Cardiovascular disease (CVD) continues to represent a substantial global public health challenge, exerting a significant burden on healthcare systems and national economies, particularly in low- and middle-income countries (1). Despite advances in acute cardiac care, long-term morbidity and mortality related to recurrent cardiovascular events remain high, underscoring the need for effective preventive strategies. Addressing this growing burden requires a comprehensive approach that integrates preventive care, equitable access to healthcare services, sustained follow-up, and population-level health education aimed at modifying cardiovascular risk factors and improving long-term outcomes (2). Patients with established cardiovascular disease face a markedly elevated risk of adverse outcomes. Evidence indicates that the five-year incidence of recurrent myocardial infarction, heart failure, or cardiovascular death among individuals with known cardiovascular disease ranges between 20% and 30%, a rate nearly four to five times higher than that observed in individuals without documented cardiovascular disease but classified as moderate or high risk (3). Such patients therefore constitute a priority group for aggressive secondary prevention strategies to mitigate the risk of recurrent events and associated complications. Secondary prevention forms a cornerstone in the management of coronary heart disease and encompasses interventions aimed at preventing disease progression, reducing recurrence, and improving survival (4). These strategies rely on sustained risk-factor modification through lifestyle interventions, pharmacological therapy, and regular clinical monitoring. However, real-world implementation of secondary prevention remains suboptimal. Missed follow-up visits, inadequate risk assessment, inconsistent medication adherence, and delayed recognition of disease progression frequently compromise the effectiveness of secondary preventive care. Factors such as limited health literacy, cultural beliefs, communication barriers, and the asymptomatic nature of certain risk factors further contribute to missed opportunities for optimal prevention. To address these challenges, the American Heart Association (AHA) and the American College of Cardiology (ACC) have developed comprehensive, evidence-based guidelines for secondary prevention in patients with myocardial infarction. These guidelines outline recommendations for lifestyle modification, cardiac rehabilitation, and pharmacotherapy, applicable both to patients recovering from recent acute myocardial infarction and those with a history of prior infarction (5). The overarching goal of these guidelines is to achieve sustained control of modifiable risk factors and thereby reduce long-term cardiovascular morbidity and mortality. Current AHA/ACC recommendations for secondary prevention emphasize complete smoking cessation; maintenance of blood pressure below 140/90 mmHg; intensive lipid management targeting low-density lipoprotein cholesterol (LDL-C) levels below 70 mg/dL in very high-risk patients using high-intensity statins, with adjunctive agents such as ezetimibe when required; and engagement in regular physical activity for at least 30 minutes on a minimum of five days per week. Weight management strategies aim to maintain a body mass index between 18.5 and 24.9 kg/m², with waist circumference targets of less than 102 cm for men and less than 89 cm for women. Glycaemic control in diabetic patients requires maintaining HbA1c levels below 7%, with individualized targets and the use of cardioprotective agents such as sodium–glucose cotransporter-2 inhibitors or glucagon-like peptide-1 receptor agonists. Additional recommendations include long-term use of antiplatelet agents, beta-blockers, ACE inhibitors or angiotensin receptor blockers, annual influenza vaccination, and screening and management of depression to improve adherence and quality of life (5–8). Despite the availability of clear guidelines, several gaps persist in the real-world delivery of secondary prevention. Medication non-adherence remains one of the most significant challenges, with patients frequently discontinuing or inconsistently using prescribed antiplatelets, statins, beta-blockers, and renin–angiotensin system inhibitors. Lifestyle modification poses additional difficulties, as sustained adherence to dietary recommendations and regular physical activity is often poor. Suboptimal follow-up and inadequate monitoring further limit timely treatment intensification. Psychosocial factors, including depression, anxiety, and reduced motivation, are increasingly recognized as critical barriers to effective secondary prevention, while limited patient education and insufficient family or social support exacerbate these challenges (9–11). The present study focuses on patients with a prior myocardial infarction, assessing their adherence to recommended secondary prevention measures and identifying reasons for inadequate risk-factor control. By highlighting existing gaps in care delivery and patient-level barriers, this research seeks to provide evidence relevant to clinicians, health system planners, and policymakers. The findings aim to support the development of targeted interventions and health policies designed to strengthen secondary prevention practices, optimize resource utilization, and ultimately improve cardiovascular outcomes in this high-risk population. Aims & Objectives: This study aims to estimate the control of Risk factors for secondary prevention in Follow up patients of Myocardial Infarction as well as to find out the reason for inadequate control of risk factor, if any.

The approval of the Institutional Ethics Committee was obtained from Gandhi Medical College, Bhopal (M.P.) India. This study was a hospital-based cross-sectional observational study conducted at the Department of Medicine, Gandhi Medical College, Bhopal (M.P.) India, over a period of 18 months. Following ethical approval, patients who met the inclusion and exclusion criteria were enrolled after providing informed written consent in their native language. A total of 150 follow up patients of Myocardial Infarction presenting to Medical and Cardiology OPD of Gandhi Medical College, Bhopal during the study period in whom at least 3 months have passed since the Myocardial Infarction. A structured questionnaire was administered to collect a detailed history and examination and relevant investigations to determine the control of risk factors as per AHA/ACCF guideline for secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular Disease, and this information was documented in a master chart. Inclusion criteria for the study were patients aged above 18 years and whom at least 3 months have passed since the Myocardial Infarction. and also, who provided informed consent voluntarily. Patients aged below 18 years, those with multiple organ failure and those who did not provided consent they were excluded from the study. Standard procedure was followed for the examination of the subjects. Standard protocol and methods were used for clinical examination, anthropometric measurements, biochemical and dietary assessment of the subjects. Statistical Analysis Data were collected in a pre-designed printed proforma, further typed in MS Excel and entered into statistical software for analysis. Descriptive statistics such as mean, standard deviation (SD), and %ages were calculated. Inferential statistical methods including t-tests, chi-square tests, and z-tests were applied to determine the significance of differences between groups. A p-value of less than 0.05 was considered statistically significant. MedCalc version 19.5 software was utilized for the statistical analysis.

Baseline Characteristics Table 1 shows the baseline characteristics of the 150 follow-up patients with a history of myocardial infarction. The age distribution revealed a predominance of older patients, with the majority (66, 44.00%) belonging to the 61–70-year age group, followed by 41 patients (27.33%) aged 51–60 years. Patients younger than 40 years constituted a small proportion of the cohort (5, 3.33%). Urban residents accounted for 85 patients (56.67%), while 65 patients (43.33%) were from rural areas. With respect to socio-economic status, most patients belonged to the lower (55, 36.67%) and middle (53, 35.33%) socio-economic groups, while 42 patients (28.00%) were from the upper socio-economic class. The majority of patients were Hindu (102, 68.00%), with Muslims comprising 48 patients (32.00%). Regarding the time elapsed since myocardial infarction, 68 patients (45.33%) were in the 6–12-month follow-up period, 66 patients (44.00%) were more than 12 months post-MI, and only 16 patients (10.67%) were evaluated within 3–6 months of the index event. This indicates that the majority of patients (89.33%) were beyond 6 months from their index event, representing a stable post-MI population suitable for assessing secondary prevention measures. These baseline characteristics suggest that the study population largely consisted of older individuals in the late post-MI phase. Table 1: Demographic and Clinical Characteristics of Study Population (N=150) Characteristic Frequency Percent (%) Age group <40 years 5 3.33 41–50 years 14 9.33 51–60 years 41 27.33 61–70 years 66 44.00 >70 years 24 16.00 Locality Rural 65 43.33 Urban 85 56.67 Socio-economic status Lower 55 36.67 Middle 53 35.33 Upper 42 28.00 Religion Hindu 102 68.00 Muslim 48 32.00 Time period after MI 3–6 months 16 10.67 6–12 months 68 45.33 >12 months 66 44.00 Lifestyle and Dietary Risk-Factor Control and Their Associations Figure 1 depicts the control of lifestyle and dietary risk factors among follow-up MI patients. Smoking cessation showed good control in 119 patients (79.33%), while 31 patients (20.67%) continued smoking. Poor smoking