Background/Objectives: Obstructive sleep apnea (OSA) is a common disorder characterized by intermittent hypoxia and sleep fragmentation, assessed using the Apnea–Hypopnea Index (AHI). Systemic inflammation is central to OSA progression, and the systemic inflammatory response index (SIRI) has emerged as a potential biomarker for inflammatory diseases. This study investigates the relationship between SIRI and OSA severity while comparing other inflammatory markers. Methods: A retrospective study was conducted among 150 OSA patients at a tertiary care hospital. Based on AHI, patients were categorized into mild, moderate, and severe OSA groups. Blood parameters, including neutrophil, monocyte, and lymphocyte counts, were analyzed, and inflammatory indices (SIRI, NLR, PLR) were calculated. Correlation, ROCs, and regression analyses assessed associations between inflammatory markers and OSA severity. Results: SIRI demonstrated an excellent predictive ability for severe OSA with an AUC of 0.960 (cut-off: 1.105; sensitivity: 92.2%; specificity: 91.4%). The STOP-BANG score alone had lower discriminatory power (AUC: 0.737), but combining it with SIRI improved accuracy (AUC: 0.983). The best performance was observed when SIRI, STOP-BANG, PLR, and CRP were combined, yielding an AUC of 1.00, indicating perfect discrimination. Conclusions: SIRI shows strong predictive value for identifying severe OSA, underscoring its utility as a simple, cost-effective biomarker to aid early recognition and referral, particularly in primary care and resource-limited settings.

Background: Insomnia, a prevalent sleep disorder, significantly impacts medical students due to the high levels of stress and demanding academic schedules. The educational environment of medical students, marked by intense competition and high expectations, often contributes to chronic stress, a known precursor to sleep disturbances. This study aimed to compare the prevalence of insomnia among medical students in government and private medical colleges and assess the factors contributing to insomnia in these groups. Methods: The cross-sectional study was conducted among 490 medical students from government and private medical colleges over three months (April to June 2024). Systematic sampling was used to select participants, and data were collected via a self-administered questionnaire, including sociodemographic information and the Athens insomnia scale. Data were analysed using SPSS Version 26.0, with chi-square tests for qualitative data and Mann-Whitney U tests for insomnia comparisons. Results: The study revealed a significantly higher prevalence of insomnia in private medical college students (40.8%) compared to government college students (11.8%). Significant associations were found between insomnia and insufficient sleep, stress, and depression in both groups. Additionally, the use of mobile devices at night and irregular sleep patterns during exams were linked to higher insomnia rates. The median insomnia score was higher in private medical college students compared to government college students, indicating a statistically significant difference (p value <0.05). Conclusions: Targeted interventions to improve sleep quality and mental health support are crucial for this population. Regular assessments and feedback mechanisms should be implemented to enhance the effectiveness of these interventions.

Background: Tuberculosis remains a major public health burden in India, accounting for 25% of the global tuberculosis cases. Weight gain during tuberculosis treatment is a key recovery indicator influenced by sociodemographic and clinical factors. Addressing these challenges is crucial for achieving India’s Tuberculosis elimination goal by 2025. Objectives: To assess weight gain across different phases of anti tubercular therapy among tuberculosis patients in urban and rural Mysuru, and to determine its association with sociodemographic and disease-related characteristics. Methodology: A retrospective cross-sectional study was done using secondary data of tuberculosis patients who attended primary health care centers in urban and rural areas of Mysuru. Weight measurements were recorded at baseline, post-intensive phase and post-continuation phase of antitubercular-therapy. Sociodemographic and disease-related characteristics were collected. Statistical analysis included Friedman test to compare weight gain during different phases of antitubercular treatment, chi square test to find association of weight changes with socio-demographic and disease-related characteristics and ordinal logistic regression analysis performed to predict factors affecting weight changes. Results: Overall, patients experienced a significant change in weight during treatment, with 85.8% showing weight gain, among whom 48% gained more than 3 kg. The prevalence of weight gain was slightly higher among the rural population compared to urban, though the difference was not significant. Sociodemographic and disease characteristics, such as gender and drug sensitivity, significantly influenced the outcomes. Conclusion: Weight gain during antitubercular therapy is a significant indicator of recovery influenced by socio-demographic and disease related factors. Addressing them through targeted nutritional interventions and regular monitoring is crucial.