Nevin Manimala

Front Endocrinol (Lausanne). 2025 Nov 10;16:1697797. doi: 10.3389/fendo.2025.1697797. eCollection 2025.

ABSTRACT

BACKGROUND AND AIM: Helicobacter pylori (H. pylori, HP) infection plays a significant role in the development and progression of various intra-gastric and extra-gastric diseases. Its infection is associated with numerous factors, including a series of metabolic-related diseases, and the potential connections between them remain highly controversial. Meanwhile, the prevalence of metabolic diseases has been increasing exponentially with changes in economic levels and lifestyles. Exploring the correlations and potential mechanisms between HP and metabolic diseases is crucial for future disease prevention and control. Due to the ongoing controversy surrounding its relevance and the absence of articles investigating the metabolic-related mediating mechanisms and threshold effects of related metabolic diseases leading to HP infection, this study holds significant importance for guiding future lifestyle and disease control.

METHODS: By collecting relevant test and examination indicators from 7,387 participants at Peking University Shenzhen Hospital, we analyzed the potential pathogenic mechanisms using statistical methods such as regression analysis, mediation analysis, and threshold analysis.

RESULTS: We found that factors such as blood glucose levels (fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c)), Body Mass Index (BMI), and blood pressure (Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP)) were the main risk factors influencing the target outcomes in this study, while higher levels of Albumin (Alb) may have a certain protective effect, with BMI playing a particularly significant role among these factors.

CONCLUSION: This discovery has deepened our understanding of metabolic diseases, BMI, related metabolic indicators, and HP infection.

PMID:41293740 | PMC:PMC12640847 | DOI:10.3389/fendo.2025.1697797

Front Endocrinol (Lausanne). 2025 Nov 10;16:1697617. doi: 10.3389/fendo.2025.1697617. eCollection 2025.

ABSTRACT

OBJECTIVE: To evaluate the associations between systemic inflammatory biomarkers-systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), pan-immune inflammation value (PIV), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR)-and prostate cancer (PCa) risk, and to assess their potential for risk in both general and clinical populations.

METHODS: A dual-cohort study was conducted using data from the National Health and Nutrition Examination Survey (NHANES; 2001-2010; N=7,354 males, 514 were classified as PCa) and a clinical validation cohort from the second affiliated hospital of Nanchang University (N=353, 175 with biopsy-confirmed PCa). Multivariable logistic regression, restricted cubic spline (RCS) analysis, and receiver operating characteristic (ROC) curve analysis were employed to examine linear/nonlinear relationships and predictive performance of the biomarkers. Models were adjusted for demographic, clinical, and laboratory covariates.

RESULTS: Elevated SII, NLR, PLR, SIRI, and PIV were significantly associated with increased PCa risk in both cohorts, while higher LMR was protective. In the clinical cohort, the highest quartile of SIRI (OR=6.265, 95% CI: 3.130-13.012) and PIV (OR=6.638, 95% CI: 3.343-13.665) showed the strongest risks. RCS analyses revealed nonlinear relationships between biomarkers and PCa risk, total PSA (tPSA), and free PSA (fPSA). Elevated SII, NLR, PLR, SIRI, and PIV were significantly associated with increased PCa risk in both cohorts, while a higher LMR was protective. In the clinical cohort, the highest quartile of SIRI (OR=6.265, 95% CI: 3.130-13.012) and PIV (OR=6.638, 95% CI: 3.343-13.665) exhibited the strongest risks. RCS analyses revealed nonlinear relationships between biomarkers and PCa risk, total PSA (tPSA), and free PSA (fPSA). ROC analysis indicated moderate discriminatory power for PIV (AUC=0.709, 95% CI: 0.655-0.763) and SIRI (AUC=0.704, 95% CI: 0.650-0.759) compared with tPSA in the clinical cohort. However, fPSA and SIRI did not demonstrate a clear advantage, and the DeLong test showed no significant statistical difference.

CONCLUSION: Systemic inflammatory biomarkers, particularly composite indices such as SIRI and PIV, are strongly associated with PCa risk and demonstrate nonlinear relationships with PSA parameters. These biomarkers may enhance risk stratification for PCa and serve as non-invasive tools to complement existing diagnostic approaches.

PMID:41293737 | PMC:PMC12640860 | DOI:10.3389/fendo.2025.1697617

Front Endocrinol (Lausanne). 2025 Nov 10;16:1687745. doi: 10.3389/fendo.2025.1687745. eCollection 2025.