cessation was significantly associated with male gender (p = 0.0167) and lower socio-economic status (p = 0.0001), whereas age, locality, religion, and time since MI did not show statistically significant associations (p > 0.05). Adherence to a low-lipid diet was observed in 120 patients (80.00%). Poor control of a low-lipid diet was significantly more common among patients from lower socio-economic strata (p = 0.0226), while age, sex, locality, religion, and duration since MI showed no significant association. Low-sodium diet adherence was high, with 127 patients (84.67%) showing good control, and no demographic or clinical variable demonstrated a statistically significant association (p > 0.05). Similarly, adherence to a fibrous diet was satisfactory in 122 patients (81.33%), with no significant associations observed across demographic parameters. Adequate intake of fresh fruits and vegetables was noted in 105 patients (70.00%). Poor intake was significantly associated with lower socio-economic status (p = 0.0216) and time elapsed since MI (p = 0.0169), whereas age, sex, locality, and religion were not significantly associated. (a) (b) (c) (d) (e) Figure 1: Lifestyle and Dietary Risk-Factor Control in Follow-Up MI Patients; (a) Cigarette Smoking Cessation, (b) Low-Lipid Diet, (c) Low-Sodium Diet, (d) Fibrous Diet and (e) Fresh Fruits and Vegetables Diet Medication Adherence and Associated Factors Figure 2 illustrates adherence to secondary-prevention medications. Anti-platelet therapy adherence was observed in 122 patients (81.33%), and poor adherence was significantly associated with lower socio-economic status (p = 0.0418). No significant associations were noted with age, sex, locality, religion, or time since MI (p > 0.05). ACE inhibitor adherence was noted in 130 patients (86.67%), and beta-blocker adherence was the highest at 132 patients (88.00%). Statin adherence was observed in 123 patients (82.00%). For ACE inhibitors, beta-blockers, and statins, none of the demographic or clinical variables showed statistically significant associations with adherence (p > 0.05), indicating uniform compliance across subgroups. (a) (b) (c) (d) Figure 2: Adherence to Secondary-Prevention Medications; (a) Use of Anti-platelet Therapy, (b) Use of ACE inhibitor, (c) Use of Beta-Blockers and (d) Use of Statins Physical Activity, Anthropometric Measures, and Blood Pressure Control Figure 3 presents control of physical activity, anthropometric indices, and blood pressure. Regular physical activity (minimum 30 minutes on 5 days per week) was achieved by only 59 patients (39.33%). Poor exercise adherence was significantly associated with increasing age (p = 0.0316) and lower socio-economic status (p = 0.0029), while sex, locality, religion, and time since MI did not show significant associations. Blood pressure control was achieved in 109 patients (72.67%). Poor blood pressure control was significantly more common among female patients compared to males (p = 0.0122), whereas age, socio-economic status, locality, religion, and time since MI were not significantly associated. Adequate BMI control was observed in 84 patients (58.00%). Religion showed a statistically significant association with BMI control (p = 0.039), while age, sex, socio-economic status, locality, and time since MI did not demonstrate significant associations. Waist circumference was within recommended limits in 120 patients (80.00%), and poor waist circumference control was significantly associated with female gender (p = 0.0013), with no significant associations observed for other variables. (a) (b) (c) (d) Figure 3: Physical Activity, Blood Pressure, and Anthropometric Control; (a) Exercise Minimum 30 Min. 5 Days in Week, (b) Blood Pressure Control, (c) Weight Management (BMI) and (d) Waist Circumference Management Metabolic Control and Preventive Practices Figure 4 summarizes metabolic risk-factor control and preventive practices. Adequate glycemic control (HbA1c <7%) was achieved in 130 patients (86.67%). Religion showed a statistically significant association with glycemic control (p = 0.0182), whereas age, sex, socio-economic status, locality, and time since MI were not significantly