Mahboobeh Namnabati, Reza Sotoudeh, Niloofar Bahrami
Family Attitude Toward Infant Home-Based Care Program Amid COVID-19 Pandemic in Iran: A Cross-Sectional Study
Home health care management & practice
accurate prediction complications often informs shared decisionmaking derived 10 years ago enhance prediction intrapostoperative myocardial infarction cardiac arrest mica gupta score criticized unreliable calibration inclusion wide spectrum unrelated operations present study developed novel machine learning ml model estimate perioperative risk mica compared gupta score patients undergoing major operations identified 20162020 acsnsqip gupta score calculated patient novel ml model developed predict mica using acs nsqipprovided data fields covariates discrimination cstatistic calibration brier score ml model compared existing gupta score within entire cohort across operative subgroups 2473487 patients included analysis 25177 10 experienced mica 552 mi 391 ca 56 mi ca ml model fit using randomly selected training cohort exhibited higher discrimination within testing dataset compared gupta score cstatistic 084 vs 080 p 0001 furthermore ml model significantly better calibration entire cohort brier score 00097 vs 00100 model performance markedly improved among patients undergoing thoracic aortic peripheral vascular foregut surgery present ml model outperformed gupta score prognostication mica across heterogenous range operations given growing integration ml healthcare models may readily incorporated clinical practice guide benchmarking efforts