Diar Zooravar

Cardiovascular-Kidney-Metabolic (CKM) syndrome reflects the interconnected nature of cardiovascular, renal, and metabolic dysfunction. Sarcopenia, or the loss of skeletal muscle mass, is linked to adverse outcomes in chronic diseases, but its role within the CKM framework remains poorly defined. This study aimed to investigate the association between sarcopenia, CKM syndrome severity, and mortality risk. This study analyzed data from 5,925 adults (aged ≥ 20 years) across eight NHANES cycles (1999–2006, 2011–2018). Sarcopenia was defined using FNIH criteria based on DXA-derived muscle mass. CKM syndrome staging followed the AHA classification. Multinomial and ordinal logistic regression examined the relationship between sarcopenia and CKM stage. Cox proportional hazards models evaluated the impact of sarcopenia on all-cause, cardiovascular (CVD), and non-CVD mortality. Sensitivity analysis was performed to confirm robustness. During a mean follow-up of 125.47 (0.94) months, 851 deaths occurred. Sarcopenia was significantly associated with increased odds of advanced CKM stages: (OR: 2.236, 95% CI: 1.594–3.135), stage 3 (OR: 3.332, 95% CI: 2.001–5.548) and stage 4 (OR: 3.495, 95% CI: 2.157–5.662), compared to Stage 1. Sarcopenia also predicted higher mortality risks in patients with CKM stage 1–4: all-cause mortality (HR: 1.527, 95% CI: 1.274–1.831), CVD mortality (HR: 1.903, 95% CI: 1.299–2.788) and non-CVD mortality (HR: 1.407, 95% CI: 1.124–1.762). Sarcopenia is strongly linked to CKM syndrome severity and is a predictor of mortality across CKM stages. These findings suggest that assessing and managing sarcopenia could offer a valuable strategy to mitigate disease progression and improve survival in individuals with CKM syndrome.

Background and Aims: Lung cancer remains a leading cause of cancer‐related deaths worldwide, with early detection critical for improving prognosis. Traditional machine learning (ML) models have shown limited generalizability in clinical settings. This study proposes a deep learning‐based approach using transfer learning to accurately segment lung tumor regions from CT scans and classify images as cancerous or noncancerous, aiming to overcome the limitations of conventional ML models.Methods: We developed a two‐stage model utilizing a ResNet50 backbone within a U‐Net architecture for lesion segmentation, followed by a multi‐layer perceptron (MLP) for binary classification. The model was trained on publicly available CT scan datasets and evaluated on an independent clinical dataset from Hazrat Rasool Hospital, Iran. Training employed binary cross‐entropy and Dice loss functions. Data augmentation, dropout, and regularization were used to enhance model generalizability and prevent overfitting.Results: The model achieved 94% accuracy on the real‐world clinical test set. Evaluation metrics, including F1 score, Matthews correlation coefficient (MCC), Cohen's kappa, and Dice index, confirmed the model's robustness and diagnostic reliability. In comparison, traditional ML models performed poorly on external test data despite high training accuracy, highlighting a significant generalization gap.Conclusion: This research presents a reliable deep learning framework for lung cancer detection that outperforms traditional ML approaches on external validation. The results demonstrate its potential for clinical deployment. Future work will focus on prospective validation, interpretability techniques, and integration into hospital workflows to support real‐time decision making and regulatory compliance.

Background and Aims: The triglyceride‐glucose (TyG) index, a surrogate marker for insulin resistance and metabolic syndrome, has been implicated in breast cancer (BC) risk. However, its predictive value remains controversial. This systematic review and meta‐analysis assessed the association between the TyG index and BC risk, its role in differentiating malignant from benign breast lesions, and its potential prognostic significance.Methods: A comprehensive search of PubMed, Scopus, Web of Science, Embase, and Google Scholar was conducted up to January 2025. Studies were included if they met the following criteria: (1) assessed the TyG index about BC risk, progression, or prognosis; (2) included a comparator group (healthy individuals, benign breast lesion patients, or internal controls); (3) reported effect sizes (odds ratio [OR] or hazard ratio [HR]) with 95% confidence intervals (CI); and (4) provided sufficient statistical data on the TyG index. Excluded studies included in vitro or animal research, reviews, case reports, and those lacking relevant quantitative data. Effect sizes were pooled using a random‐effects model; heterogeneity was assessed via I² statistics, and sensitivity analyses were performed. A restricted cubic spline model evaluated dose–response relationships.Results: Thirteen studies, including retrospective, case–control, cohort, and cross‐sectional designs, were analyzed. Case–control and cross‐sectional studies revealed a significant association between a higher TyG index and increased BC risk (OR: 1.87, 95% CI: 1.45–2.41, p < 0.01). However, cohort studies did not confirm this relationship (HR: 1.04, 95% CI: 0.97–1.11, p = 0.23). The TyG index effectively differentiated malignant from benign breast lesions (WMD: 0.23, 95% CI: 0.18–0.27, p < 0.01) with a pooled AUC of 0.64. Dose–response analysis suggested a non‐linear relationship between the TyG index and BC risk (p < 0.001).Conclusion: While the TyG index may not strongly predict BC onset, it reflects metabolic alterations linked to cancer progression. Its ability to distinguish benign from malignant lesions highlights its clinical utility. Future studies should standardize TyG index thresholds and validate their prognostic value through longitudinal research.Trial Registration: PROSPERO: CRD42024547997

