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.
Intensive Care Med
; 31(10): 1345-55, 2005 Oct.
Article
em En
| MEDLINE
| ID: mdl-16132892
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 ANDSETTING:
A total of 16,784 patients consecutively admitted to 303 intensive care units from 14 October to 15 December 2002. MEASUREMENTS ANDRESULTS:
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 H=10.56, p=0.39, C=14.29, p=0.16). Customized 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.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Índice de Gravidade de Doença
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Modelos Logísticos
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Mortalidade Hospitalar
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Unidades de Terapia Intensiva
Tipo de estudo:
Clinical_trials
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Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Adult
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Humans
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Middle aged
Idioma:
En
Revista:
Intensive Care Med
Ano de publicação:
2005
Tipo de documento:
Article
País de afiliação:
Portugal