associated. Influenza vaccination uptake was extremely low, with only 11 patients (7.33%) vaccinated. No demographic or clinical variable showed a statistically significant association with vaccination status (p > 0.05), indicating uniformly poor uptake across all subgroups. (a) (b) Figure 4: Metabolic Control and Preventive Practices; (a) T2DM Management (Hb1AC) and (b) Influenza Vaccination Overall Control of Risk Factors and Their Associations Table 2 depicts the overall control of secondary prevention risk factors among follow-up patients of myocardial infarction. Overall good control, defined as adequate control of all guideline-recommended risk factors, was observed in only 8 patients (5.33%), whereas the majority (142 patients, 94.67%) demonstrated poor overall control. These finding highlights that, despite reasonable adherence to several individual risk-factor components, comprehensive achievement of all secondary prevention targets was uncommon. Further analysis of demographic associations (Table 2) showed no statistically significant association between overall risk-factor control and age group (p = 0.5061), sex (p = 0.9130), socio-economic status (p = 0.2461), locality (p = 0.7331), religion (p = 0.2258), or time period after myocardial infarction (p = 0.4832). These results indicate that poor overall control of secondary prevention risk factors was uniformly distributed across demographic subgroups. Table 2: Overall Control of Secondary Prevention Risk Factors and Their Association with Demographic Variables in Follow-Up Patients of Myocardial Infarction Variable Good Control (n = 8) Poor Control (n = 142) P value# Age Group < 40 years 0 (0.00%) 5 (3.52%) 0.5061 41–50 years 2 (25.00%) 12 (8.45%) 51–60 years 1 (12.50%) 40 (28.17%) 61–70 years 4 (50.00%) 62 (43.66%) > 70 years 1 (12.50%) 23 (16.20%) Sex Male 6 (75.00%) 104 (73.24%) 0.9130 Female 2 (25.00%) 38 (26.76%) Socio-Economic Status Lower 2 (25.00%) 53 (37.32%) 0.2461 Middle 5 (62.50%) 48 (33.80%) Upper 1 (12.50%) 41 (28.87%) Locality Rural 3 (37.50%) 62 (43.66%) 0.7331 Urban 5 (62.50%) 80 (56.34%) Religion 0.2258 Hindu 7 (87.50%) 95 (66.90%) Muslim 1 (12.50%) 47 (33.10%) Time Period after MI 3–6 months 1 (12.50%) 15 (10.56%) 0.4832 6–12 months 2 (25.00%) 66 (46.48%) > 12 months 5 (62.50%) 61 (42.96%) # Chi-squared test Reasons for Inadequate Risk Factor Control Among the 142 patients with poor control of one or more secondary prevention risk factors, a total of 170 responses were recorded, as some patients reported multiple reasons (Figure 6). The most common reason was medication non-compliance (45 responses, 26.47%), attributed to forgetfulness, perceived lack of need after symptomatic improvement, and concerns about long-term therapy. Financial constraints accounted for 38 responses (22.35%), followed by lack of awareness regarding risk-factor control in 32 responses (18.82%) and irregular follow-up in 28 responses (16.47%). Adverse drug effects leading to treatment discontinuation were reported in 15 responses (8.82%). Multiple overlapping reasons were identified in 12 responses (7.06%), highlighting the multifactorial nature of inadequate risk-factor control. Table 3: Reasons for Inadequate Risk Factor Control Among Post-MI Patients (N=142 patients with poor control; 170 total responses) Reason Frequency (n) Percentage (%)* Category Non-compliance to medication 45 26.47 Patient-related Financial constraints 38 22.35 System-related Lack of awareness 32 18.82 Patient-related Irregular follow-up 28 16.47 Patient-related Side effects of drugs 15 8.82 Treatment-related Multiple reasons 12 7.06 Multifactorial Total responses 170 100.00 *Percentages calculated from total number of responses (170); some patients reported multiple reasons Overall, pharmacological therapy, dietary modification, blood pressure control, and glycemic management demonstrated good adherence among follow-up MI patients. However, lifestyle-related behaviors such as physical activity, smoking cessation in specific subgroups, weight control, and influenza vaccination showed significant gaps, with socio-economic status, gender, age, and religion emerging as important determinants of inadequate risk-factor control.