Diabetic microvascular complications, including diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN), contribute significantly to morbidity and healthcare burdens among individuals with diabetes. The Mediterranean diet (MD) has been associated with improved metabolic health, but its role in mitigating microvascular complications remains unclear. This systematic review and meta-analysis aimed to assess the impact of MD adherence on the risk and progression of these complications. A comprehensive search of PubMed, Web of Science, Embase, and Scopus was conducted through February 12, 2025 to identify studies evaluating MD adherence and diabetic microvascular complications. Meta-analysis was performed where possible, with effect sizes reported as odds ratios (ORs) or hazard ratios (HRs) with 95% confidence intervals (CIs). Fourteen studies, encompassing 138 to 71,392 participants, were included. Meta-analysis indicated a significant reduction in DR risk among individuals adhering to the MD (HR: 0.69, 95% CI: 0.49–0.97, p = 0.03; OR: 0.32, 95% CI: 0.12–0.82, p = 0.02). A lower likelihood of DN development was observed (HR: 0.85, 95% CI: 0.73–0.99, p = 0.04; OR: 0.49, 95% CI: 0.25–0.96, p = 0.04). However, results for diabetic neuropathy were inconclusive due to study heterogeneity. Sensitivity analyses revealed notable heterogeneity and publication bias was detected in some analyses. Adherence to the Mediterranean diet is associated with a reduced risk of diabetic nephropathy and retinopathy, supporting its potential as a dietary intervention for diabetes management. However, the evidence for neuropathy remains inconclusive. Future well-controlled randomized trials are needed to strengthen causal inferences and refine clinical recommendations for MD-based interventions in diabetic microvascular complications.

Objectives: This study aims to assess the association between the estimated glucose disposal rate (eGDR) and the risk of diabetic microvascular complications in patients with T1DM. Methods: A systematic search of PubMed, Scopus, and Web of Science was conducted up to August 2024, including studies that examined the relationship between eGDR and diabetic retinopathy (DR), diabetic kidney disease (DKD), and diabetic neuropathy (DN) in patients with T1DM. A meta-analysis was performed to compare the eGDR values in patients with and without microvascular complications and assess the risk of these complications. Results: 22 studies were included. Lower eGDR values were significantly associated with a higher risk of microvascular complications. Specifically, a one-unit increase in eGDR was associated with a 18% reduction in the risk of DKD (ES: 0.82, 95% CI: 0.74–0.92), a 21% reduction in the risk of DR (OR: 0.79, 95% CI: 0.73–0.85). Patients with DKD, DR, and DN had eGDR values significantly lower by 1.29, 0.75, and 0.64 units, respectively, compared to those without complications. Conclusion: This meta-analysis highlights the potential role of eGDR as a non-invasive marker for the early detection of microvascular complications, highlighting the importance of regular eGDR monitoring to facilitate timely interventions.

Purpose: Glucagon-like peptide-1 (GLP-1) receptor agonists have shown potential in managing eating disorders (EDs). Recent studies highlight their effects on pathophysiological pathways, indicating their therapeutic promise, particularly for binge eating disorder (BED). This systematic review evaluates the therapeutic effects of GLP-1 agonists on BED, focusing on weight management and eating behaviors. Methods: A systematic search of PubMed, Scopus, Web of Science, and the Cochrane Library, along with manual searches, identified studies assessing GLP-1 agonists in BED patients up to November 8, 2024. Observational studies and clinical trials meeting inclusion criteria were analyzed. Results: Five studies (182 participants) were included. Patients receiving GLP-1 agonists experienced greater weight loss (− 3.81 kg; 95% CI − 5.14 to − 2.49; p < 0.01, I ²: 59.88%) compared to controls. GLP-1 agonists significantly reduced BMI (− 1.48 kg/m²) and waist circumference (− 3.14 cm). Binge Eating Scale (BES) scores improved significantly (− 8.14 points; 95% CI − 13.13 to − 3.15; p < 0.01), though heterogeneity was noted. Conclusions: This review underscores the potential role of GLP-1 agonists in BED management. However, given the limited data, especially concerning EDs other than BED and the long-term effects of these medications, further comprehensive clinical trials are recommended to evaluate the impact of various GLP-1 agonists on different EDs across diverse demographic groups. Level of evidence: Level I, randomized controlled trials.

