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      SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission

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          Abstract

          Objective

          To develop a model to assess severity of illness and predict vital status at hospital discharge based on ICU admission data.

          Design

          Prospective multicentre, multinational cohort study.

          Patients and setting

          A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002.

          Measurements and results

          ICU admission data (recorded within ±1 h) were used, describing: prior chronic conditions and diseases; circumstances related to and physiologic derangement at ICU admission. Selection of variables for inclusion into the model used different complementary strategies. For cross-validation, the model-building procedure was run five times, using randomly selected four fifths of the sample as a development- and the remaining fifth as validation-set. Logistic regression methods were then used to reduce complexity of the model. Final estimates of regression coefficients were determined by use of multilevel logistic regression. Variables selection and weighting were further checked by bootstraping (at patient level and at ICU level). Twenty variables were selected for the final model, which exhibited good discrimination (aROC curve 0.848), without major differences across patient typologies. Calibration was also satisfactory (Hosmer-Lemeshow goodness-of-fit test Ĥ=10.56, p=0.39, Ĉ=14.29, p=0.16). Customised equations for major areas of the world were computed and demonstrate a good overall goodness-of-fit.

          Conclusions

          The SAPS 3 admission score is able to predict vital status at hospital discharge with use of data recorded at ICU admission. Furthermore, SAPS 3 conceptually dissociates evaluation of the individual patient from evaluation of the ICU and thus allows them to be assessed at their respective reference levels.

          Electronic Supplementary Material

          Electronic supplementary material is included in the online fulltext version of this article and accessible for authorised users: http://dx.doi.org/10.1007/s00134-005-2763-5

          Related collections

          Most cited references 25

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          A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study.

          To develop and validate a new Simplified Acute Physiology Score, the SAPS II, from a large sample of surgical and medical patients, and to provide a method to convert the score to a probability of hospital mortality. The SAPS II and the probability of hospital mortality were developed and validated using data from consecutive admissions to 137 adult medical and/or surgical intensive care units in 12 countries. The 13,152 patients were randomly divided into developmental (65%) and validation (35%) samples. Patients younger than 18 years, burn patients, coronary care patients, and cardiac surgery patients were excluded. Vital status at hospital discharge. The SAPS II includes only 17 variables: 12 physiology variables, age, type of admission (scheduled surgical, unscheduled surgical, or medical), and three underlying disease variables (acquired immunodeficiency syndrome, metastatic cancer, and hematologic malignancy). Goodness-of-fit tests indicated that the model performed well in the developmental sample and validated well in an independent sample of patients (P = .883 and P = .104 in the developmental and validation samples, respectively). The area under the receiver operating characteristic curve was 0.88 in the developmental sample and 0.86 in the validation sample. The SAPS II, based on a large international sample of patients, provides an estimate of the risk of death without having to specify a primary diagnosis. This is a starting point for future evaluation of the efficiency of intensive care units.
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            The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults.

            The objective of this study was to refine the APACHE (Acute Physiology, Age, Chronic Health Evaluation) methodology in order to more accurately predict hospital mortality risk for critically ill hospitalized adults. We prospectively collected data on 17,440 unselected adult medical/surgical intensive care unit (ICU) admissions at 40 US hospitals (14 volunteer tertiary-care institutions and 26 hospitals randomly chosen to represent intensive care services nationwide). We analyzed the relationship between the patient's likelihood of surviving to hospital discharge and the following predictive variables: major medical and surgical disease categories, acute physiologic abnormalities, age, preexisting functional limitations, major comorbidities, and treatment location immediately prior to ICU admission. The APACHE III prognostic system consists of two options: (1) an APACHE III score, which can provide initial risk stratification for severely ill hospitalized patients within independently defined patient groups; and (2) an APACHE III predictive equation, which uses APACHE III score and reference data on major disease categories and treatment location immediately prior to ICU admission to provide risk estimates for hospital mortality for individual ICU patients. A five-point increase in APACHE III score (range, 0 to 299) is independently associated with a statistically significant increase in the relative risk of hospital death (odds ratio, 1.10 to 1.78) within each of 78 major medical and surgical disease categories. The overall predictive accuracy of the first-day APACHE III equation was such that, within 24 h of ICU admission, 95 percent of ICU admissions could be given a risk estimate for hospital death that was within 3 percent of that actually observed (r2 = 0.41; receiver operating characteristic = 0.90). Recording changes in the APACHE III score on each subsequent day of ICU therapy provided daily updates in these risk estimates. When applied across the individual ICUs, the first-day APACHE III equation accounted for the majority of variation in observed death rates (r2 = 0.90, p less than 0.0001).
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              Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients.

              To revise and update models in the Mortality Probability Model (MPM II) system to estimate the probability of hospital mortality among 19,124 intensive care unit (ICU) patients that can be used for quality assessment within and among ICUs. Models developed and validated on consecutive admissions to adult medical and surgical ICUs in 12 countries. A total of 12,610 patients for model development, 6514 patients for model validation. Patients younger than 18 years and burn, coronary care, and cardiac surgery patients were excluded. Vital status at hospital discharge. The admission model, MPM0, contains 15 readily obtainable variables. In developmental and validation samples it calibrated well (goodness-of-fit tests: P = .623 and P = .327, respectively, where a high P value represents good fit between observed and expected values) and discriminated well (area under the receiver operating characteristic curve = 0.837 and 0.824, respectively). The 24-hour model, MPM24 (developed on 10,357 patients still in the ICU at 24 hours), contains five of the admission variables and eight additional variables easily ascertained at 24 hours. It also calibrated well (P = .764 and P = .231 in the developmental and validation samples, respectively) and discriminated well (area under the receiver operating characteristic curve = 0.844 and 0.836 in the developmental and validation samples, respectively). Among severity systems for intensive care patients, the MPM0 is the only model available for use at ICU admission. Both MPM0 and MPM24 are useful research tools and provide important clinical information when used alone or together.
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                Author and article information

                Contributors
                +351-21-3153784 , r.moreno@mail.telepac.pt
                Journal
                Intensive Care Med
                Intensive Care Medicine
                Springer-Verlag (Berlin/Heidelberg )
                0342-4642
                1432-1238
                17 August 2005
                17 August 2005
                October 2005
                : 31
                : 10
                : 1345-1355
                Affiliations
                [1 ]Unidade de Cuidados Intensivos Polivalente, Hospital de St. António dos Capuchos, Centro Hospitalar de Lisboa (Zona Central), Lisbon, Portugal
                [2 ]Department of Anaesthesiology and General Intensive Care, University Hospital of Vienna, Vienna, Austria
                [3 ]Unidade de Cuidados Intensivos, Hospital Garcia de Orta, Pragal, Portugal
                [4 ]Department of Medical Statistics, University of Vienna, Vienna, Austria
                [5 ]Department of Intensive Care, Hospital Universitario Asociado General de Castelló, Castello, Spain
                [6 ]Department of Anesthesia and Intensive Care Medicine, Hospital San Paolo, Università degli Sudi, Milan, Italy
                [7 ]Critical Care Directorate, Royal Hallamshire Hospital, Sheffield, UK
                [8 ]Department of Anesthesia and Intensive Care Medicine, Hospital of Ferrara, Ferrara, Italy
                [9 ]Department Réanimation Médicale, Hôpital St. Louis, Université Paris VII, Paris, France
                Article
                2763
                10.1007/s00134-005-2763-5
                1315315
                16132892
                © Springer-Verlag 2005
                Categories
                Original
                Custom metadata
                © Springer-Verlag 2005

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