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Few and feasible preoperative variables can identify high-risk surgical patients: derivation and validation of the Ex-Care risk model.
Gutierrez, Claudia S; Passos, Sávio C; Castro, Stela M J; Okabayashi, Lucas S M; Berto, Mariana L; Lorenzen, Marina B; Caumo, Wolnei; Stefani, Luciana C.
Afiliación
  • Gutierrez CS; Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil.
  • Passos SC; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil.
  • Castro SMJ; Department of Statistics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
  • Okabayashi LSM; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil.
  • Berto ML; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil.
  • Lorenzen MB; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil.
  • Caumo W; Department of Surgery, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Pain and Palliative Care Service at Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Laboratory of Pain and Neuromodulation, Hospital de Clínicas de Porto Alegre (HCP
  • Stefani LC; Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Anaesthesia and Perioperative Medicine Service, Hospital de Clinicas de Porto Alegre, Brazil; Department of Surgery, School of Medicine, Universidade Federal do Rio Gran
Br J Anaesth ; 126(2): 525-532, 2021 02.
Article en En | MEDLINE | ID: mdl-33127046
BACKGROUND: The development of feasible preoperative risk tools is desirable, especially for low-middle income countries with limited resources and complex surgical settings. This study aimed to derive and validate a preoperative risk model (Ex-Care model) for postoperative mortality and compare its performance with current risk tools. METHODS: A multivariable logistic regression model predicting in-hospital mortality was developed using a large Brazilian surgical cohort. Patient and perioperative predictors were considered. Its performance was compared with the Charlson comorbidity index (CCI), Revised Cardiac Risk Index (RCRI), and the Surgical Outcome Risk Tool (SORT). RESULTS: The derivation cohort included 16 618 patients. In-hospital death occurred in 465 patients (2.8%). Age, with adjusted splines, degree of procedure (major vs non-major), ASA physical status, and urgency were entered in a final model. It showed high discrimination with an area under the receiver operating characteristic curve (AUROC) of 0.926 (95% confidence interval [CI], 0.91-0.93). It had superior accuracy to the RCRI (AUROC, 0.90 vs 0.76; P<0.01) and similar to the CCI (0.90 vs 0.82; P=0.06) and SORT models (0.90 vs 0.92; P=0.2) in the temporal validation cohort of 1173 patients. Calibration was adequate in both development (Hosmer-Lemeshow, 9.26; P=0.41) and temporal validation cohorts (Hosmer-Lemeshow 5.29; P=0.71). CONCLUSIONS: The Ex-Care risk model proved very efficient at identifying high-risk surgical patients. Although multicentre studies are needed, it should have particular value in low resource settings to better inform perioperative health policy and clinical decision-making.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procedimientos Quirúrgicos Operativos / Técnicas de Apoyo para la Decisión / Mortalidad Hospitalaria Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Región como asunto: America do sul / Brasil Idioma: En Revista: Br J Anaesth Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procedimientos Quirúrgicos Operativos / Técnicas de Apoyo para la Decisión / Mortalidad Hospitalaria Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Adolescent / Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Región como asunto: America do sul / Brasil Idioma: En Revista: Br J Anaesth Año: 2021 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido