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.

In Harrison’s Principles of Internal Medicine, human understanding is emphasized as one of three necessary characteristics that a physician must have. Inflammation, which is caused by inflammatory inducers (inf-ids), is a fundamental feature of disease at the cellular and molecular levels. Inflammation protects the body, but excessive or prolonged inflammation can be damaging and can cause disease. Humans are repeatedly exposed to external and internal environmental factors that generate inf-ids throughout their lives. External environmental factors include microbial and non-microbial inf-ids, as well as stressors that inevitably arise during social interactions. Internal environmental factors include the adaptive physiological response that is present from birth. Inf-ids may also be produced by the four-step habit loop, which consists of a cue (e.g., stressor), emotions, routine act (adaptive response), and a reward. Immune cells in the circulatory system and in tissues may have positive and negative effects in inflammatory responses. However, low-grade inflammation may be difficult to detect. We propose a model of disease development that integrates external and internal environmental factors from the perspective of human understanding.

In Harrison’s Principles of Internal Medicine, human understanding is emphasized as one of three necessary characteristics that a physician must have. Inflammation, which is caused by inflammatory inducers (inf-ids), is a fundamental feature of disease at the cellular and molecular levels. Inflammation protects the body, but excessive or prolonged inflammation can be damaging and can cause disease. Humans are repeatedly exposed to external and internal environmental factors that generate inf-ids throughout their lives. External environmental factors include microbial and non-microbial inf-ids, as well as stressors that inevitably arise during social interactions. Internal environmental factors include the adaptive physiological response that is present from birth. Inf-ids may also be produced by the four-step habit loop, which consists of a cue (e.g., stressor), emotions, routine act (adaptive response), and a reward. Immune cells in the circulatory system and in tissues may have positive and negative effects in inflammatory responses. However, low-grade inflammation may be difficult to detect. We propose a model of disease development that integrates external and internal environmental factors from the perspective of human understanding.

In Harrison’s Principles of Internal Medicine, human understanding is emphasized as one of three necessary characteristics that a physician must have. Inflammation, which is caused by inflammatory inducers (inf-ids), is a fundamental feature of disease at the cellular and molecular levels. Inflammation protects the body, but excessive or prolonged inflammation can be damaging and can cause disease. Humans are repeatedly exposed to external and internal environmental factors that generate inf-ids throughout their lives. External environmental factors include microbial and non-microbial inf-ids, as well as stressors that inevitably arise during social interactions. Internal environmental factors include the adaptive physiological response that is present from birth. Inf-ids may also be produced by the four-step habit loop, which consists of a cue (e.g., stressor), emotions, routine act (adaptive response), and a reward. Immune cells in the circulatory system and in tissues may have positive and negative effects in inflammatory responses. However, low-grade inflammation may be difficult to detect. We propose a model of disease development that integrates external and internal environmental factors from the perspective of human understanding.

In Harrison’s Principles of Internal Medicine, human understanding is emphasized as one of three necessary characteristics that a physician must have. Inflammation, which is caused by inflammatory inducers (inf-ids), is a fundamental feature of disease at the cellular and molecular levels. Inflammation protects the body, but excessive or prolonged inflammation can be damaging and can cause disease. Humans are repeatedly exposed to external and internal environmental factors that generate inf-ids throughout their lives. External environmental factors include microbial and non-microbial inf-ids, as well as stressors that inevitably arise during social interactions. Internal environmental factors include the adaptive physiological response that is present from birth. Inf-ids may also be produced by the four-step habit loop, which consists of a cue (e.g., stressor), emotions, routine act (adaptive response), and a reward. Immune cells in the circulatory system and in tissues may have positive and negative effects in inflammatory responses. However, low-grade inflammation may be difficult to detect. We propose a model of disease development that integrates external and internal environmental factors from the perspective of human understanding.

Objective: This study was performed to evaluate the efficacy and safety of lurasidone (160 mg/day) compared to quetiapine XR (QXR; 600 mg/day) in the treatment of acutely psychotic patients with schizophrenia. Methods: Patients were randomly assigned to 6 weeks of double-blind treatment with lurasidone 160 mg/day (n=105) or QXR 600 mg/day (n=105). Primary efficacy measure was the change from baseline to week 6 in Positive and Negative Syndrome Scale (PANSS) total score and Clinical Global Impressions severity (CGI-S) score. Adverse events, body measurements, and laboratory parameters were assessed. Results: Lurasidone demonstrated non-inferiority to QXR on the PANSS total score. Adjusted mean±standard error change at week 6 on the PANSS total score was -26.42±2.02 and -27.33±2.01 in the lurasidone and QXR group, respectively. The mean difference score was -0.91 (95% confidence interval -6.35–4.53). The lurasidone group showed a greater reduction in PANSS total and negative subscale on week 1 and a greater reduction in end-point CGI-S score compared to the QXR group. Body weight, body mass index, and waist circumference in the lurasidone group were reduced, with significantly lower mean change compared to QXR. Endpoint changes in glucose, cholesterol, triglycerides, and low-density lipoprotein levels were also significantly lower. The most common adverse drug reactions with lurasidone were akathisia and nausea. Conclusion Lurasidone 160 mg/day was found to be non-inferior to QXR 600 mg/day in the treatment of schizophrenia with comparable efficacy and tolerability. Adverse effects of lurasidone were generally tolerable, and beneficial effects on metabolic parameters can be expected.