The use of POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator to predict mortality and complications in patients submitted to Emergency Surgery.
Rev Col Bras Cir
; 50: e20233624, 2023.
Article
em En, Pt
| MEDLINE
| ID: mdl-38055550
ABSTRACT
INTRODUCTION:
the ability of the care team to reliably predict postoperative risk is essential for improvements in surgical decision-making, patient and family counseling, and resource allocation in hospitals. The Artificial Intelligence (AI)-powered POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator represents a user-friendly interface and has since been downloaded in its iPhone and Android format by thousands of surgeons worldwide. It was originally developed to be used in non-traumatic emergency surgery patients. However, Potter has not been validated outside the US yet. In this study, we aimed to validate the POTTER calculator in a Brazilian academic hospital.METHODS:
mortality and morbidity were analyzed using the POTTER calculator in both trauma and non-trauma emergency surgery patients submitted to surgical treatment between November 2020 and July 2021. A total of 194 patients were prospectively included in this analysis.RESULTS:
regarding the presence of comorbidities, about 20% of the population were diabetics and 30% were smokers. A total of 47.4% of the patients had hypertensive prednisone. After the analysis of the results, we identified an adequate capability to predict 30-day mortality and morbidity for this group of patients.CONCLUSION:
the POTTER calculator presented excellent performance in predicting both morbidity and mortality in the studied population, representing an important tool for surgical teams to define risks, benefits, and outcomes for the emergency surgery population.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Cirurgiões
Limite:
Humans
País/Região como assunto:
America do sul
/
Brasil
Idioma:
En
/
Pt
Ano de publicação:
2023
Tipo de documento:
Article