Annals of medicine最新文献

{"title":"Performance of novel biomarkers for prediction of diabetic kidney disease in patients with diabetes mellitus.","authors":"Lu-Xi Zou, Zhi-Li Hou, Chen-Huan Qian, Xue Wang, Ling Sun","doi":"10.1080/07853890.2025.2562996","DOIUrl":"10.1080/07853890.2025.2562996","url":null,"abstract":"<p><strong>Introduction: </strong>Diabetic kidney disease (DKD) is a common and serious complication in patients with diabetes mellitus (DM). This study was aimed to reveal the validity of seven emerging novel biomarkers of angiopoietin-like-4 (ANGPTL4), neutrophil gelatinase-associated lipocalin (NGAL), monocyte chemoattractant protein-1 (MCP-1), growth differentiation factor-15 (GDF15), fibroblast growth factor-23 (FGF23), n-terminal osteopontin (ntOPN) and pyruvate kinase muscle isozyme M2 (PKM2) in detecting DM patients at high risk of DKD and establish prediction models for DKD onset in DM patients.</p><p><strong>Methods: </strong>This was a cross-sectional study of 348 adult patients with Type 1 DM for at least 5 years, or Type 2 DM, followed by a prospective observational cohort of 141 adult DM patients without renal involvement at baseline and follow-up for at least 2 years. We performed logistic regression analysis to analyze the relationship between the variables and the risk of DKD occurrence, and receiver operator characteristic (ROC) analysis to assess the predictive ability of multi-biomarker panels for DKD onset.</p><p><strong>Results: </strong>In the cross-sectional cohort, the seven urinary biomarkers were all elevated in DKD patients, of which the high levels of urinary ntOPN, GDF15, NGAL, MCP-1 and FGF23 significantly increased the risk of DKD diagnosis; the urinary MCP-1 alone performed best in DKD detection with the largest area under the ROC curve (AUC). In the prospective cohort, the high levels of urinary GDF15, MCP-1, ANGPTL4 and FGF23 significantly increased the risk of DKD development, and the model constructed based on the above four biomarkers had the largest AUC (0.873) for predicting the 2-year risk of DKD occurrence.</p><p><strong>Conclusion: </strong>Our study demonstrated that the four-biomarker model performed the best in predicting DKD, which could provide more accurate tools for DKD risk prediction, thereby improving the prognosis in DM patients.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2562996"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12466183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145139310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The positive correlation between the triglyceride glucose-body mass index and the presence and severity of early-onset coronary artery disease.","authors":"Ru-Hua Liu, Jing Li, Zhi-Xiang Sun, Ting-Ting Zhou, Cong Zhao, Qing-Wu Tian, Jun-Jie Guo, Chao Xuan","doi":"10.1080/07853890.2025.2564277","DOIUrl":"10.1080/07853890.2025.2564277","url":null,"abstract":"<p><strong>Objective: </strong>The triglyceride glucose-body mass index (TyG-BMI) has emerged as a novel, comprehensive tool for evaluating insulin resistance and metabolic risk. We intend to determine the relationship between the TyG-BMI and early-onset coronary artery disease (CAD).</p><p><strong>Methods: </strong>A retrospective case-control study was performed, which included a cohort of 2,356 participants. Binary logistic regression was utilized to estimate odds ratios (ORs) and 95% confidence intervals (CIs), while restricted cubic splines (RCS) were applied to assess potential nonlinear associations. The predictive accuracy was evaluated using receiver operating characteristic (ROC) curves.</p><p><strong>Results: </strong>The TyG-BMI was significantly elevated and independently correlated with the presence of early-onset CAD (OR = 1.004, 95% CI: 1.002-1.007, <i>p</i> = 0.002). In comparison with the first quartile, the fourth quartile of the TyG-BMI index demonstrated an increased risk of early-onset CAD (OR = 1.84, 95% CI: 1.32-2.56, <i>p</i> < 0.001). A nonlinear relationship between the TyG-BMI and early-onset CAD was illustrated by an inverted L-shaped curve, as depicted by RCS. Additionally, the TyG-BMI index correlated positively with the number of diseased vessels and the Gensini score. ROC analysis revealed that the TyG-BMI (AUC = 0.673) was more effective in predicting early-onset CAD than either the TyG index (AUC = 0.625) or BMI alone (AUC = 0.656).</p><p><strong>Conclusions: </strong>The TyG-BMI index is independently associated with the early-onset CAD and has demonstrated a significant correlation with the extent of coronary artery lesions. It may serve as a cost-effective and accessible tool for identifying individuals at higher risk.