurses and doc- tors. The consequences of these are an increase in the number of adverse events, such as cardiac arrest1 and in the number of patients admitted or readmitted in critical care units,2 contributing undoubtedly to higher mortality rates. As a result, many initiatives have been designed trying to reduce such problems, including the development of early warning scoring systems with the perspective of timely medical response. The aim of this project is to elucidate the dimensions of early warning systems (EWS), to raise discussion on their validity and to stimulate health leadership in in- KEY WORDS: early warning systems; health care; health risk; critical care; troducing early warning systems into health care mechanisms. After having collected intensice care unit; nursing care and presented data from several recent articles on the topic, this project intends to discuss about the introduction and function of EWS. WHAT EARLY WARNING SYSTEMS ARE The application of EWS is not a novel approach restricted solely to medical fields. These systems were first designed for the timely identification of ecological and finan- cial risks. The need for gathering data and information on time, sharing information within different regimes and establishing models for calculation and analysis methods introduced the use of these “tools”.3 These systems were initially applied for the detec- tion of economic weakness and vulnerability.
    [Show full text]
  • New Zealand Early Warning Score Vital Sign Chart User Guide 2017
    New Zealand Early Warning Score Vital Sign Chart User Guide 2017 July 2017 Contents Contents ............................................................................................................................... 2 Figures .............................................................................................................................. 3 1. Introduction .................................................................................................................... 4 2. Chart overview ............................................................................................................... 4 2.1. Section 1: graphing area ............................................................................................. 5 2.2. Section 2: escalation pathway .................................................................................... 5 2.3 Section 3: NZEWS modifications ................................................................................. 5 2.4. Section 4: additional parameters ................................................................................ 6 3. Clinical use .................................................................................................................... 6 3.1. Documenting vital signs .............................................................................................. 6 3.1.1 Respiratory rate .................................................................................................... 6 3.1.2. Supplementary oxygen........................................................................................
    [Show full text]
  • The Admission Hamilton Early Warning Score (HEWS)
    Original Research The Admission Hamilton Early Warning Score (HEWS) Predicts the Risk of Critical Event during Hospitalization Benjamin Tam BHSc MD, Michael Xu BHSc, Michelle Kwong BHSc Cand., Christine Wardell BHSc Cand., Andrew Kwong BHSc Cand., Alison Fox-Robichaud MSc MD FRCPC About the Authors: Lead author Benjamin Tam is an internist and a trainee in the Adult Critical Care Medicine residency program at McMaster University in Hamilton, Ontario. His interest is in patient safety, particularly the use of rapid response teams and early warning scores to reduce critical events and improve the patient experience. Co-authors Michael, Xu, Michelle Kwong, Christine Wardell, Andrew Kwong are BHSc Candidates at McMaster University. Principal investigator and corresponding author Alison Fox-Robichaud is with the Department of Medicine, Division of Critical Care, Faculty of Health Sciences, McMaster University. Correspondence may be directed to [email protected]. Benjamin Tam Abstract Background: Early warning scores detect patients at risk of deterioration in hospital. Our objective was to first, demonstrate that the admission Hamilton Early Warning Score (HEWS) predicts critical events and second, estimate the workload required to identify critical events during hospitalization. Methods: We prospectively identified a consecutive cohort of medical/surgical patients for retrospective review. Critical events were defined as a composite of inpatient death, cardio-pulmonary arrest or ICU transfer. Likelihood of a critical event during hospitalization and the number needed to evaluate to detect a critical event was based on highest admission HEWS. Results: We found 506 critical events occurred in 7130 cases. HEWS identified graduated levels of risk at admission. We found 2.6 and 1.8 patients needed to be evaluated in the ‘high-risk’ and very ‘high-risk’ subgroups to detect a critical event.
    [Show full text]
  • (INEWS) V2 (Previously NEWS) National Clinical Guideline No
    Irish National Early Warning System (INEWS) V2 (previously NEWS) National Clinical Guideline No. 1 September 2020 National Patient Safety Office Oifig Náisiúnta um Shábháilteacht Othar The Nati onal Early Warning Score (NEWS) Nati onal Clinical Guideline has been updated and revised by the Irish Nati onal Early Warning System (INEWS) Guideline Development Group (GDG) under the auspices of the HSE Nati onal Deteriorati ng Pati ent Recogniti on and Response Improvement Programme (DPIP). Using this Nati onal Clinical Guideline This Nati onal Clinical Guideline applies to adult (≥ 16 years) non-pregnant pati ents in acute setti ngs. It does not apply to children or pati ents in obstetric care. This Nati onal Clinical Guideline is relevant to all healthcare professionals working in acute setti ngs. Disclaimer NCEC Nati onal Clinical Guidelines do not replace professional judgment on parti cular cases, whereby the clinician or health professional decides that individual guideline recommendati ons are not appropriate in the circumstances presented by an individual pati ent, or whereby an individual pati ent declines a recommendati on as a course of acti on in their care or treatment plan. In these circumstances the decision not to follow a recommendati on should be appropriately recorded in the pati ent’s healthcare record. Users of NCEC Nati onal Clinical Guidelines must ensure they have the current version (hardcopy or soft copy) by checking the relevant secti on in the Nati onal Pati ent Safety Offi ce on the Department of Health website: htt ps://www.gov.ie/en/collecti on/c9fa9a-nati onal-clinical-guidelines/ Published by: The Department of Health, Block 1, Miesian Plaza, 50-58 Lower Baggot Street, Dublin 2, D02 VW90, Ireland.
