QJM: An International Journal of Medicine最新文献

{"title":"Age-Related Physiological and Molecular Biomarkers Associated with Kidney Function: a Systematic Review and Meta-Analysis.","authors":"Caoimhe McGarvey, Kate Doyle, Adam Roche, David Mockler, Silvin Knight, Rose Anne Kenny, Donal J Sexton","doi":"10.1093/qjmed/hcaf111","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf111","url":null,"abstract":"<p><strong>Background: </strong>The prevalence of Chronic Kidney Disease (CKD) is rising rapidly due to population ageing, with significant consequences for morbidity and mortality. The use of effective, predictive biomarkers would enable early introduction of targeted, proactive management of kidney disease.</p><p><strong>Aim: </strong>The aim of this review is to summarise all available studies investigating the association of neurocardiovascular, inflammatory and epigenetic biomarkers with kidney function and their ability to predict CKD incidence or progression.</p><p><strong>Design: </strong>Systematic review and meta-analysis.</p><p><strong>Methods: </strong>Systematic searches were conducted in Scopus, Embase, MEDLINE and CINAHL covering available literature until November 29, 2023. Studies assessing the relationship between named biomarkers and kidney outcomes in adults were included. Title, abstract and full text screening involved 2 independent reviewers using Covidence software. Data extraction and quality assessment, using the Newcastle-Ottawa scale (NOS), were completed by two reviewers. Systematic narrative analysis was performed for all biomarkers, and meta-analysis was conducted for studies reporting odds or hazard ratios.</p><p><strong>Results: </strong>Sixty-eight observational studies were included. Several biomarkers showed significant association with kidney function but significant independent associations with CKD incidence and progression were limited. Results from the meta-analysis: heart rate variability and CKD progression: pooled hazard ratio 1.75 (1.25-2.45), arterial stiffness and kidney function and CKD incidence: pooled odds ratios 1.08 (1.03-1.13) and 1.14 (1.01-1.29).</p><p><strong>Conclusions: </strong>Further longitudinal research focussing on the outcomes of CKD incidence and progression is required. The use of physiological and molecular biomarkers has the potential to improve the management and prognostication of CKD.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144028958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of novel biomarkers and drug targets for frailty-related skeletal muscle aging: a multi-omics study.","authors":"Qijun Wang, Xuan Zhao, Wei Wang, Xiaolong Chen, Shibao Lu","doi":"10.1093/qjmed/hcaf108","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf108","url":null,"abstract":"<p><strong>Background: </strong>Skeletal muscle aging is the major cause and hallmark of frailty, which poses a significant challenge to the healthcare system.</p><p><strong>Aim: </strong>This study aimed to identify the potential biomarkers for the early detection and therapeutic intervention of this age-related condition.</p><p><strong>Methods: </strong>A transcriptomics-based methodology using machine learning algorithms was performed to select the biomarker genes. A predictive machine learning model for (pre-)frailty based on the transcriptomic profile of the biomarker genes was constructed and validated. The cell-type specific changes of the biomarkers during muscle aging were investigated in a single-cell RNA sequencing dataset of human skeletal muscle. Summary data-based Mendelian randomization (SMR) and Bayesian colocalization analyses were performed to identify biomarker genes with therapeutic effects on frailty-related skeletal muscle aging, and drug candidates were explored in the DSigDB database.</p><p><strong>Results: </strong>We identified 24 biomarker genes, most of which were discovered for the first time. The optimal predictive model showed excellent performance in the external test set. Differential expression of the biomarkers in the single-cell dataset indicated a critical role of endothelial cells modulated by the marker genes MGP and ID1 in muscle degeneration. The SMR and colocalization analyses showed causal relationships between 2 marker genes (MGP and WAC) and frailty-related muscle aging. Potential therapeutics for MGP modulation were identified in the DSigDB database.</p><p><strong>Conclusions: </strong>This multi-omics study identified biomarkers associated with frailty-related muscle aging and provided new insights into the etiology and therapeutic targets for this age-related condition.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Porokeratosis of Mibelli.","authors":"Jia Zhou, Jun Li","doi":"10.1093/qjmed/hcaf104","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf104","url":null,"abstract":"","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behind the Blue: A Cutaneous Mirage Unfolds as Behçet's Disease.","authors":"Hiren Kalyani, Rahul Bisaralli, Tejaswee Banavathu, Swetal Pandey, Prasan Deep Rath","doi":"10.1093/qjmed/hcaf107","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf107","url":null,"abstract":"","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144043802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parrot's Beak Sign in Brucellosis.","authors":"Nitin Gupta, Muralidhar Varma, Tirlangi Praveen Kumar","doi":"10.1093/qjmed/hcaf106","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf106","url":null,"abstract":"","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144005035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pragmatic Versus Evidence Based Medicine-it's not either-or.","authors":"Piotr Szawarski, David Hillebrandt","doi":"10.1093/qjmed/hcaf086","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf086","url":null,"abstract":"<p><p>Pragmatism in medicine remains largely unacknowledged, undefined and un-described. We argue that it should not be viewed as an antithesis to evidence based approach, but rather as a way of solving a clinical problem whilst acknowledging limitations arising from the context in which the care is provided. The imperfection of the approach may be its strength, as uncertainty demands continuous re-appraisal of the situation. Existence of readily available evidence, compiled in a guideline may be an advantage, but is not a prerequisite for success. Indeed, the evidence based approach is not perfect and its application meets a number of limitations. We would like to assert that pragmatic approach focused on seeking the most available, given therapeutic context, solutions remains the most available and efficient in present day medical practice. It fills many holes between the academic perfection of research and vast heterogeneity of individual patients and clinical contexts.