ABSTRACT

BACKGROUND: Postoperative hyperglycemia (POH) is a common metabolic complication in non-diabetic patients undergoing surgery for gastric cancer, and it significantly increases the risk of adverse outcomes. However, current prediction models primarily rely on a limited set of perioperative variables and conventional statistical methods, which often lack accuracy and generalizability. This study aimed to develop and validate a machine learning-based model for the early prediction of POH risk in non-diabetic patients following radical gastrectomy.

METHODS: This single-center, retrospective cohort study included 393 non-diabetic patients who underwent radical gastrectomy for gastric cancer between March 2021 and September 2024. A total of 38 perioperative clinical features covering preoperative, intraoperative, and early postoperative periods were collected. The primary outcome was POH, defined as a fasting venous plasma glucose level ≥ 7.8 mmol/L within 24 hours post-surgery. Nine machine learning algorithms, including Support Vector Machine with a radial basis function kernel (SVM-radial), Random Forest, XGBoost, and Logistic Regression, were developed and compared. Model performance was evaluated using accuracy, the area under the receiver operating characteristic curve (AUC), recall, and F1-score. Shapley Additive Explanations (SHAP) analysis was employed to interpret the model and identify key predictive factors.

RESULTS: The incidence of POH was 42.7%. Among all models, the SVM-radial model achieved the best test-set performance (AUC = 0.758, accuracy = 0.724, F1 = 0.743, recall = 0.750, Brier score = 0.186, calibration slope = 1.07).The model exhibited excellent discrimination, predictive accuracy, and probability calibration, indicating strong generalization capabilities and potential clinical utility. Seven key predictors were identified: operation duration, nutritional risk score, sex, surgical approach 2 (robotic surgery), preoperative fasting blood glucose, thrombosis risk score, and alkaline phosphatase. SHAP analysis confirmed the non-linear contributions of these features to POH risk and supported their interpretability for clinical decision-making.

CONCLUSION: A novel machine learning-based model, utilizing multi-dimensional perioperative features, can accurately predict the risk of POH in non-diabetic patients with gastric cancer. The SVM-radial model demonstrated superior predictive performance and clinical interpretability, providing a viable tool for early risk stratification and personalized glycemic management in the surgical setting.

PMID:41293736 | PMC:PMC12640856 | DOI:10.3389/fendo.2025.1687745

BMC Geriatr. 2025 Nov 25. doi: 10.1186/s12877-025-06679-x. Online ahead of print.

ABSTRACT

BACKGROUND: Frailty in older adults is associated with increased healthcare utilization and costs, yet evidence on the clinical effectiveness and cost-effectiveness of frailty management programs in primary care remains limited, particularly in Asian settings. This pilot randomized controlled trial (RCT) evaluated a structured, primary care-based frailty intervention in Korea to assess its feasibility, clinical impact, and economic outcomes.

METHODS: We conducted a 6-month pilot RCT involving community-dwelling older adults recruited from four urban primary care clinics. Participants were randomized to either the intervention group, which received frailty screening with the validated Korean Frailty Index for Primary Care (KFI-PC) and monthly health coaching delivered by trained nurses and health coaches, or the control group receiving usual care. Outcomes included changes in frailty index scores and total healthcare costs. Between-group comparisons were assessed using independent t-tests, chi-squared tests, and cost-effectiveness analysis from a healthcare system perspective.

RESULTS: A total of 84 participants were analyzed (intervention, n = 39; control, n = 45). At 3 months, the intervention showed a greater reduction in the frailty index than usual care, but the between-group difference was not statistically significant (mean difference – 0.03, 95% CI – 0.064 to 0.004); at 6 months the difference remained non-significant. However, the Group × Time interaction was significant (F = 4.99, p = 0.009). Total 6-month costs were lower in the intervention group, indicating economic dominance.

CONCLUSIONS: This pilot RCT provides preliminary clinical evidence and demonstrates economic dominance of a structured, primary care-based frailty management program, supporting feasibility and the need for larger, longer trials. By integrating KFI-PC-based screening with telephone-based health coaching, the intervention reduced physician burden while addressing multidimensional needs of frail older adults. These findings support the feasibility of scaling frailty management in primary care, although further research is required to confirm long-term effectiveness and sustainability.

TRIAL REGISTRATION: CRIS (KCT0005922), registered on February 22, 2021.

PMID:41291451 | DOI:10.1186/s12877-025-06679-x

BMC Gastroenterol. 2025 Nov 25. doi: 10.1186/s12876-025-04489-4. Online ahead of print.

ABSTRACT

BACKGROUND: One of the recommended protease inhibitor treatments for HIV is Atazanavir boosted with Ritonavir (ATV/r). However, hyperbilirubinemia is a well-recognized adverse effect of this therapy.

