KH-741 (KH 741 / KH741)

Development and validation of prediction model (VALOR-m) for all-cause mortality following very late-onset schizophrenia-like psychosis: A 23-year population-based study.

Fung Chris Chit Sze CCS, Chan Joe Kwun Nam JKN, Chan Wai Chi WC, Cheng Calvin Pak Wing CPW et al.

Individuals with very late-onset schizophrenia-like psychosis (VLOSLP) experience a persistent mortality gap compared to the general population, yet no validated prognostic tools tailored to this growing population exist. We aimed to develop and validate a 3-year all-cause mortality prediction model (VALOR-m) for individuals with VLOSLP. We developed VALOR-m with LASSO-penalised Cox regression. To evaluate temporal drift and geographic generalisability, we employed a two-stage approach: 1)temporal validation stratified by two time periods (period 1: 2002-2013; period 2: 2014-2024), and 2)temporal recalibration with internal-external cross-validation (IECV) stratified by seven catchment areas in period 2. Discrimination was assessed by time-dependent AUC and Harrell's c-statistic; calibration by calibration slope and observed-to-expected ratio (O/E ratio). Using a population-based electronic health record cohort from Hong Kong (2002-2024), we identified 33,594 older adults (aged≥60 years) with VLOSLP. Of 33,594 individuals included (16,262[48·4%] male; mean age of onset 76·4 years), 11,272 (33·6%) died within 3 years. VALOR-m retained 11 predictors and demonstrated good discrimination (pooled time-dependent AUC:0·772 95%CI[0·765-0·779]; Harrell's c-statistic 0·734 95%CI[0·728-0·741]) and satisfactory calibration (calibration slope 0·885 95%CI[0·859-0·911]; O/E ratio 0·972 95%CI[0·908-1·041]) in IECV. VALOR-m provides the first validated individualised mortality risk estimates for individuals with VLOSLP, applicable to real-world clinical practice using routinely collected data. VALOR-m achieved comparable discrimination to conventional comorbidity indices with fewer predictors, suggesting that it better captures the unique mortality profile of VLOSLP, and supporting its use to guide antipsychotic treatment decisions, personalised healthcare management in this understudied yet growing population.

Diagnostic performance and interference analysis of a chemiluminescent H. pylori stool antigen assay stratified by 13C-urea breath test values in a multicenter study.

Wang Zixia Z, Chen Xiaozhong X, Lu Huiqiong H, Deng Qianyun Q et al.

Helicobacter pylori (H. pylori) infection remains a significant global health challenge, and accurate non-invasive diagnostic methods are essential for effective clinical management. This study aimed to evaluate the diagnostic performance of the MAGLUMI H. pylori antigen chemiluminescent immunoassay (CLIA) in a multicenter setting and compare its efficacy with the urea breath test (UBT), which served as the reference standard. A prospective multicenter study was conducted across four tertiary hospitals in China, enrolling 741 subjects. The diagnostic performance of the MAGLUMI H. pylori antigen CLIA was assessed using UBT as the reference standard, and influencing factors were explored through stratified analysis based on continuous UBT values. The assay demonstrated high precision with a coefficient of variation (CV) of less than 5%. The diagnostic sensitivity was 94.59%, and specificity was 97.76%, with excellent agreement with UBT (Kappa = 0.9258). Stratified analysis revealed variations in diagnostic performance across different infection burden levels. Furthermore, the assay showed consistent performance across different stool consistencies and in clinical samples with abnormal stool findings, achieving an overall accuracy exceeding 91.30%, and complete agreement between CLIA and UBT was observed in these limited samples. The MAGLUMI H. pylori antigen CLIA is a reliable, non-invasive diagnostic method with excellent clinical applicability and generalizability. Its strong performance across diverse clinical scenarios supports its potential as an effective tool for diagnosing H. pylori infection.

Erratum to "Concomitant Use of NSAIDs or SSRIs with NOACs Requires Monitoring for Bleeding" by Lee MT, et al. (Yonsei Med J 2020;61(9):741-749).

This corrects the article on p. 741 in vol. 61, PMID: 32882758.

Heterogeneity in academic burnout and its association with professional identity among undergraduate nursing students: a latent profile analysis.

Tao Mingfen M, Chen Xinyue X, Ding Wanyu W, Wang Yingying Y et al.

To identify latent profiles of academic burnout among undergraduate nursing students and examine the demographic, academic, and professional-identity differences across these profiles. A cross-sectional survey was conducted from October to December 2025 among 741 undergraduate nursing students from four universities in Anhui Province, China. Data were collected using a demographic questionnaire, the Learning Burnout of University Students scale, and the Professional Identity Scale. Latent profile analysis was performed using the 20 academic-burnout items as manifest indicators. Model selection was based on information criteria, entropy, likelihood-ratio tests, profile size, posterior classification probabilities, parsimony, and interpretability. Chi-square tests and one-way analysis of variance were used for descriptive profile comparisons. To complement statistical screening with conceptual considerations, factors associated with profile membership were examined using an exploratory multinomial logistic regression model informed by a conceptual framework based on directed acyclic graph principles. Three profiles were identified: low academic burnout (n = 132, 17.81%), moderate academic burnout (n = 381, 51.42%), and high academic burnout (n = 228, 30.77%). The three profiles mainly represented a low-to-high severity gradient rather than qualitatively distinct burnout patterns. Compared with the low-burnout profile, students with poorer academic performance were more likely to be assigned to the moderate- or high-burnout profiles. Sophomore students had higher odds of being in the high-burnout profile than senior students, whereas confidence in employment prospects was associated with lower odds of high burnout. Professional identity scores decreased progressively from the low- to the high-burnout profile, with statistically significant differences across all pairwise comparisons. Academic burnout among undergraduate nursing students is heterogeneous, and approximately one-third of students were classified into a high-burnout profile. Professional identity showed a clear inverse gradient across burnout profiles. In the conceptual-framework-informed exploratory regression model, academic performance, grade level, only-child status, reasons for choosing nursing, and perceived employment prospects were associated with profile membership. Because of the cross-sectional design, possible residual confounding, and classification uncertainty, these associations should not be interpreted as causal. Nursing educators and public health education administrators should consider profile-specific strategies that combine academic support, career guidance, psychological support, and professional identity development.