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  • Title: Customized probability models for early severe sepsis in adult intensive care patients. Intensive Care Unit Scoring Group.
    Author: Le Gall JR, Lemeshow S, Leleu G, Klar J, Huillard J, Rué M, Teres D, Artigas A.
    Journal: JAMA; 1995 Feb 22; 273(8):644-50. PubMed ID: 7844875.
    Abstract:
    OBJECTIVE: To develop customized versions of the Simplified Acute Physiology Score II (SAPS II) and the 24-hour Mortality Probability Model II (MPM II) to estimate the probability of mortality for intensive care unit patients with early severe sepsis. DESIGN AND SETTING: Logistic regression models developed for patients with severe sepsis in a database of adult medical and surgical intensive care units in 12 countries. PATIENTS: Of 11,458 patients in the intensive care unit for at least 24 hours, 1130 had severe sepsis based on criteria of the American College of Chest Physicians and the Society of Critical Care Medicine (systemic inflammatory response syndrome in response to infection, plus hypotension, hypoperfusion, or multiple organ dysfunction). RESULTS: In patients with severe sepsis, mortality was higher (48.0% vs 19.6% among other patients) and 28-day survival was lower. The customized SAPS II was well calibrated (P = .92 for the goodness-of-fit test) and discriminated well (area under the receiver operating characteristic [ROC] curve, 0.78). Performance in the validation sample was equally good (P = .85 for the goodness-of-fit test; area under the ROC curve, 0.79). The customized MPM II was well calibrated (P = .92 for the goodness-of-fit test) and discriminated well (area under the ROC curve, 0.79). Performance in the validation sample was equally good (P = .52 for the goodness-of-fit test; area under the ROC curve, 0.75). The models are independent of each other; either can be used alone to estimate the probability of mortality of patients with severe sepsis. CONCLUSIONS: Customization provides a simple technique to apply existing models to a subgroup of patients. Accurately assessing the probability of hospital mortality is a useful adjunct for clinical trials.
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