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144043959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Multi-omics Technologies with Traditional Chinese Medicine to Enhance Cancer Research and Treatment.","authors":"Xiaohui Wen, Yaran Wang, Chao Su, Yanyi You, Ziqing Jiang, Daoqi Zhu, Qin Fan","doi":"10.1093/qjmed/hcaf103","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf103","url":null,"abstract":"<p><p>Cancer remains a formidable global health challenge owing to its complexity, including tumor heterogeneity and intricate regulatory networks. Traditional Chinese medicine (TCM) offers unique multi-targeted therapeutic approaches with demonstrated benefits such as improved prognosis, reduced side effects, and long-term tumor stabilization. This review explores the convergence of multi-omics technologies-genomics, transcriptomics, proteomics, metabolomics, and epigenomics-with TCM to elucidate the molecular mechanisms underlying its anti-cancer effects. By integrating omics data, researchers can uncover regulatory networks, identify therapeutic targets, and validate the efficacy of TCM. Advances in single-cell omics, spatial omics, and machine learning are creating new opportunities for personalized TCM-based therapies. However, translating these findings into clinical applications remains challenging. This review highlights the potential of omics-integrated TCM in addressing cancer complexity and proposes actionable strategies for overcoming research and application barriers, thereby facilitating the development of innovative and effective treatment options.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144042219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Invisible Foes: How Air Pollution and Lifestyle Conspire in the Rise of Colorectal Cancer.","authors":"Di Zhao, Meng Zhu","doi":"10.1093/qjmed/hcaf074","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf074","url":null,"abstract":"<p><strong>Background: </strong>Air pollution is a recognized risk factor for colorectal cancer (CRC), but its specific impact in China, especially among older populations, remains underexplored.</p><p><strong>Methods: </strong>We used multivariable Cox models with restricted cubic splines (RCS) to assess the dose-response relationship between air pollution and CRC risk. Subgroup analyses by sex, residence (urban vs. rural), and pre-existing health conditions (hypertension, diabetes) were conducted. Mediation analysis assessed the indirect effects of smoking and alcohol on CRC risk.</p><p><strong>Results: </strong>Exposure to PM2.5, NO2, and SO2 was linked to increased CRC risk. For PM2.5, the hazard ratio (HR) for the highest exposure quartile was 2.35 (95% CI: 1.85-3.03) in urban residents and 1.93 (95% CI: 1.45-2.56) in rural residents. For NO2, the HR per 10 µg/m³ increase was 1.82 (95% CI: 1.56-2.12), and for SO2, it was 1.56 (95% CI: 1.31-1.85). Smoking mediated 14.03% of the effect of PM2.5 on CRC, while alcohol consumption mediated 5.12%. Subgroup analysis showed higher susceptibility in females (HR = 3.47, 95% CI: 2.63-4.63) compared to males (HR = 2.98, 95% CI: 2.25-3.79), and individuals with hypertension (HR = 2.67, 95% CI: 1.98-3.60) or diabetes (HR = 2.10, 95% CI: 1.55-2.86) were at significantly higher risk.</p><p><strong>Conclusions: </strong>Long-term exposure to PM2.5, NO2, and SO2 significantly increases CRC risk in older Chinese adults, with smoking as a key mediator. Females, urban residents, and those with hypertension or diabetes are especially vulnerable. Public health strategies should focus on reducing pollution in these high-risk groups.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143992962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The frozen hands: visual clues to diabetic cheiroarthropathy.","authors":"Santosha Mantha, Sachin Modi, Shilika Lalwani, Amit S Nachankar, Vikram Singh Shekhawat","doi":"10.1093/qjmed/hcaf102","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf102","url":null,"abstract":"","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144041560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable machine learning prediction of 1-year kidney function progression among patients with type 2 diabetes mellitus and chronic kidney disease: a retrospective study.","authors":"Jinyi Wu, Qi Gao, Ming Tian, Shuangping Tan, Junwu Dong, Honglan Wei","doi":"10.1093/qjmed/hcaf101","DOIUrl":"https://doi.org/10.1093/qjmed/hcaf101","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to develop and validate a risk prediction model for 1-year CKD progression in patients with T2DM and CKD by employing various machine learning (ML) algorithms.</p><p><strong>Methods: </strong>This study included a total of 12,151 patients with T2DM and CKD with estimated glomerular filtration rate (eGFR) between 30 and 59.9 mL/min/1.73 m2 from a tertiary hospital in Wuhan, enrolled between 2012 and 2024. The cohort was divided into a training set of 5,954 patients, an internal validation set of 2,552 patients, and an external validation set of 3,645 patients. We developed 1-year CKD progression risk prediction models using 10 different machine learning algorithms. CKD progression was defined as a decline in eGFR by more than 30% from baseline and/or a reduction in eGFR to below 15 mL/min/1.73 m2. The SHAP (SHapley Additive exPlanations) method was utilized to explain the predictions of a model.</p><p><strong>Results: </strong>Among the 10 ML models, the XGBoost model achieved the best predictive performance for 1-year progression of kidney function with an AUC of 0.906 in the internal validation set and 0.768 in the external validation set. The final predictive model incorporating only nine variables has been implemented into a web application to enhance its usability in clinical settings.</p><p><strong>Conclusion: </strong>Our findings suggest that the XGBoost model may serve as a valuable decision-support tool for predicting kidney function decline in patients with T2DM and CKD.</p>","PeriodicalId":20806,"journal":{"name":"QJM: An International Journal of Medicine","volume":" ","pages":""},"PeriodicalIF":7.3,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}