ABSTRACT
BACKGROUND: The intricate interplay between type 2 diabetes mellitus (T2DM) and cardiovascular diseases (CVD) necessitates a comprehensive investigation into the cardiovascular risk landscape among individuals with T2DM. The burgeoning global burden of both conditions underscores the urgency of targeted research in this area, with the potential to inform preventive strategies and mitigate adverse cardiovascular outcomes. By unravelling the risk of CVD among T2DM patients and identifying key risk factors, the current research could pave the way for tailored interventions that could have the potential to substantially alleviate the cardiovascular burden associated with T2DM. AIMS AND OBJECTIVES: To assess the cardiovascular risk and its determinants among T2DM patients. METHODS: A cross sectional study was conducted among known diabetes patients accessing urban outreach clinic serving approximately 20,000 population across 18 urban slums in central Karnataka from September 2022 to June 2023. A pre-tested semi-structured questionnaire was used to collect information on socio-demographic details and CVD risk was assessed using QRISK3 score. Data were entered in Excel 2019 (Microsoft, Redmond, WA, USA) and analysed using SPSS version 25.0 (IBM Corp., Armonk, NY, USA) and are presented in the tables and figures. RESULTS: A total of 483 adults above 30 years participated in the study. Among them, the majority were men (67.9%). Cardiovascular risk factors were found more among males and the 10-year cardiovascular risk assessment prediction through QRISK3 score was higher among males compared to females and it was found to be statistically significant (13.5±8.6% vs. 19.5±10.1%, p<0.001). CONCLUSION: According to a comparison of cardiovascular risk variables by gender among diabetic patients using the QRISK3's 10-year risk assessment, males, smokers/tobacco users, obese, and known hypertensives had significantly greater risk.
ABSTRACT
Background: India has launched COVID vaccination program on January 16, 2021 and precautionary dose (third dose) on January 10, 2022. Our study evaluated adverse events following immunization (AEFI) among healthcare workers (HCWs) following first, second, and precautionary dose of ChAdOx1 nCoV-19 (COVISHIELD) vaccine. We also evaluated the association of AEFI with the study participants' characteristics. Objectives: (1) To assess the adverse events among HCWs following first, second, and precautionary dose of COVISHIELD vaccine. (2) To determine the factors associated with adverse events of COVISHIELD vaccine. Materials and Methods: A retrospective cohort study was conducted among HCWs of a tertiary care teaching hospital in central Karnataka from January 2021 to June 2022. A semi-structured, pretested questionnaire was used to interview the HCW of tertiary care teaching hospital regarding adverse events following first, second, and precautionary dose of COVISHIELD vaccine; data collected was entered in MS Excel 2019 and analyzed using SPSS v24.0. Results: Among 454 participants majority of them were females (231, 50.88%) and in the age group 18-27 years (151, 33.25%), and the majority were nursing staff (147, 32.37%). Adverse events were reported among 204 (44.93%) following the first dose, 149 (32.81%) after the second dose, and 230 (50.66%) participants following the precautionary dose. Generalized weakness and fever were the common adverse effects reported by participants. Conclusion: Majority of the study population did not report any adverse events following vaccination. Among the study participants who reported adverse events, most events were reported on the same day. Symptoms were mild in severity and short-lived.
ABSTRACT
Background: Artificial intelligence-based imaging is a low-cost, radiation-free solution for the breast imaging process that uses infrared radiation emitted by the body. This is a novel procedure that, when feasible, could be a better solution, particularly in underprivileged communities having low access to breast health care. Aims: To assess the acceptance and explore challenges for an artificial intelligence-based screening solution for breast health among the urban slum population. Settings and Design: A mixed-method study was conducted in urban slums of central Karnataka, India. Material and Methods: The study was carried out for a period of two years in 2019-21 among women in the reproductive age group in urban slums of central Karnataka to understand the acceptance of an artificial intelligence-based imaging solution for screening breast health. In-depth interviews were conducted to identify the strength, weaknesses, opportunities, and challenges (SWOC) screening for breast health. Statistical Analysis Used: Quantitative data were analysed using Statistical Package for the Social Sciences (SPSS) v16.0, and for qualitative data, manual descriptive content analysis was carried out, and the sub-themes were generated. Results: A total of 768 women accessed the thermalytix ® breast imaging services, the majority of them in the age group 31-40 years (35%), belonging to the Muslim religion (68.5%) with a mean monthly family income of Rs. 11,950.67/- SWOC analysis identified reduced cost for the screening services and involvement of female self-help groups (SHGs) as strengths. Weaknesses included poor breast health awareness among women and the stigma associated with breast cancer. Conclusions: Artificial intelligence-based screening is a feasible solution for breast health in low-income, low health access areas like urban slums. Engagement of the local community and active involvement of the health system is of paramount importance for the sustainability of any novel strategy.