Background/Objective Obesity is linked to increased risks of cardiovascular disease, diabetes, and certain cancers. Bariatric surgery (BS) aids in weight management, significantly altering body composition. This study evaluates the predictive value of five complete blood count (CBC)-derived indices [C-reactive-protein-albumin-lymphocyte (CALLY), glucose-to-lymphocyte ratio (GLR), prognostic nutritional index (PNI), hemoglobin, albumin, lymphocyte, platelet (HALP), and controlling nutritional status (COUNT)] on body composition changes post-BS. Method A retrospective study was conducted on 240 patients undergoing BS at Sina Hospital, Tehran, Iran. Indices were calculated using routine laboratory tests, and body composition changes were measured using bioelectrical impedance analysis at 3 and 6 months post-surgery. Results Higher pre-surgical GLR values positively correlated with increased fat-free mass (FFM) (p = 0.005 ¹, p = 0.003 ²), muscle mass (MM) (p = 0.011 ¹, p = 0.008 ²), and total body water (TBW) (p = 0.005 ¹, p = 0.005 ²) post-surgery. In contrast, higher PNI was negatively associated with changes in FM (p = 0.029 ¹, p = 0.015 ²), FFM (p = 0.002 ¹, p = 0.018 ²), TBW (p = 0.002 ¹, p = 0.015 ²) and MM (p = 0.003 ²), particularly after laparoscopic sleeve gastrectomy (LSG). Furthermore, there was a significant correlation between pre-surgical HALP score and changes in FFM (p = 0.002 ¹, p = 0.042 ²), TBW (p = 0.002 ¹) and MM (p = 0.011 ¹, p = 0.041 ²). In addition, the modified HALP score showed a more significant correlation compared to the HALP score to predict the changes FM (p = 0.002 ¹, p = 0.002 ²), FFM (p = 0.001 ¹, p = 0.006 ²), TBW (p = 0.001 ¹, p = 0.003 ²) and MM (p = 0.001 ¹, p = 0.023 ²) particularly, after 6 months. Conclusion Our findings suggest that pre-surgical assessment of GLR, PNI, and HALP indices may provide valuable insights into predicting changes in body composition after bariatric surgery. Specifically, these indices could serve as tools for tailoring preoperative nutritional strategies and post-surgical interventions. However, as this study is retrospective, further prospective research with longer follow-ups is required to validate these findings and evaluate their utility in clinical practice. ¹ 3 months after metabolic bariatric surgery. ² 6 months after metabolic bariatric surgery. Graphical Abstract

Background/aims : The Triglyceride-Glucose (TyG) index, recognized as an indicator of insulin resistance and metabolic syndrome, has been correlated with various cancer risks, including that of breast cancer (BC). This systematic review and meta-analysis sought to investigate the relationship between the TyG index and the risk of developing BC, as well as its potential in distinguishing between malignant and benign breast conditions. Methods : An extensive search of the literature was conducted across databases such as PubMed, Scopus, Web of Science, and Google Scholar until July 2024. Observational studies reporting TyG index values alongside their correlation with BC were included. Results : A total of thirty studies, encompassing 2,058,536 participants, were analyzed. The findings revealed that a higher TyG index significantly correlated with increased BC risk (Effect Size [ES]: 1.65, 95% Confidence Interval [CI]: 1.15–2.36, p = 0.006 ). Individuals in the highest TyG index category had a 1.87-fold greater risk of BC compared to those in the lowest category (ES: 1.87, 95% CI: 1.45–2.41, p = 0.001 ). This association was notably stronger in Asian populations. Moreover, patients with malignant breast lesions showed elevated TyG index values in contrast to those with benign lesions ( p < 0.001 ). Conclusion : An elevated TyG index is significantly linked to a heightened risk of BC and may be useful for differentiating between benign and malignant breast lesions. Further exploration into the clinical applicability of the TyG index as a cost-effective screening tool is suggested.