ORIGINAL ARTICLE

Assessment of Four Mortality Prediction Models in Patients with

Bushra Jamil, Kiran Alam Qureshi, Maria Khan, and Veerta Ali Ujan. Departments of , Pathology and Microbiology, The Aga Khan University Hospital, Karachi, Pakistan.

Abstract

Early recognition of sepsis and the rapid institution of and laboratory parameters were studied in patients admitted to therapy are absolutely essential for appropriate management of the ICU with severe sepsis and septic . The outcome patients admitted to the hospital. Both score-generating clinical predicted by calculations defined in the models was compared tools and clinical acumen are important for identifying the sick, with the actual outcome, in order to assess the reliability and while early intervention in acute deterioration is beneficial, utility of these systems in predicting outcome of sepsis. before and after ICU admission. Several scoring systems have been devised which attempt to identify risk factors and predict Methods outcome of different patient groups. The purpose of this pilot study was to assess the value of four mortality risk scoring Case records of 20 patients who were admitted to the systems, i.e. Mortality Probability Models (MPM) - admission, ICU with the diagnosis of sepsis, over a period of 3 months in MPM -24 hours, Simplified Acute Physiology Score (SAPS) the year 2000, were studied retrospectively. Five patients had II and Acute Physiology and Chronic Health Evaluation to be excluded because of insufficient data. The patients were (APACHE) II, in predicting outcome in patients admitted to selected randomly and based on the data available, were analyzed the intensive care unit with sepsis. The expected outcome was according to the following scoring systems: Mortality Probability calculated according to the specifications of each system and Models (MPM) - admission, MPM -24 hours, Simplified Acute was compared to the actual outcome. Physiology Score (SAPS) II and Acute Physiology and Chronic Health Evaluation (APACHE) II. Inclusion criteria included Key words age >18 year, signs and symptoms of local infection (cellulitis, septic arthritis, LRTI, UTI) or body temperature >38oC or < Mortality risk prediction models, sepsis 36oC orally with one of the following: , defined as systolic blood pressure <90 mmHg or its reduction by >40 Introduction mmHg from patient’s baseline, in the absence of other causes for hypotension, tachycardia defined as a pulse rate >90 beats Infections are a leading cause of morbidity and mortality per minute, tachypnea defined as respiratory rate >20 breaths in Pakistan. Delay in diagnosis of serious infections and per min or PCO2 <32 torr, white blood cell count >12,000 inappropriate or inadequate management lead to the development cells/cumm or <4000 cells/cumm, or with a differential count of systemic inflammatory response, followed by showing >10% band neutrophil forms. and death. Proper management of individual patients demands early recognition, accurate etiological diagnosis and appropriate Exclusion criteria included age less than 18 years, treatment. In sepsis, the extent and involvement of different admission due to extensive burns and coronary artery disease. organ systems has been shown to affect outcome. This Presence of significant coexisting illnesses was noted. The observation may allow the clinician at the bedside to recognize expected outcome was calculated on line at the official website and respond early to adverse patterns and changes of organ of French Society of Anesthesia and Intensive Care (sfar.org), system dysfunction in septic patients. Such an assessment can according to the specifications of each system. The predicted be facilitated and made more objective through the use of death rate was compared with the actual outcome of sepsis in mortality prediction models. While several systems or models each patient. Sensitivity, specificity and positive predictive have been designed for intensive care unit (ICU) patients, there value of each system were also determined. are some models which can be applied to non-ICU patients, who are not monitored invasively. Results We conducted this pilot study to assess four mortality prediction models in our patients with sepsis. Various clinical The study patients included 11 males and 5 females. Age ranged from 18 to 79 years with a mean of 52.1 years. Corresponding author: Bushra Jamil, Assistant Professor, Dept. of Females were slightly older with a mean age of 57.4 years; Medicine, Pathology and Microbiology, The Aga Khan University Hospital, Stadium Road, Karachi, Pakistan. mean age for males was 46.8 years. Most of the patients had Email: [email protected] more than one significant associated illnesses (table 1).

