Postgraduate Medical Journal最新文献

Background: Peer review is central to maintaining scientific quality and helps editors make decisions. However, the volume of scientific publications continues to rise, placing pressure on the peer review system. With the rise of generative AI, its role in supporting peer review is gaining attention. This study aims to compare human-written and AI-generated peer review reports.

Methods: We analysed 398 peer review reports linked to 119 research articles published in BMJ Open in 2024. Publicly available reports and manuscripts were included. Editorials, corrections, and protocols were excluded. AI reports were generated using ChatGPT. All reports were anonymized and assessed by two independent reviewers. We conducted a hybrid thematic analysis. Frequencies of themes were calculated and compared by reviewer type. For quantitative comparison, we used the Mann-Whitney U test to assess differences in review quality scores and Fisher's exact test to compare the distribution of themes. All analyses were conducted using R software.

Results: Human reviewers gave more detailed and diverse comments. They addressed deeper issues like interpretation, originality, and applicability. AI reviews covered more sections but focused on routine or structural elements. AI outperformed slightly in format-related domains. Co-occurrence analysis showed human reviews linked diverse themes, while AI comments were structurally clustered. Shannon Index confirmed that human reviews were more thematically diverse.

Conclusions: AI can support peer review by screening for basic errors. However, it lacks insight, critical judgment, and contextual awareness. Human input remains essential for meaningful review. Review-specific AI tools that preserve confidentiality are needed for future integration.

Background: While parainfluenza virus infections are common, there is relatively little data on the impact and risk factors of parainfluenza virus infection on severe in-hospital outcomes.

Methods: This territory-wide retrospective study elucidated the risk factors for serious in-hospital outcomes among patients hospitalized due to parainfluenza infection. Data were retrieved from the Clinical Data Analysis and Reporting System managed by the Hospital Authority, Hong Kong, from 1 January 2016 to 30 June 2023. The main outcomes of interest were: (i) death during hospitalization; (ii) severe respiratory failure requiring invasive or non-invasive mechanical ventilation; (iii) secondary bacterial pneumonia; (iv) acute kidney injury.

Results: 2058 adult patients were hospitalized due to parainfluenza virus infection during the study period. 87 (4.2%) patients died during the index admission, 467 (22.7%) patients developed severe respiratory failure, 1355 (65.8%) patients developed secondary bacterial pneumonia, and 625 (30.3%) patients developed acute kidney injury. Risk factors for severe in-hospital outcomes included underlying cardiopulmonary and kidney diseases (especially those receiving renal replacement therapy) and advanced age.

Conclusions: Important risk factors for severe in-hospital outcomes among patients with parainfluenza infections include underlying age ≥65 years, cardio-pulmonary and kidney diseases. These at-risk patients may benefit from future vaccines and antiviral drugs. Key messages What is already known on this topic: Severe in-hospital outcomes among adult patients with parainfluenza infections are common What this study adds: The risk factors for severe in-hospital outcomes include underlying age ≥ 65 years, cardio-pulmonary, and kidney diseases How this study might affect research, practice, or policy: These at-risk patients may benefit from future vaccines and antiviral drugs.

Background: Health literacy is recognized as a major determinant of wellbeing. We examined how health literacy links the association of educational level with participation in leisure-time physical activity (LTPA) and muscle-strengthening exercise (MSE).

Methods: We analyzed a nationwide sample of 5248 adults. Education attainment was grouped into four groups: elementary school, middle school, high school, and college. Health literacy was assessed using the Health Literacy Index for the Community (HLIC). The Global Physical Activity Questionnaire was also employed, with engagement in ≥150 min of moderate-to-vigorous LTPA per week and MSE ≥ twice weekly defined as meeting recommended levels. Counterfactual-based mediation analyses were conducted to estimate the natural indirect effects (NIE), presented as odds ratios (ORs) with 95% confidence intervals (CIs).

Results: Among the participants, 20.5% and 25.2% met the recommended LTPA and MSE levels, respectively. Compared with those with an education attainment of elementary school or below, ORs (95% CI) for the NIE of education level on LTPA, mediated through the HLIC, were 1.06 (1.02-1.09) for middle school, 1.10 (1.04-1.15) for high school, and 1.14 (1.06-1.21) for college or above, accounting for 65.8%, 19.5%, and 16.4% of the total effects, respectively. For MSE, the ORs (95% CI) of the NIE were 1.06 (1.03-1.10) for middle school, 1.12 (1.07-1.17) for high school, and 1.16 (1.10-1.24) for college or above, accounting for 31.8%, 27.1%, and 24.8% of the total effects.