METHODS: This retrospective cross-sectional study analyzed 121 clinical records of people living with HIV (PLHIV) receiving Atazanavir/Ritonavir treatment at the Iranian Research Center for HIV/AIDS between 2014 and 2020. Study variables were extracted from the digital and physical records at the clinic and recorded using a structured data extraction form developed by the research team. For qualitative variables, results are presented as numbers and percentages, and for quantitative variables, results are presented as medians with interquartile ranges (IQR). The authors evaluated the association between demographics, clinical characteristics and laboratory profile with hyperbilirubinemia through univariate and multivariate logistic regression.

RESULTS: Hyperbilirubinemia was present in over 85% of the patients, with more than half exhibiting grade III or higher indirect hyperbilirubinemia. No significant associations were found between demographics, ART regimens, or laboratory profiles and hyperbilirubinemia (p > 0.05).

CONCLUSIONS: There was a high prevalence of indirect hyperbilirubinemia, with a significant proportion experiencing grade 3-4 elevations. Although no statistically significant associations were observed, it would be valuable to investigate potential genetic predispositions that may make certain individuals more susceptible to developing high-grade hyperbilirubinemia on ATV/r.

PMID:41291449 | DOI:10.1186/s12876-025-04489-4

BMC Geriatr. 2025 Nov 25;25(1):953. doi: 10.1186/s12877-025-06654-6.

ABSTRACT

BACKGROUND: Health check-ups have emerged as a promising tool for disease prevention and health improvement. China introduced a community-based program providing annual health check-ups and consultation services at no cost for seniors aged 65 and above. However, the program’s impact has not yet been evaluated. This study purposed to assess the impact of the free health check-up program for the elderly.

METHODS: We analysed a pooled cross-sectional data from the National Health Service Survey (Shandong) in 2013 and 2018, comprising 38,948 representative samples. The outpatient care utilization, inpatient care utilization, and the EuroQol-5 Dimension (EQ5D) score were used to assess the program’s effects on reducing medical use and improving health. A combined Difference-in-Difference and treatment-effect model were employed to assess the program’s impact, after balancing the differences between the 2013 and 2018 samples using Coarsened Exact Matching. Moreover, this study explored variations in impact between urban and rural areas, as well as potential mechanism of underlying policy effect.

RESULTS: The free health check-up program for the elderly was significantly associated with an increase in EQ5D score and a reduction in outpatient care and inpatient care utilization (P < 0.01). Furthermore, the impacts were differed between urban and rural areas. The implementation of the free health check-up program has a statistically significant negative impact on the inpatient care utilization(P < 0.1) and positive impact on EQ5D scores (P < 0.05) among rural elderly, while these impacts do not reach statistical significance for urban elderly. The results of mechanism analysis indicated that free health check-ups program assists elderly in improving health through reducing unhealthy behaviors, such as smoking and alcohol consumption.

CONCLUSION: The free health check-up program for the elderly was associated with a reduction in their medical use and an increase in their health, positioning it as a potential model for other countries grappling with an ageing populace. Despite free nature of the program, the increment in the health check-up utilization remains low among the elderly. Enhanced efforts to promote effective use and follow-up consultation are necessary.

PMID:41291448 | DOI:10.1186/s12877-025-06654-6

BMC Gastroenterol. 2025 Nov 25. doi: 10.1186/s12876-025-04453-2. Online ahead of print.

NO ABSTRACT

PMID:41291436 | DOI:10.1186/s12876-025-04453-2

Mol Med. 2025 Nov 25. doi: 10.1186/s10020-025-01379-z. Online ahead of print.