Oct - Dec 2004 . 93 Table 1. Significant coexisting illnesses in sepsis patients Table 3. Sensitivity, specificity and positive predictive value of mortality prediction models Co-morbid conditions N (%) Diabetes mellitus 6 (40) Scoring system Sensitivity (%) Specificity (%) PPVa Renal failure (acute and chronic) 5 (33.3) APACHE II 100 at score of >22 45.4 0.45 Chronic liver disease 4 (26.2) SAPS II 87.5 at score of >39 55.5 0.636

Hematological disorders a 3 (20) MPM admission 80 at score of >20 50 0.727 IHD/CMPb 2 (13.3) MPM 24 h 77.7 at score of >19.4 42.8 0.636 Gut perforation 2 (13.3) c NHL 1 (6.6) apositive predictive value Elephantiasis 1 (6.6) Mitral incompetence 1 (6.6) Hypertension 1 (6.6) Discussion Liver abscess 1 (6.6) Diverticular disease 1 (6.6) Severe sepsis and septic shock are major reasons for hospital and intensive care unit admissions. Data from the Aga a Acute lymphocytic leukemia (2) aplastic anemia (1) Khan University Hospital shows that over the last 15 years, the b Ischemic heart disease/ cardiomyopathy c Non-Hodgkin lymphoma overall mortality due to sepsis has remained around 36.6%. Mortality rate in patients with septic shock has been a staggering 81%. This is excessive in comparison mortality rates ranging 1,2 Diabetes mellitus was the commonest associated illness from 40-60% quoted in literature . In critically ill patients in the intensive care unit (ICU) who are already compromised followed by renal failure and chronic liver disease. A significant because of coexisting serious co-morbidities, septic shock may number of patients had more than one co-morbid conditions be associated with higher mortality3. It has been shown that concomitantly. Three patients did not have any underlying the systemic inflammatory response to severe infection evolves illnesses; one of them was 27 weeks pregnant. Infections of the in stages from sepsis to severe sepsis to septic shock with skin and soft tissues, including cellulitis and necrotizing fasciitis corresponding increases in the proportion of patients with were the commonest infections preceding sepsis and septic positive blood cultures, end organ failure and crude mortality4. shock; pneumonia was also common (table 2). Ten patients It is logical to presume that the progression of sepsis and 28- expired (66.6%), 3 recovered from their illness and outcome day mortality may be influenced by effective early interventions5. of 2 patients who were transferred to another facility could not Even those patients who have developed end organ damage be ascertained. and shock might benefit from early identification and rapid support. Studies have shown that the crude mortality of all patients in an intensive care as well as that for patients with Table 2. Site of infection in patients with sepsis septic shock in an ICU decreases if physicians remain in the hospital and are supervised by subspecialists trained in critical care 6,7. The ability of the highly skilled ICU personnel and the Site of infection N (%) ability of the sophisticated patient monitors would be expected Skin and soft tissues 6 (40) to have detected the onset of shock at an earlier point in time. Lung 4 (26.2) Additionally, the ICU has highly skilled physicians, nurses and Gut perforation 2 (13.3) support personnel who have the ability to evaluate patients Urinary tract 1 (6.6) more frequently with continuous assessment of vital signs. The Endocarditis 1 (6.6) typical ICU patient is monitored with sophisticated equipment Encephalitis 1 (6.6) which is expected to alert the ICU staff to critical alterations in the patient’s clinical status. The result would be earlier detection and treatment of septic shock. In contrast, general ward patients do not have access to the same frequency or The sensitivity and specificity of all the scoring systems intensity of assessments and monitors, resulting in delays in were calculated and results are shown in table 3. The sensitivity the detection of shock onset3. The prolonged period of of APACHE II for predicting mortality was 100% at the score hypoperfusion of critical organ beds, such as liver, brain, heart, of >22 which translates into a predicted death rate of >42.4. kidney and gastrointestinal tract may give rise to multiple organ For the rest of the scoring systems, sensitivity ranged from 77 dysfunction and failure, which is associated with a high rate of to 87%. Specificity was highest at 55.5% for SAPS II. morbidity and mortality 8.

