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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
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 fro...
Autores principales: | , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1315315/ https://www.ncbi.nlm.nih.gov/pubmed/16132892 http://dx.doi.org/10.1007/s00134-005-2763-5 |
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author | 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 |
author_facet | 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 |
author_sort | Moreno, Rui P. |
collection | PubMed |
description | 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 |
format | Text |
id | pubmed-1315315 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-13153152006-02-08 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 Intensive Care Med Original 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 Springer-Verlag 2005-08-17 2005-10 /pmc/articles/PMC1315315/ /pubmed/16132892 http://dx.doi.org/10.1007/s00134-005-2763-5 Text en © Springer-Verlag 2005 |
spellingShingle | Original 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 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 |
title | 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 |
title_full | 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 |
title_fullStr | 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 |
title_full_unstemmed | 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 |
title_short | 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 |
title_sort | 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 |
topic | Original |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1315315/ https://www.ncbi.nlm.nih.gov/pubmed/16132892 http://dx.doi.org/10.1007/s00134-005-2763-5 |
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