    [Show full text]
  • (NEWS2) for COVID-19
    Carr et al. BMC Medicine (2021) 19:23 https://doi.org/10.1186/s12916-020-01893-3 RESEARCH ARTICLE Open Access Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Ewan Carr1*† , Rebecca Bendayan1,2†, Daniel Bean1,3, Matt Stammers4,5,6, Wenjuan Wang7, Huayu Zhang8, Thomas Searle1,2, Zeljko Kraljevic1, Anthony Shek9, Hang T. T. Phan4,5, Walter Muruet7, Rishi K. Gupta10, Anthony J. Shinton6, Mike Wyatt11, Ting Shi8, Xin Zhang12, Andrew Pickles1,2, Daniel Stahl1, Rosita Zakeri13,14, Mahdad Noursadeghi15, Kevin O’Gallagher13,14, Matt Rogers11, Amos Folarin1,3,16,17, Andreas Karwath18,19,20, Kristin E. Wickstrøm21, Alvaro Köhn-Luque22, Luke Slater18,19,20, Victor Roth Cardoso18,19,20, Christopher Bourdeaux11, Aleksander Rygh Holten23, Simon Ball20,24, Chris McWilliams25, Lukasz Roguski3,16,19, Florina Borca4,5,6, James Batchelor4, Erik Koldberg Amundsen21, Xiaodong Wu26,27, Georgios V. Gkoutos18,19,20,24, Jiaxing Sun26, Ashwin Pinto6, Bruce Guthrie8, Cormac Breen7, Abdel Douiri7, Honghan Wu3,16, Vasa Curcin7, James T. Teo9,13†, Ajay M. Shah13,14† and Richard J. B. Dobson1,2,3,16,17† Abstract Background: The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. Methods: Training cohorts comprised 1276 patients admitted to King’s College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020.
    [Show full text]
  • Vital Signs and Introduction to NEWS Samantha Coulter, 4Th Year Medical Student Dr Jason Long, Director of Clinical Skills
    Vital Signs and Introduction to NEWS Samantha Coulter, 4th Year Medical Student Dr Jason Long, Director of Clinical Skills Contents Learning Outcomes ........................................................................................................................... 3 Introduction to Vital Signs ................................................................................................................. 3 National Early Warning Score ............................................................................................................ 3 Assessment of Radial Pulse ............................................................................................................... 4 Method ..................................................................................................................................... 4 Blood Pressure .................................................................................................................................. 5 What Blood Pressure Numbers Mean ........................................................................................ 5 Hypertension vs Hypotension .................................................................................................... 6 Introduction to Sphygmomanometry ......................................................................................... 6 Blood Pressure Equipment ........................................................................................................ 7 Method ....................................................................................................................................
    [Show full text]
  • Predictive Value of Modified Early Warning Score (MEWS)
    Open access Original research BMJ Open: first published as 10.1136/bmjopen-2020-041882 on 15 March 2021. Downloaded from Predictive value of Modified Early Warning Score (MEWS) and Revised Trauma Score (RTS) for the short- term prognosis of emergency trauma patients: a retrospective study Zhejun Yu,1 Feng Xu,2 Du Chen 1 To cite: Yu Z, Xu F, Chen D. ABSTRACT Strengths and limitations of this study Predictive value of Modified Objectives This study aimed to assess the predictive Early Warning Score (MEWS) value of the Modified Early Warning Score (MEWS) and ► To the best of our knowledge, no other study has and Revised Trauma Score (RTS) Revised Trauma Score (RTS) for emergency trauma for the short- term prognosis of done a statistical comparison of these two scoring patients who died within 24 hours. emergency trauma patients: a systems in the field of early emergency trauma. Design A retrospective, single- centred study. retrospective study. BMJ Open ► Focus on early decision- making and rational use Setting This study was conducted at a tertiary hospital in 2021;11:e041882. doi:10.1136/ of trauma scoring system, to improve early triage Southern China. bmjopen-2020-041882 efficiency. Participants A total of 1739 patients with acute trauma, ► The retrospective nature of the study was a limita- ► Prepublication history for aged 16 years or older who presented to the emergency this paper is available online. tion, as it was not conducted in real-time and was department from 1 November 2016 to 30 November 2019, To view these files, please visit limited by subjective differences in artificial statisti- were included.
    [Show full text]