94 . Infectious Diseases Journal of Pakistan In septic patients, the number of organ systems with early recognition of sepsis-related complications in a large impaired function is important because it correlates with clinical cohort of our patient population, before recommending them 9,10,11 outcome . It has been shown that the pattern and evolution as essential tools for bed side evaluation of patients with sepsis. of organ system dysfunction over the first 3 days of sepsis is significantly related to 30-day mortality 12. This observation References may potentially allow the clinician at the bedside to recognize and respond early to adverse patterns and changes of organ 1. Bone RC. Gram negative sepsis: Background, clinical system dysfunction in septic patients. Clinical assessment can features, and intervention. Chest 1991;100:802-808 be facilitated and made even more objective through the use 2. Parrillo JE, Parker MM, Natanson C, et al. Septic of mortality prediction models. While such systems have been shock in humans: Advances in the understanding of designed for ICU patients, some of these can easily be applied pathogenesis, cardiovascular dysfunction, and therapy. to non-ICU patients, who are not monitored invasively. Ann Intern Med 1990;113:227-242 3. Balk RA. Outcome of septic shock: Location, location, However, debate still continues about the accuracy of location. Crit Care Med 1998; 26:983-984 these scoring systems, their efficiency in assessing the severity 4. Rangel-Frausto MS, Pittet D, Costigan M, et al. The of illness and whether they have a prognostic role in the natural history of systemic inflammatory response estimation of the illness outcome. Additionally, these tools have syndrome (SIRS). A prospective study. JAMA 1995; to be validated in the population in question before they are 273:117-123 adopted for outcome prediction and decision making. 5. Lundberg JS, Perl TM, Wiblin T, et al. Septic shock: An analysis of outcomes for patients with onset on We studied Mortality Probability Models (MPM) - hospital wards versus intensive care units. Crit Care admission, MPM -24 hours, Simplified Acute Physiology Score Med 1998; 26:1020-1024 (SAPS) II and Acute Physiology and Chronic Health Evaluation 6. Li YC, Phillips MC, Shaw L, et al. Onsite physician (APACHE) II to assess their utility in predicting mortality in staffing in a community hospital intensive care unit. our patients. Impact on test and procedure use and on patient outcome. JAMA 1984; 252:2023-2027 It has been emphasized that the calculation of a risk 7. Reynolds HN, Haupt MT, Thill-Baharozian MC, et assigned to a measured score is an epidemiologic tool, and al. Impact of critical care physician staffing on patients should not be used as a single patient prevision tool. However, with septic shock in a university hospital medical sequential calculations may be of immense importance in early recognition of deterioration and the need for more aggressive intensive care unit. JAMA 1998; 260:3446-3450 intervention in patients who present at an early stage of sepsis. 8. Swank GM, Dietch EA. Role of gut in multiple organ Through early diagnosis and intervention, we may be able to failure: Bacterial translocation and permeability decrease mortality associated with sepsis and septic shock in changes. World J Surg 1996;20:411-417 our patient population. 9. LeGall JR, Lemeshow S, Leeu G, et al. Customized probability model for early severe sepsis in adult In the current study, we recruited ICU patients only intensive care patients. JAMA 1995; 273: 644-650 because of variables in APACHE II system. MPM- admission, 10. Marshall JC, Cook DJ, Christou NV, et al. Multiple MPM-24 hours and SAPS II could be used in non-ICU patients score: A reliable descriptor of a as well. Most of the patients in our study had serious concomitant complex clinical outcome. Crit Care Med 1995; illnesses, which could have contributed to mortality. While 23:1638-1652 APACHE II correctly predicted mortality above a certain score, 11. Vincent JL, Moreno R, Takala J, et al. The SOFA and proved to be the most sensitive of the models studied, (sepsis- related organ failure assessment) score to SAPS II was the most specific system for this purpose. The describe organ dysfunction/failure. Intensive Care Med other systems too performed reasonably well, although 1996; 22:707-710 calculations on sensitivity, specificity and positive predictive 12. Russell JA, Singer J, Bernard GR, et al. Changing value may not be entirely reliable with a small sample size. pattern of organ dysfunction in early human sepsis is related to mortality. Crit Care Med 2000; 28:3405- There is a need to study the utility of these models in 3411

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