Yapay Zeka Hızlı Bakış & Çıkarımlar
AI InsightAccording to the results of our study, we suggest the use of gestalt for physicians working in limited-resource or crowded EDs.
📌 3 Maddede Bu Makale
Özet
Objective: This study aims to measure and compare the CURB-65 score and the predictive performance of physician’s gestalt in predicting mortality for COVID-19 patients admitted to the emergency department (ED) and intended for hospitalization. Methods: This study was designed as prospective-observational. All COVID-19 patients admitted to the ED between May 1 and June 1, 2021, were included in the study. Based on these results, the gestalt percentages and CURB-65 scores of the hospitalized patients were calculated, and the in-hospital mortality predictive power was analyzed. Results: This study was performed with 101 patients after utilising the inclusion-exclusion criteria. The mean age of the patients was 75.9±9.31 years and 55 (54.5%) were male. The most suitable cut-off value for CURB-65 was found to be ≥2.50, and the most suitable cutoff value for Gestalt was found to be ≥35%. Area under the curve (AUC) value, sensitivity and specificity of CURB-65, was calculated as 0.668, 0.500 and 0.841, respectively. For Gestalt, these values were found as 0.630, 0.789 and 0.444, respectively. Conclusion: In this study, it was revealed that the predictive powers of the CURB-65 score and physician’s gestalt were successful in predicting in-hospital mortality for COVID-19 patients, but they were not superior to each other. According to the results of our study, we suggest the use of gestalt for physicians working in limited-resource or crowded EDs.