Background: Acute deterioration of patients in general wards often leads to major adverse events (MAEs), including unplanned intensive care unit transfers, cardiac arrest, or death. Traditional early warning scores (EWSs) have shown limited predictive accuracy, with frequent false positives. We conducted a prospective observational external validation study of an artificial intelligence (AI)-based EWS, the VitalCare - Major Adverse Event Score (VC-MAES), at a tertiary medical center in the Republic of Korea. Methods: Adult patients from general wards, including internal medicine (IM) and obstetrics and gynecology (OBGYN)—the latter were rarely investigated in prior AI-based EWS studies—were included. The VC-MAES predictions were compared with National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) predictions using the area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and logistic regression for baseline EWS values. False-positives per true positive (FPpTP) were assessed based on the power threshold. Results: Of 6,039 encounters, 217 (3.6%) had MAEs (IM: 9.5%, OBGYN: 0.26%). Six hours prior to MAEs, the VC-MAES achieved an AUROC of 0.918 and an AUPRC of 0.352, including the OBGYN subgroup (AUROC, 0.964; AUPRC, 0.388), outperforming the NEWS (0.797 and 0.124) and MEWS (0.722 and 0.079). The FPpTP was reduced by up to 71%. Baseline VC-MAES was strongly associated with MAEs (P<0.001). Conclusions The VC-MAES significantly outperformed traditional EWSs in predicting adverse events in general ward patients. The robust performance and lower FPpTP suggest that broader adoption of the VC-MAES may improve clinical efficiency and resource allocation in general wards.

Unhealthy lifestyle behaviors such as smoking, alcohol consumption, and physical inactivity (multiple risks) often lead to serious health consequence and impaired health status. The purpose of this study was to investigate the trend in health-related behavioral factors over time among adults in South Korea (hereafter Korea). The data of 1,595,842 Koreans older than 19 years who participated in the 2008-2014 Korea Community Health Survey were analyzed to assess the trend in the prevalence of behavioral risk factors. Individual or clustering health-related behaviors were assessed according to sex, age, and region among 228,712 adults who participated in the 2014 survey. From 2008 to 2014, the age-adjusted prevalence of obesity and high-risk alcohol use increased the prevalence of male current smoking and marginally decreased walking ability. Over 7 years, the percentage of adults who reported having all three healthy behaviors (i.e., currently not smoking, not consuming alcohol or having high-risk alcohol use, and engaging in walking) decreased from 35.2% in 2008 to 29.6% in 2014. Increased efforts to emphasize multiple health-related behavioral risk factors, including reducing alcohol use and smoking, and to encourage walking are needed in the thirties and forties age groups in Korea.
Adult* ; Alcohol Drinking ; Health Surveys* ; Humans ; Korea ; Life Style ; Male ; Obesity ; Prevalence ; Risk Factors ; Smoke ; Smoking ; Walking