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2564277"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12477769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145152301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of the transcription factor KLF16 in metabolic dysfunction associated fatty liver disease: regulatory linkages between lipid deposition and the expression of ATF4.","authors":"Guanjun Cai, Xinyuan Cui, Wenyi Li, Shan Huang, Wenfang Peng","doi":"10.1080/07853890.2025.2566872","DOIUrl":"10.1080/07853890.2025.2566872","url":null,"abstract":"<p><strong>Background and aims: </strong>The escalating prevalence of metabolic dysfunction-associated fatty liver disease (MAFLD) poses a significant global health burden. MAFLD is characterized by abnormal lipid accumulation in liver parenchymal cells and activation of endoplasmic reticulum stress. However, the effect of Krüppel-like factor 16(KLF16) on glycolipid metabolism has been limited. We investigated whether KLF16 could alleviate MAFLD through endoplasmic reticulum stress.</p><p><strong>Methods: </strong>HepG2 and mouse primary hepatocytes were treated with oleic acid (OA) to model MAFLD <i>in vitro</i>. siRNA was used to downregulate KLF16 expression in cells. C57/BL6J mice were fed a high-fat diet to model MAFLD <i>in vivo</i>, and AAV8 was used to regulate KLF16 and ATF4 expression. Western-blot, RT-qPCR, oil red O staining, and dual-luciferase reporter assays were used to explore the underlying mechanisms in MAFLD. T-test and ANOVA were used to compare the differences among groups.</p><p><strong>Results: </strong>KLF16 expression was upregulated in MAFLD models. KLF16 downregulation aggravates lipid deposition in liver cells. The expression of ATF4 protein was downregulated in MAFLD models with KLF16 knockdown. KLF16 transcriptionally regulates ATF4 expression through two binding sites. ATF4 overexpression alleviates lipid deposition exacerbated by KLF16 knockdown in mice.</p><p><strong>Conclusion: </strong>In the face of abnormal lipid deposition in MAFLD, liver cells can play a spontaneous protective role by upregulating KLF16, which can promote the expression of ATF4 at the transcriptional level, further affecting downstream lipid metabolism-related genes. KLF16 may serve as a promising target gene to improve the progression or prognosis of MAFLD.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2566872"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12490409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145201988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting six-month mortality in adult hemophagocytic lymphohistiocytosis with machine learning: a prognostic approach utilizing laboratory data.","authors":"Jun Zhou, Mingjun Xie, Yongbin Ma, Min Wang, Jingping Liu, Yaman Wang, Mengxiao Xie, Hua-Guo Xu","doi":"10.1080/07853890.2025.2566869","DOIUrl":"10.1080/07853890.2025.2566869","url":null,"abstract":"<p><strong>Background: </strong>Hemophagocytic lymphohistiocytosis (HLH) is associated with high mortality rates. This study was conducted to develop and validate a predictive model for adult HLH patients at high risk of six months mortality using machine learning (ML) algorithms.</p><p><strong>Methods: </strong>The study utilized univariate analysis and LASSO regression, incorporating eleven ML algorithms, to perform a comprehensive analysis of both admission and discharge variables. Model performance was assessed using metrics such as AUC, F1 score, Kaplan Meier (KM) curves, calibration curves and decision curve analysis (DCA).</p><p><strong>Results: </strong>A total of 136 patients meeting the HLH-2004 criteria were included in this study. Among them, 59 patients received chemotherapy or other cytotoxic drugs, while the remaining 77 patients underwent symptomatic treatment. The median age was 52 years among nonsurvivors and 48 years among survivors, with 47 (42.6%) males in the nonsurvivor group and 31 (47.6%) in the survivor group. Age and nine discharge variables were identified as the most significant features for model construction. Random forest (RF) algorithm demonstrated superior predictive capabilities, achieving an AUC of 1.00, accuracy of 0.98 and F1 score of 0.98 in the training cohort, and an AUC of 0.89, accuracy of 0.85 and F1 score of 0.85 in the validation cohort. The top five predictors were all discharge variables (ferritin, white blood cell (WBC), albumin (ALB), platelet (PLT) and direct bilirubin (DB)).</p><p><strong>Conclusion: </strong>The predictive model developed in this study provides a valuable tool for clinicians to early identify high-risk HLH patients, thereby enabling more targeted and effective interventions.