Background: Type 2 diabetes mellitus (T2DM) is a chronic metabolic condition with a profound impact on health-related quality of life (HRQoL). Poor adherence to medication, exercise prescriptions and self-care activities remains a significant barrier to glycaemic control and optimal patient outcomes. However, the multidimensional associations between adherence behaviours and quality of life (QoL) domains remain underexplored in Indian urban populations. Objectives: This study aimed to assess adherence to medication, exercise and diabetes-related self-care activities, and to examine their associations with health-related QoL across four domains—physical health, psychological health, social relationships and environment—in T2DM patients. Methods: A cross-sectional observational study was conducted among 193 T2DM patients recruited from diabetic clinics in Surat, Gujarat, India. Adherence to medication was measured using the Iraqi Anti-Diabetic Medication Adherence Scale (IADMAS), exercise adherence using the Exercise Adherence Rating Scale (EARS) and self-care activities using the Diabetes Self-Management Questionnaire (DSMQ). QoL was assessed using the Gujarati version of the World Health Organization Quality of Life instrument, brief version (WHOQOL-BREF). Glycaemic control was evaluated through glycated haemoglobin (HbA1c). Spearman’s correlation coefficient was used for statistical analysis. Results: The mean age of participants was 49.78 ± 13.21 years; 59.07% were female. The mean medication adherence score was 7.11 ± 1.77; exercise adherence was 15.75 ± 5.50. Physical health QoL was low in 45.6% of participants. At the nominal level, medication adherence showed significant positive correlations with physical health QoL ( r = 0.22, P = .009) and social relationship QoL ( r = 0.304, P = .019); exercise adherence was significantly associated with physical health ( r = 0.25, P = .029), psychological health ( r = 0.49, P = .010) and general health satisfaction ( r = 0.554, P = .001); and multiple DSMQ subscales—including glucose management (GM), dietary control (DC) and physical activity (PA)—demonstrated significant correlations across QoL domains. After Benjamini-Hochberg false discovery rate (BH-FDR) correction for the 54 correlations tested, only the associations between DSMQ-GM and environmental QoL ( r = 0.581, P < .001) and between exercise adherence and general health satisfaction ( r = 0.554, P = .001) remained significant. Conclusion: Adherence to medication, exercise and diabetes-related self-care activities showed nominally significant associations with HRQoL in T2DM patients, of which the associations of diabetes self-management (GM) with environmental QoL and of exercise adherence with general health satisfaction remained robust after correction for multiple testing. Targeted interventions to improve adherence across these domains may benefit patient outcomes and well-being, though confirmatory studies are warranted.
Introduction: This review examines the significance and scientific foundation of drug expiration dates. It emphasises the risks linked to expired medications and their implications for health and safety. Methods: In September 2025, a comprehensive literature search was conducted in PubMed, Scopus, and Google Scholar. Studies regarding drug degradation mechanisms, the impact of environmental factors on medication stability, and the consequences of using expired pharmaceuticals were identified and discussed. Results: The study highlights the importance of medication expiration dates as crucial indicators of drug safety and effectiveness, ensuring the potency and purity of medications. It identifies chemical degradation and environmental factors as vital elements that can compromise drug integrity post-expiration, potentially resulting in inefficacy or harm. Nevertheless, many medications remain effective beyond their expiration dates, challenging the absolute view of expired drugs as ineffective or hazardous. The risks associated with expired medications vary based on the type of medication and storage conditions, with particular concern for individuals with pre-existing conditions or those taking multiple medications. Conclusion: Comply with expiration dates and appropriately dispose of expired medications to uphold efficacy and safety, prevent environmental pollution, and reduce health risks. Despite the challenges, including disposal costs and the necessity for regular medication audits, as well as medication hoarding, this highlights the need for increased awareness and education regarding the importance of adhering to medication expiration dates and safe disposal practices.
Background and Aims: Lymph node involvement remains one of the most powerful determinants of prognosis across gastrointestinal (GI) malignancies and constitutes a central component of the tumour-node-metastasis (TNM) staging system. Conventional nodal staging relies primarily on the absolute number of metastatic lymph nodes identified during pathological evaluation. However, this approach is highly dependent on the extent of lymphadenectomy and the adequacy of nodal retrieval, leading to potential stage migration and heterogeneity within individual nodal categories. Objective: To review the conceptual basis, methodological considerations and clinical implications of alternative nodal metrics, including lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS), in GI cancers and to examine their potential role in improving prognostic stratification beyond conventional TNM staging. Evidence Acquisition: A narrative review of the literature was performed focusing on studies evaluating nodal metrics in GI malignancies, including colorectal, gastric, pancreatic, oesophageal, biliary and hepatopancreatobiliary cancers. Emphasis was placed on studies examining the prognostic performance of LNR and LODDS, methodological issues related to nodal assessment and their integration into prognostic models. Evidence Synthesis: Evidence from multiple GI malignancies suggests that ratio-based and probabilistic nodal metrics may provide improved prognostic discrimination compared with traditional node-count-based staging systems, particularly in settings where nodal retrieval is limited or heterogeneous. LNR offers a clinically intuitive measure of metastatic density, while LODDS provides statistical robustness in scenarios of sparse nodal harvest or node-negative disease. These metrics have demonstrated value in survival modelling and prognostic nomograms across several tumour types. Conclusions: Alternative nodal metrics represent promising complementary tools for refining prognostic assessment in GI oncology. While the TNM classification remains the global standard for staging, incorporation of proportional and probabilistic nodal indices into prognostic models may enhance risk stratification and support more individualised prognostic assessment and risk-adapted treatment strategies.
Background and Aims: Point-of-care testing (POCT) for blood glucose provides rapid results and is widely used in clinical practice; however, concerns remain regarding its accuracy and agreement with laboratory auto-analyser methods. The purpose of this study was to compare glucose measurements obtained using POCT and a laboratory auto-analyser in a secondary healthcare centre within a low-resource setting. Methods: A comparison study was conducted using 120 paired blood glucose measurements obtained simultaneously by a POCT glucometer and a laboratory auto-analyser. Descriptive statistics were used to summarise glucose values. Pearson correlation and linear regression analyses assessed the relationship between methods, while agreement was evaluated using Bland-Altman analysis. Statistical significance was set at P < .05. Results: The mean glucose concentration measured by POCT was 6.59 ± 2.27 mmol/L, while that measured by the auto-analyser was 6.33 ± 2.93 mmol/L. A strong positive correlation was observed between the two methods ( r = 0.971, P < .001). Linear regression analysis yielded the equation auto-analyser = 1.249 × POCT − 1.905 ( R ² = 0.943), indicating proportional bias. Bland-Altman analysis demonstrated a mean bias of −0.26 mmol/L, with 95% limits of agreement ranging from −2.03 to +1.50 mmol/L. Greater variability in differences was observed at higher glucose concentrations. Conclusion: POCT glucose measurements show excellent correlation with laboratory auto-analyser results but exhibit systematic and proportional bias, particularly at higher glucose levels. While POCT is suitable for rapid glucose assessment and monitoring, laboratory auto-analyser methods remain the preferred reference for diagnostic and critical clinical decision-making.