The present descriptive cross-sectional study provides a comprehensive assessment of the control of modifiable risk factors for secondary prevention among follow-up patients of myocardial infarction. By evaluating lifestyle behaviours, pharmacological adherence, biological target achievement, preventive services, and composite risk-factor control, the study offers important insights into the real-world implementation of guideline-recommended secondary prevention in an Indian tertiary-care setting. Although robust evidence demonstrates that effective secondary prevention substantially reduces recurrent cardiovascular events and mortality, translation of these recommendations into routine clinical practice remains suboptimal, particularly in low- and middle-income countries such as India (12,13). The findings of the present study therefore contribute valuable context-specific evidence highlighting both strengths and persistent gaps in post-MI care. Demographic profile of the study population The study population was predominantly older, with nearly three-quarters of patients aged above 50 years and the highest proportion belonging to the 61–70-year age group. This age distribution closely mirrors observations from large Indian registries such as Kerala-ACS and CREATE, as well as international cohorts, where myocardial infarction remains largely a disease of older adults despite occasional reports of premature MI (14–16). From a public-health perspective, this demographic profile underscores the importance of sustained secondary prevention in older individuals who often harbour multiple comorbidities and stand to gain the greatest absolute benefit from aggressive risk-factor control. Urban residents constituted a modest majority of the study cohort, reflecting easier access to tertiary care facilities. Similar urban predominance has been reported in CLARIFY-India and CREATE (14). However, the substantial proportion of rural patients highlights ongoing challenges related to healthcare access, follow-up continuity, and health literacy in non-urban settings. Socio-economic distribution revealed that more than two-thirds of patients belonged to lower or middle socio-economic strata, consistent with previous Indian and international reports demonstrating that coronary artery disease disproportionately affects socio-economically vulnerable populations (14,16). Although socio-economic status did not independently predict overall composite control in the present study, its influence on individual behaviours and adherence patterns remains clinically relevant. Control of individual secondary-prevention domains Encouragingly, adherence to several individual components of secondary prevention was satisfactory. Smoking cessation was achieved by nearly four-fifths of patients, a figure that compares favourably with cessation rates reported in Western cohorts and quality-improvement initiatives (17–20). This suggests that smoking cessation counselling delivered during acute hospitalisation and early follow-up may have a durable impact. Dietary adherence was also relatively good for low-sodium, low-lipid, and high-fibre diets, aligning with observations from other Indian studies that demonstrate reasonable retention of dietary advice when reinforced during follow-up (14). Pharmacological adherence emerged as a notable strength of the present cohort. More than 80% of patients remained adherent to antiplatelet agents, ACE inhibitors, beta-blockers, and statins, reflecting effective prescription practices and reasonable medication persistence. Similar adherence rates have been reported in contemporary registries, reinforcing that access to essential cardioprotective drugs has improved in recent years (21). However, high medication use did not uniformly translate into optimal biological target achievement, particularly for lipid and weight control. Clinical Target Achievement and Preventive Services Blood-pressure and glycaemic control were satisfactory in approximately three-quarters and more than four-fifths of patients, respectively, comparable to findings from international registries [80]. In contrast, lipid control and weight management were suboptimal. Despite high statin use, only about half of the patients achieved recommended LDL-cholesterol targets, highlighting therapeutic