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2566869"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12498379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145226485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of the systemic immune inflammation index with failure after core decompression for osteonecrosis of the femoral head: a prospective time-to-event analysis.","authors":"Chengsi Li, Haichuan Guo, Ziyu Han, Tianyu Wang, Dongwei Wu, Zhenbang Yang, Xinqun Cheng, Yingze Zhang, Yanbin Zhu","doi":"10.1080/07853890.2025.2566867","DOIUrl":"10.1080/07853890.2025.2566867","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to assess the association between preoperative systemic immune inflammation index (SII) and failure after core decompression (CD).</p><p><strong>Methods: </strong>We conducted a prospective study of patients admitted to a tertiary referral hospital with osteonecrosis of the femoral head who underwent CD between October 1, 2014 and April 30, 2019, and provided a minimum 3-year follow-up assessment. Restricted cubic splines assessed the dose-effect relationship between SII and failure. Propensity score matching (PSM) balanced potential preoperative confounders. Kaplan-Meier analyses estimated cumulative incidence as a function of time for the failure between low SII and high SII groups. Multivariable Cox proportional hazards models evaluated the independent association of high SII with failure after adjustment for perioperative factors. Prespecified subgroup analyses explored heterogeneity.</p><p><strong>Results: </strong>We found a positive relationship between the preoperative SII and failure after CD. Among 963 CD procedures performed in 676 patients, failure was observed in 97 cases in a median period of 5.4 years. The cumulative incidence of failure was 10.6% (95% CI, 8.7%, 12.8%) at 5 years. After PSM, failure rates at 5 years were identified as significant differences between the high SII and low SII groups (Log-rank p = 0.019), and that high SII was independently associated with a 1.90-fold (95% CI, 1.14, 3.18; p = 0.014) increased risk of failure. Significant heterogeneity was observed by gender and aetiology (P for interaction < 0.05).</p><p><strong>Conclusions: </strong>Preoperative high SII is a significant risk factor for failure after CD, which could be considered when evaluating surgical indications and providing preoperative counseling to patients.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2566867"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12502117/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145234331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.","authors":"Zhiqiang Xiang, Jing Deng, Hao Liang, Mengliang Jiang, Yuhan Liang, Zhaohai Liu, Yachen Wu, Leyuan Peng, Xiaoming Dai, Zhu Zhu","doi":"10.1080/07853890.2025.2568118","DOIUrl":"10.1080/07853890.2025.2568118","url":null,"abstract":"<p><strong>Objective: </strong>Posthepatectomy recurrence of hepatocellular carcinoma (HCC) is a major cause of poor prognosis. Accurate prediction is essential for reducing the burden of advanced disease and improving outcomes.</p><p><strong>Methods: </strong>A systematic search of the PubMed, Embase, and Cochrane Library databases was conducted from their inception to December 31, 2024. The standard quality assessment of diagnostic accuracy studies (QUADAS-2) tool was utilized to analyse the methodological quality of the included studies. Bivariate linear mixed models were used to pool diagnostic estimates, including sensitivity (Se), specificity (Sp), positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR). Additionally, the area under the receiver operating characteristic curves (AUC) of the included studies was utilized to evaluate the diagnostic value.</p><p><strong>Results: </strong>A total of 6665 HCC patients included in 20 studies were enrolled. The pooled Se, Sp, PLR, NLR, DOR and AUC for the overall AI-assisted diagnostic performance for postoperative HCC recurrence were 0.87 (95% CI: 0.72-0.83), 0.85 (95% CI: 0.80-0.90), 5.39 (95% CI: 3.85-7.55), 0.25 (95% CI: 0.20-0.33), 21 (95% CI: 13-35), and 0.89 (95% CI: 0.86-0.91), respectively.</p><p><strong>Conclusion: </strong>AI showed high accuracy in predicting the posthepatectomy recurrence of HCC and would shed light on screening and monitoring high-risk patients following liver resection for further treatment.