Development and validation of the Ex-Care BR model: a multicentre initiative for identifying Brazilian surgical patients at risk of 30-day in-hospital mortality.

Passos, Sávio C; de Jezus Castro, Stela M; Stahlschmidt, Adriene; da Silva Neto, Paulo C; Irigon Pereira, Paulo J; da Cunha Leal, Plínio; Lopes, Maristela B; Dos Reis Falcão, Luiz F; de Azevedo, Vera L F; Lineburger, Eric B; Mendes, Florentino F; Vilela, Ramon M; de Araújo Azi, Liana M T; Antunes, Fabrício D; Braz, Leandro G; Stefani, Luciana C

Passos, Sávio C; de Jezus Castro, Stela M; Stahlschmidt, Adriene; da Silva Neto, Paulo C; Irigon Pereira, Paulo J; da Cunha Leal, Plínio; Lopes, Maristela B; Dos Reis Falcão, Luiz F; de Azevedo, Vera L F; Lineburger, Eric B; Mendes, Florentino F; Vilela, Ramon M; de Araújo Azi, Liana M T; Antunes, Fabrício D; Braz, Leandro G; Stefani, Luciana C.

Afiliación

Passos SC; Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Anesthesiology and Perioperative Medicine Service, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
de Jezus Castro SM; Department of Statistics, Institute of Mathematics and Statistics, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Stahlschmidt A; Anesthesiology and Perioperative Medicine Service, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil.
da Silva Neto PC; Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Irigon Pereira PJ; Department of Anesthesiology, Hospital Ernesto Dornelles, Porto Alegre, Brazil.
da Cunha Leal P; Hospital São Domingos, São Luís, Brazil.
Lopes MB; Hospital Marcelino Champagnat, Curitiba, Brazil.
Dos Reis Falcão LF; Department of Surgery, School of Medicine, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
de Azevedo VLF; Obras Sociais Irmã Dulce, Salvador, Brazil.
Lineburger EB; Hospital São José, Criciúma, Brazil.
Mendes FF; Department of Surgical Clinic, School of Medicine, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Brazil.
Vilela RM; Department of Anesthesiology, Irmandade Santa Casa de Misericórdia Porto Alegre, Porto Alegre, Brazil.
de Araújo Azi LMT; Department of Anesthesiology and Surgery, School of Medicine, Universidade Federal da Bahia (UFBA), Salvador, Brazil.
Antunes FD; Department of Medicine, School of Medicine, Universidade Federal de Sergipe (UFS), Aracaju, Brazil.
Braz LG; Department of Surgical Specialties and Anesthesiology, School of Medicine, Universidade Estadual Paulista (UNESP), Botucatu, Brazil.
Stefani LC; Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil; Department of Surgery, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clínicas de Porto Alegre, Brazil. Electronic address: lpstefani

Br J Anaesth ; 133(1): 125-134, 2024 Jul.

Article en En | MEDLINE | ID: mdl-38729814

ABSTRACT

ABSTRACT

BACKGROUND:

Surgical risk stratification is crucial for enhancing perioperative assistance and allocating resources efficiently. However, existing models may not capture the complexity of surgical care in Brazil. Using data from various healthcare settings nationwide, we developed a new risk model for 30-day in-hospital mortality (the Ex-Care BR model).

METHODS:

A retrospective cohort study was conducted in 10 hospitals from different geographic regions in Brazil. Data were analysed using multilevel logistic regression models. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration plots. Derivation and validation cohorts were randomly assigned.

RESULTS:

A total of 107,372 patients were included, and 30-day in-hospital mortality was 2.1% (n=2261). The final risk model comprised four predictors related to the patient and surgery (age, ASA physical status classification, surgical urgency, and surgical size), and the random effect related to hospitals. The model showed excellent discrimination (AUROC=0.93, 95% confidence interval [CI], 0.93-0.94), calibration, and overall performance (Brier score=0.017) in the derivation cohort (n=75,094). Similar results were observed in the validation cohort (n=32,278) (AUROC=0.93, 95% CI, 0.92-0.93).

CONCLUSIONS:

The Ex-Care BR is the first model to consider regional and organisational peculiarities of the Brazilian surgical scene, in addition to patient and surgical factors. It is particularly useful for identifying high-risk surgical patients in situations demanding efficient allocation of limited resources. However, a thorough exploration of mortality variations among hospitals is essential for a comprehensive understanding of risk. CLINICAL TRIAL REGISTRATION NCT05796024.

Asunto(s)

Mortalidad Hospitalaria; Humanos; Masculino; Femenino; Brasil/epidemiología; Persona de Mediana Edad; Estudios Retrospectivos; Anciano; Medición de Riesgo/métodos; Adulto; Procedimientos Quirúrgicos Operativos/mortalidad; Estudios de Cohortes; Anciano de 80 o más Años; Curva ROC; Adulto Joven; Factores de Riesgo

Palabras clave

mortality; perioperative death; postoperative outcome; prediction model; risk assessment; risk factors

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Mortalidad Hospitalaria Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Región como asunto: America do sul / Brasil Idioma: En Revista: Br J Anaesth Año: 2024 Tipo del documento: Article País de afiliación: Brasil Pais de publicación: Reino Unido

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