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Association of Comorbidities With Postoperative In-Hospital Mortality: A Retrospective Cohort Study

The purpose of this article is to evaluate the American Society of Anesthesiologists Physical Status (ASA PS) and the Charlson comorbidity index (CCI) for the prediction of postoperative mortality. The ASA PS has been suggested to be equally good as the CCI in predicting postoperative outcome. Howev...

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Detalles Bibliográficos
Autores principales: Kork, Felix, Balzer, Felix, Krannich, Alexander, Weiss, Björn, Wernecke, Klaus-Dieter, Spies, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4554144/
https://www.ncbi.nlm.nih.gov/pubmed/25715258
http://dx.doi.org/10.1097/MD.0000000000000576
Descripción
Sumario:The purpose of this article is to evaluate the American Society of Anesthesiologists Physical Status (ASA PS) and the Charlson comorbidity index (CCI) for the prediction of postoperative mortality. The ASA PS has been suggested to be equally good as the CCI in predicting postoperative outcome. However, these scores have never been compared in a broad surgical population. We conducted a retrospective cohort study in a German tertiary care university hospital. Predictive accuracy was compared using the area under the receiver-operating characteristic curves (AUROC). In a post hoc approach, a regression model was fitted and cross-validated to estimate the association of comorbidities and intraoperative factors with mortality. This model was used to improve prediction by recalibrating the CCI for surgical patients (sCCIs) and constructing a new surgical mortality score (SMS). The data of 182,886 patients with surgical interventions were analyzed. The CCI was superior to the ASA PS in predicting postoperative mortality (AUROC(CCI) 0.865 vs AUROC(ASA)(PS) 0.833, P < 0.001). Predictive quality further improved after recalibration of the sCCI and construction of the new SMS (AUROC(SMS) 0.928 vs AUROC(sCCI) 0.896, P < 0.001). The SMS predicted postoperative mortality especially well in patients never admitted to an intensive care unit. The newly constructed SMS provides a good estimate of patient's risk of death after surgery. It is capable of identifying those patients at especially high risk and may help reduce postoperative mortality.