Conclusion: Health literacy may serve as a key mechanism contributing to disparities in physical activity across different educational levels. Key messages What is already known on this topic: Health literacy has garnered considerable public health interest as a key determinant of health disparities. Although previous studies have reported that health literacy is positively associated with engagement in physical activity, research on its mediating role in the association between educational attainment and leisure-time physical activity (LTPA) and muscle-strengthening exercise (MSE) is scarce in the literature. What this study adds: This study demonstrated that health literacy mediates a meaningful proportion of the link between high educational attainment and engagement in the recommended levels of LTPA or MSE. This suggests that health literacy can be an important factor underlying disparities in physical activity across varying education levels. How this study might affect research, practice, or policy: Our findings suggest that proactive policy interventions are required to enhance health literacy among individuals with low educational levels and to promote physical activity.

Purpose: Coronary artery disease (CAD) is a leading cause of cardiovascular morbidity and mortality worldwide. Recent studies suggest disruptions in circadian rhythms may contribute to CAD, but the underlying mechanisms remain unclear. This study employs summary-data-based Mendelian randomization to explore the roles of circadian rhythm genes in CAD and their clinical implications.

Methods: We retrieved circadian rhythm-related genes from the GeneCards database and utilized genome-wide association study summary data for CAD from the IEU database, further validated with FinnGen and UK Biobank datasets. We integrated expression quantitative trait loci (eQTL), methylation quantitative trait loci (mQTL), and protein abundance quantitative trait loci (pQTL) data to assess causal associations with CAD. Colocalization analysis confirmed that the signals originated from the same genetic variants.

Results: Our analyses identified 49 mQTLs, 11 eQTLs, and one pQTL causally associated with CAD. Integration of mQTL and eQTL data revealed 13 methylation sites and eight key genes, particularly RASD1 (OR = 0.777, 95% CI: 0.672-0.898) and SREBF1 (OR = 0.893, 95% CI: 0.844-0.946). The DNA methylation level at site cg20122488 was negatively correlated with RASD1 expression, while eQTL data for SREBF1 indicated a regulatory relationship with CAD risk.

Conclusions: This study emphasizes the significant roles of circadian rhythm genes RASD1 and SREBF1 in CAD pathogenesis. Findings suggest therapeutic potential for these genes, warranting further research to validate their functions and inform preventive and treatment strategies. Key messages What is already known Coronary artery disease (CAD) is a leading global cause of cardiovascular mortality, with circadian rhythm disruptions increasingly implicated in its pathogenesis, though causal genetic mechanisms remain unclear. What this study adds This Mendelian randomization study identifies 13 methylation sites and eight key circadian-related genes (e.g. RASD1, SREBF1) with causal links to CAD, revealing specific epigenetic and transcriptional regulatory effects on disease risk. How this study might affect research, practice, or policy The findings highlight circadian rhythm genes as potential therapeutic targets, offering novel insights for CAD prevention strategies and guiding future research into circadian-based interventions.

Purpose: Some patients with drug-induced liver injury (DILI) would progress into chronicity or lethal. Although adipocyte fatty acid-binding protein (AFABP) is essential in liver diseases, its role in DILI is unknown. We aimed to investigate their association and construct predictive models for chronic/lethal DILI using machine learning.

Methods: DILI patients (n = 331) were enrolled and categorized into recovery (n = 213), chronicity (n = 89), or death/liver transplantation (LT) group (n = 29) based on 6-month follow-up. ELISA and immunohistochemistry were used to determine serum and hepatic AFABP levels, respectively. Patients were randomly divided into training (70%) and validation (30%) cohorts. Machine learning models were constructed for chronic and death/LT outcomes based on serum AFABP. Furthermore, the performance of previous models and constructed models were evaluated for predicting death/LT outcome.

Results: The AFABP level was associated with the progression of DILI patients, whatever in serum or liver. The Extreme Gradient Boosting model presented the best predictive performance for chronic DILI, with the AUROC of 0.87 (95%CI = 0.82-0.91) in training cohort and AUROC of 0.90 (95%CI = 0.82-0.95) in validation cohort. The logistic regression model presented the best predictive performance for death/LT outcome, with the AUROC of 0.90 (95%CI = 0.85-0.94) in training cohort and AUROC of 0.92 (95%CI = 0.83-0.96) in validation cohort. Furthermore, it showed better predictive performance for death/LT outcome than previous models.

Conclusion: Serum AFABP level was associated with DILI progression, and machine learning models based on AFABP accurately predicted DILI outcomes, potentially assisting clinical management. Key messages What is already known on this topic: The chronic and lethal drug-induced liver injury (DILI) harms human health. Although adipocyte fatty acid-binding protein (AFABP) is essential in liver diseases, its role in DILI is unknown. We aimed to investigate their association and construct predictive models for chronic/lethal DILI using machine learning. What this study adds: The AFABP was associated with the progression of DILI patients, whatever in serum or liver. The Extreme Gradient Boosting model presented the best predictive performance for chronic DILI. The logistic regression model presented the best predictive performance for lethal DILI. Furthermore, it showed better predictive performance for lethal DILI than previous models. How this study might affect research, practice, or policy: We demonstrated that serum AFABP level was associated with the progression of DILI, and constructed accurate machine learning models to predict DILI outcomes based on serum AFABP, which could assist the clinical management of DILI patients.