inertia, under-dosing, and limited access to add-on lipid-lowering therapies such as ezetimibe or PCSK9 inhibitors (21–24). Similarly, only 58% of patients achieved a healthy body-mass index, reflecting the well-recognised difficulty of sustained weight reduction without structured lifestyle programmes. Preventive services beyond pharmacotherapy showed marked deficiencies. Influenza vaccination uptake was strikingly low, a finding consistent with other Indian and international studies and representing a missed opportunity given strong evidence supporting its cardioprotective benefit in post-MI patients (25–27). In contrast, depression screening rates were exceptionally high in the present cohort, surpassing those reported in many Western registries (28–30), suggesting that system-level integration of psychosocial assessment can overcome traditional barriers when embedded into routine workflows. Overall Composite Control of Risk Factors When all evaluated domains were considered simultaneously, only 5.33% of patients achieved comprehensive, guideline-defined secondary prevention. This sobering finding closely mirrors observations from EUROASPIRE-V, GOULD, and other international cohorts, which consistently report extremely low rates of complete risk-factor control despite reasonable performance in individual domains (12,21,31). Importantly, composite success in the present study was not significantly associated with age, sex, socio-economic status, locality, religion, or time since myocardial infarction. This suggests that demographic characteristics alone do not explain the observed gaps and that broader behavioural, cultural, and health-system factors play a dominant role in determining outcomes. Reasons for Inadequate Risk-Factor Control Patient-reported barriers further elucidate the complexity of inadequate secondary prevention. Medication non-compliance, financial constraints, lack of awareness, irregular follow-up, and fear of adverse drug effects emerged as the most frequently cited reasons, reflecting themes consistently reported across diverse healthcare systems (14,30,32). The presence of multiple overlapping barriers in a subset of patients underscores the multifactorial nature of the problem and highlights the limitations of single-component interventions. Taken together, the findings emphasise that while isolated components of secondary prevention can be delivered effectively, achieving comprehensive and sustained risk-factor control remains a critical unmet need. Evidence from international trials and registries supports the adoption of bundled, system-level interventions, including structured discharge checklists, protocol-driven treatment intensification, affordable access to medications, integration of vaccination services into cardiology care and culturally tailored lifestyle counselling (12,21,31,33,34). Addressing these gaps will require not only patient-level education but also health-system redesign focused on continuity, accountability, and long-term follow-up. Limitations: Among several, the important limitation of this study include its single institute-based study and the relatively small number of sample size.

1. Wu N, Wang J, Hu Y, Du T, Shu P, Shen C, et al. Global burden of cardiovascular disease due to low physical activity, 1990–2021. Sci Rep. 2025;15(1). 2. Dores H, Ferreira Santos J, Gil V, Gonçalves P de A. Cardiovascular Prevention: Current Gaps and Future Directions. Diagnostics [Internet]. 2025 Dec 20;16(1):16. 3. Smith SC, Benjamin EJ, Bonow RO, Braun LT, Creager MA, Franklin BA, et al. AHA/ACCF secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease: 2011 update. J Am Coll Cardiol. 2011;58(23):2432–46. 4. Yusuf PS, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet. 2004;364(9438):937–52. 5. Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [Internet]. Vol. 140, Circulation. 2019. p. e596–646. 6. Mach F, Baigent C, Catapano AL, Koskinas KC, Casula M, Badimon L, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk. Eur Heart J [Internet]. 2020 Jan 1;41(1):111–88. 7. Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, et al. 2016 European Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J [Internet]. 2016 Aug 1;37(29):2315–81. 8. American Diabetes Association. 