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2568118"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12502119/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145234379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of metabolic management centers online tools in patients with type 2 diabetes.","authors":"Miao Xu, Jialin Li, Ying Peng, Fengmei Xu, Qidong Zheng, Yufan Wang, Tingyu Ke, Dong Zhao, Yuancheng Dai, Qijuan Dong, Bangqun Ji, Juan Shi, Yifei Zhang, Li Li, Weiqing Wang","doi":"10.1080/07853890.2025.2563751","DOIUrl":"https://doi.org/10.1080/07853890.2025.2563751","url":null,"abstract":"<p><strong>Objectives: </strong>To assess the value of National Metabolic Management Centers (MMC) specialized online tools, for the maintenance of metabolic control among patients with type 2 diabetes (T2DM).</p><p><strong>Patients: </strong>This retrospective study enrolled T2DM patients from 10 MMCs (June 2017-April 2021) and divided into non- and application of online tools (non-AOT and AOT) groups.</p><p><strong>Measurements: </strong>Propensity score matching (PSM) was used to balance the characteristics of patients between groups. The effect of online tools was evaluated by the change in HbA1c, with additional stratified analyses in subgroups.</p><p><strong>Results: </strong>After PSM, 12528 patients with T2DM were followed for a median of 15.88 (7.10, 24.27) months, the AOT group demonstrated better control of HbA1c (-0.90 [-2.60, 0.00] % vs. -0.70 [-2.20, 0.10] %, <i>p</i> < 0.0001), and a greater reduction in body mass index (-0.34 ± 1.68 kg/m² vs. -0.13 ± 1.55 kg/m², <i>p</i> < 0.0001) and Visceral fat area (VFA) (-5.33 ± 30.95 cm² vs. -3.97 ± 26.11 cm², <i>p</i> = 0.009), compared to the non-AOT group, and the high-frequency AOT group achieved a more significant HbA1c reduction than the low-frequency AOT group (-1.50 [-3.60, -0.30] % vs. -0.80 [-2.38, 0.10] %, <i>p</i> < 0.0001) and a greater reduction in VFA (-7.07 ± 30.32 cm² vs. -4.90 ± 31.10 cm², <i>p</i> = 0.010) after adjustment. Stratification analyses revealed greater HbA1c reductions in those with younger age, lower education level or poor HbA1c control at baseline.</p><p><strong>Conclusions: </strong>MMC online tools significantly improve metabolic outcomes, particularly for T2DM patients with younger age, lower education levels or poor baseline HbA1c control. They offer a scalable and effective model for out-of-hospital diabetes care.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2563751"},"PeriodicalIF":4.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145260250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical and epidemiological characteristics of respiratory syncytial virus, SARS-CoV-2 and influenza paediatric viral respiratory infections in southwest Saudi Arabia.","authors":"Ali Alsuheel Asseri, Saleh M Al-Qahtani, Ibrahim A Alzaydani, Ahmed Al-Jarie, Noha Saad Alyazidi, Ali A Alrmelawi, Alya Musfer Alqahtani, Rahaf S Alsulayyim, Ameerah K Alzailaie, Dhay M Abdullah, Abdelwahid S Ali","doi":"10.1080/07853890.2024.2445791","DOIUrl":"https://doi.org/10.1080/07853890.2024.2445791","url":null,"abstract":"<p><strong>Background: </strong>There is a global consensus that respiratory tract infections are the major causes of morbidity and mortality among children. In this study, we aimed to compare the clinical and epidemiological characteristics of respiratory syncytial virus (RSV), influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children admitted to hospital with acute respiratory infections. We also opted to identify the predictors of paediatric intensive care unit (PICU) admission.</p><p><strong>Methods: </strong>In this study, a retrospective investigation and analysis of 423 children who were admitted to Abha Maternity and Children Hospital, in the southern region of Saudi Arabia, between January and December 2022 were conducted.</p><p><strong>Results: </strong>The median age of these children was 16.5 months (Q1-Q3: 6-46.3). It was observed that the infectivity levels of RSV, SARS-CoV-2, influenza A and influenza B infections peaked in early to mid-September, mid-July, May and June, and October, respectively. There was a statistically significant difference in the total WBC counts between RSV and influenza B (<i>p</i> = 0.035) and SARS-CoV-2 and influenza B (<i>p</i> = 0.013). Moreover, there was a statistically significant difference in the absolute lymphocyte count between influenza A and RSV (<i>p</i> = 0.002). The median number of days in hospital was 6 days (Q1-Q3: 4-10). Patients with RSV infection required a significantly longer hospital stay, with a median of 8 days (Q1-Q3: 4-10). The factors associated with the likelihood of PICU admission for all study participants were congenital heart disease (odds ratio (OR) = 2.9, 95% confidence intervals (CI) [1.4-6.1]), RSV (OR = 2.3, 95% CI [1.3-4.1]) and age <6 months (OR = 2.0, 95% CI [1.2-3.4]).</p><p><strong>Conclusions: </strong>RSV was identified as the most common pathogen causing acute lower respiratory infections among the studied patients. One of the more significant findings to emerge from this study is the seasonal changes in RSV and influenza infections, which mandates further research.