A Study on Biochemical Markers in Myocardial Infarction in Patients at a Tertiary Hospital in Andhra Pradesh
Background Myocardial infarction MI is a leading cause of morbidity and mortality globally. While studies in various ethnic groups have explored gender- and age-related differences in MI outcomes most Indian studies focused on epidemiology. This study aimed to investigate the gender and age disparities in MI among rural and urban populations focusing on clinical biomarkers like troponin serum creatinine and platelet counts.Objective To evaluate the clinical presentation biomarker profiles and outcomes in MI patients.Methods A prospective study was conducted on 249 MI patients at a tertiary care center. Data on gender age MI type STEMI vs. NSTEMI and biomarkers troponin creatinine and platelet counts were analyzed to assess the prevalence clinical features across age groups and MI severity in rural and urban populations.Results Of the 249 MI cases 62.7 were male with most cases in the 41-60 year age group. There was nearly equal distribution between rural and urban residents. ST-Elevation Myocardial Infarction STEMI was more common 64.3. Females with Non-ST-Elevation Myocardial Infarction NSTEMI showed higher troponin levels and greater renal impairment while STEMI especially in females was linked to elevated platelet counts.Conclusion The study highlights significant gender differences in MI presentation and severity with a predominance in males and a concentration in middle-aged individuals. Females with NSTEMI exhibited more severe renal impairment while STEMI in females was associated with elevated troponin and platelet levels. These findings suggest the need for gender-specific diagnostic and management strategies for MI.
Authors
- M Swathi
- P. Maneesha
- Medisettivamsi Naga Sai Krishna
- Sadia Sultana (ORCID: https://orcid.org/0000-0002-5930-0142)
- Penagaluru Pranay Krishna
Publication Details
- Journal
- RGUHS National Journal of Public Health
- Published
- 2025-01-01
- DOI
- https://doi.org/10.26463/rnjph.10_3_10
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00