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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.
Moreno, Rui P; Metnitz, Philipp G H; Almeida, Eduardo; Jordan, Barbara; Bauer, Peter; Campos, Ricardo Abizanda; Iapichino, Gaetano; Edbrooke, David; Capuzzo, Maurizia; Le Gall, Jean-Roger.
Afiliação
  • Moreno RP; Unidade de Cuidados Intensivos Polivalente, Hospital de St. António dos Capuchos, Centro Hospitalar de Lisboa (Zona Central), Lisbon, Portugal. r.moreno@mail.telepac.pt
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 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 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.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Modelos Logísticos / Mortalidade Hospitalar / Unidades de Terapia Intensiva Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans / Middle aged Idioma: En Revista: Intensive Care Med Ano de publicação: 2005 Tipo de documento: Article País de afiliação: Portugal

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Índice de Gravidade de Doença / Modelos Logísticos / Mortalidade Hospitalar / Unidades de Terapia Intensiva Tipo de estudo: Clinical_trials / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Humans / Middle aged Idioma: En Revista: Intensive Care Med Ano de publicação: 2005 Tipo de documento: Article País de afiliação: Portugal