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2445791"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of uric acid on acute coronary syndrome prognosis in elderly patients.","authors":"Yifan Li, Tiantian Sang, Naqiang Lv, Jinxing Liu, Yingzhen Gu, Xiaorong Han, Wei Zhang, Aimin Dang","doi":"10.1080/07853890.2024.2445200","DOIUrl":"https://doi.org/10.1080/07853890.2024.2445200","url":null,"abstract":"<p><strong>Background: </strong>Uric acid (UA) plays an important role in cardiovascular diseases, yet its implications in elderly patients remains incompletely understood. This study aimed to explore the impact of UA on the prognosis in advanced-age patients with acute coronary syndrome (ACS).</p><p><strong>Methods: </strong>We included 526 patients aged 80 and older who were diagnosed with ACS. The UA levels were measured at admission, and patients were divided into four groups based on quartiles of UA levels. Major adverse cardiovascular events (MACE) during follow-up were recorded.</p><p><strong>Results: </strong>The median UA level was 344.09 μmol/L, while the median follow-up duration was 64 months. Kaplan-Meier curves demonstrated a higher cumulative incidence of MACE during long-term follow-up in the Q4 group (Log-rank <i>p</i> < 0.05). Cox regression analysis revealed an independent correlation between UA levels and an increased risk of MACE (HR 1.002, 95%CI 1.000-1.003, <i>p</i> = 0.021). The ROC curve indicated that the optimal UA value for predicting MACE was 324.25 μmol/L. After matching through PSM, the MACE-free survival rate was lower in both hyperuricemia group (UA> 420.00 μmol/L) and high UA group (324.25 μmol/L < UA≤ 420.00 μmol/L) compared to the control group. Both hyperuricemia and high UA levels were independent risk factors for long-term MACE in advanced-age ACS patients, with HR values of 1.546 (1.049-2.280, <i>p</i> = 0.028) and 1.491 (1.011-2.198, <i>p</i> = 0.044), respectively.</p><p><strong>Conclusion: </strong>Elevated UA levels were identified as independent risk factors for MACE in elderly patients with ACS. The optimal predictive value of UA for poor cardiovascular prognosis was significantly lower than the traditional definition of hyperuricemia.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2445200"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142883841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Demographic and clinical features of rosacea in North Jordan: a 10-year university hospital retrospective study.","authors":"Diala Alshiyab, Saleh A Ba-Shammakh, Alaa Bani Bakr, Mohammad Abu-Hussein, Abdulqudos Al-Fakih, Sarah Alawneh, Leen Alhuneafat, Leen Heis, Firas Al-Qarqaz","doi":"10.1080/07853890.2024.2445775","DOIUrl":"https://doi.org/10.1080/07853890.2024.2445775","url":null,"abstract":"<p><strong>Background/objectives: </strong>This study aims to investigate the demographic and clinical characteristics of rosacea within the North Jordan population, focusing on Fitzpatrick skin types III and IV. The intent is to address gaps in dermatological research concerning ethnic and racial variations in rosacea's presentation and impact.</p><p><strong>Methods: </strong>We conducted a retrospective cohort analysis at the dermatology department of King Abdullah University Hospital, North Jordan, reviewing medical records of patients diagnosed with rosacea from January 2013 to December 2023. Data collection focused on demographics, rosacea subtypes and environmental factors exacerbating the condition. Statistical analysis utilized Jamovi and GraphPad Prism software.</p><p><strong>Results: </strong>The study included 610 patients, revealing a rosacea prevalence of 1.5% within the hospital's catchment area. Most patients were female (84.4%), with a median age of 44. The majority had Fitzpatrick skin types III and IV. The erythematotelangiectatic subtype was most common (73.6%), followed by papulopustular (23.4%) and phymatous (3%). Environmental triggers like sun exposure and temperature changes were nearly universally reported as exacerbating factors.</p><p><strong>Conclusions: </strong>Rosacea shows significant gender disparities and is influenced by environmental factors. The study underscores the need for targeted research and treatment strategies that consider ethnic and racial variations, along with gender-specific presentations of the disease.</p>","PeriodicalId":93874,"journal":{"name":"Annals of medicine","volume":"57 1","pages":"2445775"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142901056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}