ABSTRACT

Osteoarthritis (OA) is a global problem that seriously affects human health. At present, there is still a lack of effective drugs to treat OA. Therefore, we need to find more drugs with preventive and therapeutic effects on OA. In this study, we obtained single-cell RNA sequencing (scRNA-seq) and bulk-RNA seq datasets from Gene Expression Omnibus (GEO). By using high-dimensional weighted correlation network analysis (hdWGCNA), random forest method and protein-protein interaction (PPI) network analyses, five key genes (CXCL8, CCL20, MMP3, BIRC3 and ICAM1) related to OA were identified and the RT-qPCR experiments verified the differential expression of CXCL8, CCL20 and BIRC3 between Triclocarban (TCC) treated zebrafishes and controls. The SAVERUNNER algorithm predicted 42 candidate drugs. Mendelian randomization (MR) of the candidate drugs showed that the increased expression of TUBB1 led to a reduced risk of OA (β = -0.08, P-value = 4.56E-04), while Cabazitaxel (a microtubule dynamics inhibitor commonly used in the treatment of advanced prostate cancer) inhibits the expression of TUBB1, thus increases the risk of OA. Pitavastatin (a statin lipid-lowering drug that can reduce blood lipid levels and the risk of cardiovascular diseases) target genes expression (for HMGCR [Formula: see text]= 0.13, P-value = 2.67E-06, for ITGAL [Formula: see text]= 0.08, P-value = 6.57E-08) leads to an increased risk of OA, while Pitavastatin inhibits the expression of target genes, thus reduces risk of OA. The zebrafish experiments showed that Pitavastatin can increase the joint space of TCC treated OA zebrafish, while Cabazitaxel can decrease the joint space of TCC treated OA zebrafish. The RT-qPCR results of zebrafish verified that Pitavastatin inhibited the expression of HMGCR, while Cabazitaxel inhibited the expression of TUBB1. Our study suggested that Pitavastatin has therapeutic effects on OA, while Cabazitaxel increases the risk of OA.

PMID:41291434 | DOI:10.1186/s10020-025-01379-z

BMC Anesthesiol. 2025 Nov 25. doi: 10.1186/s12871-025-03508-x. Online ahead of print.

ABSTRACT

BACKGROUND: Reintubation after planned extubation (RAP) following general anesthesia is a serious complication associated with intensive care unit admission, prolonged hospitalization, and increased mortality. Despite its clinical significance, no routinely validated clinical scoring system currently exists for predicting RAP. This study aimed to develop a clinical prediction rule for reintubation within 24 h after general anesthesia.

METHODS: This retrospective case-control study included 657 patients (235 cases and 422 controls) who underwent general anesthesia at Ramathibodi Hospital between 2014 and 2018. Cases were defined as patients reintubated within 24 h after planned extubation, and controls were randomly selected from those with successful extubation on the same operative day. Multivariable logistic regression was used to identify predictive factors, and significant predictors were transformed into a point-based risk score.

RESULTS: Significant predictors of reintubation included age < 1 or > 65 years, ASA classification ≥ III, emergency surgery, neurosurgical or thoracic procedures, vasopressor or inotrope use, positive fluid balance ≥ 40 mL/kg, and failure to follow commands after anesthesia. The score-based model demonstrated strong discrimination with an area under the receiver operating characteristic curve (AUROC) of 0.831 (95% CI: 0.795-0.868). Hosmer-Lemeshow goodness-of-fit test using 9 groups: χ²(df = 7) = 10.67, p = 0.154. Bootstrap validation confirmed consistent performance, with an optimism-adjusted AUROC of 0.831 (95% CI: 0.798-0.870). Based on total score ranges, patients were stratified into two risk categories. Those with a score of 0-9 was classified as low risk with a positive likelihood ratio (LHR+) of 0.693 (95% CI: 0.526-0.913, p = 0.004), and scores of 9.5-20 were considered high risk with an LHR + of 11.363 (95% CI: 5.611-25.306, p < 0.001).

CONCLUSION: The RAP prediction score is a validated clinical prediction tool with good discrimination of postoperative RAP. It effectively stratifies postoperative patients into distinct risk categories and may guide for recognition and decision making for extubation during postoperative period.

PMID:41291422 | DOI:10.1186/s12871-025-03508-x

BMC Bioinformatics. 2025 Nov 25. doi: 10.1186/s12859-025-06215-z. Online ahead of print.

ABSTRACT

As data complexity and volume increase rapidly, efficient statistical methods for identifying significant variables become crucial. Variable selection plays a vital role in establishing relationships between predictors and response variables. The challenge lies in achieving this goal while controlling the False Discovery Rate (FDR) and maintaining statistical power. The knockoff filter, a recent approach, generates inexpensive knockoff variables that mimic the correlation structure of the original variables, serving as negative controls for inference. In this study, we extend the use of knockoffs to Light Gradient Boosting Machine (LightGBM), a fast and accurate machine learning technique. Shapely Additive Explanations (SHAP) values are employed to interpret the black-box nature of machine learning. Through extensive experimentation, our proposed method outperforms traditional approaches, accurately identifying important variables for each class. It offers improved speed and efficiency across multiple datasets. To validate our approach, an extensive simulation study is conducted. The integration of knockoffs into LightGBM enhances performance and interpretability, contributing to the advancement of variable selection methods. Our research addresses the challenges of variable selection in the era of big data, providing a valuable tool for identifying relevant variables in statistical modeling and machine learning applications.

PMID:41291416 | DOI:10.1186/s12859-025-06215-z