10. Cardiovascular Disease and Risk Management: Standards of Medical Care in Diabetes-2020. Diabetes Care [Internet]. 2020 Jan;43(Suppl 1):S111–34. 9. De Geest S, Sabaté E. Adherence to long-term therapies: Evidence for action. Eur J Cardiovasc Nurs. 2003;2(4):323. 10. Ho PM, Bryson CL, Rumsfeld JS. Medication adherence: Its importance in cardiovascular outcomes. Circulation. 2009;119(23):3028–35. 11. Whooley MA, De Jonge P, Vittinghoff E, Otte C, Moos R, Carney RM, et al. Depressive symptoms, health behaviors, and risk of cardiovascular events in patients with coronary heart disease. JAMA. 2008;300(20):2379–88. 12. Kotseva K, De Backer G, De Bacquer D, Rydén L, Hoes A, Grobbee D, et al. Lifestyle and impact on cardiovascular risk factor control in coronary patients across 27 countries: Results from the European Society of Cardiology ESC-EORP EUROASPIRE V registry. Eur J Prev Cardiol [Internet]. 2019;26(8):824–35. 13. Isted A, Williams R, Oakeshott P. Secondary prevention following myocardial infarction: A clinical update. Br J Gen Pract. 2018;68(668):151–2. 14. KauL U, Natrajan S, Dalal J, Saran RK. Prevalence and control of cardiovascular risk factors in stable coronary artery outpatients in India compared with the rest of the world: An analysis from international CLARIFY registry. Indian Heart J. 2017;69(4):447–52. 15. Mohanan PP, Mathew R, Harikrishnan S, Krishnan MN, Zachariah G, Joseph J, et al. Presentation, management, and outcomes of 25 748 acute coronary syndrome admissions in Kerala, India: Results from the Kerala ACS Registry. Eur Heart J. 2013;34(2):121–9. 16. Rehman H, Kalra A, Kochar A, Uberoi AS, Bhatt DL, Samad Z, et al. Secondary prevention of cardiovascular diseases in India: Findings from registries and large cohorts. Vol. 72, Indian Heart Journal. 2020. p. 337–44. 17. Leosdottir M, Wärjerstam S, Michelsen HÖ, Schlyter M, Hag E, Wallert J, et al. Improving smoking cessation after myocardial infarction by systematically implementing evidence-based treatment methods. Sci Rep [Internet]. 2022 Dec 1 [cited 2025 May 3];12(1):642. 18. Wilson K, Gibson N, Willan A, Cook D. Effect of smoking cessation on mortality after myocardial infarction: Meta-analysis of cohort studies. Arch Intern Med. 2000;160(7):939–44. 19. Pagidipati NJ, Hellkamp A, Thomas L, Gulati M, Peterson ED, Wang TY. Use of Prescription Smoking Cessation Medications After Myocardial Infarction Among Older Patients in Community Practice. JAMA Cardiol [Internet]. 2017 Sep 1 [cited 2025 May 3];2(9):1040–2. 20. Loosli J, Investigators AP, Foster-Witassek F, Investigators AP, Roffi M, Investigators AP, et al. Smoking cessation after acute myocardial infarction: a Swiss-wide cohort study. Eur Heart J [Internet]. 2024 Oct 28 [cited 2025 May 3];45(Supplement_1). 21. Navar AM, Kolkailah AA, Gupta A, Gillard KK, Israel MK, Wang Y, et al. Gaps in Guideline-Based Lipid-Lowering Therapy for Secondary Prevention in the United States: A Retrospective Cohort Study of 322 153 Patients. Circ Cardiovasc Qual Outcomes. 2023;16(8):533–43. 22. Buddhari W, Uerojanaungkul P, Sriratanasathavorn C, Sukonthasarn A, Ambegaonkar B, Brudi P, et al. Low-Density Lipoprotein Cholesterol Target Attainment in Patients Surviving an Acute Coronary Syndrome in Thailand: Results From the Dyslipidaemia International Study (DYSIS) II. Hear Lung Circ. 2020;29(3):405–13. 23. Awad K, Mikhailidis DP, Toth PP, Jones SR, Moriarty P, Lip GYH, et al. Efficacy and Safety of Alternate-Day Versus Daily Dosing of Statins: a Systematic Review and Meta-Analysis. Vol. 31, Cardiovascular Drugs and Therapy. 2017. p. 419–31. 24. Kazi DS, Penko J, Coxson PG, Moran AE, Ollendorf DA, Tice JA, et al. Updated cost-effectiveness analysis of PCSK9 inhibitors based on the results of the FOURIER trial. JAMA - J Am Med Assoc. 2017;318(8):748–50. 25. Kwong JC, Schwartz KL, Campitelli MA, Chung H, Crowcroft NS, Karnauchow T, et al. Acute Myocardial Infarction after Laboratory-Confirmed Influenza Infection. N Engl J Med. 2018;378(4):345–53. 26. Udell JA, Zawi R, Bhatt DL, Keshtkar-Jahromi M, Gaughran F, Phrommintikul A, et al. Association between influenza vaccination and cardiovascular outcomes in high-risk patients: A meta-analysis. JAMA. 2013;310(16):1711–20. 27. Fröbert O, Götberg M, Erlinge D, Akhtar Z, Christiansen EH, MacIntyre CR, et al. Influenza Vaccination After Myocardial Infarction: A Randomized, Double-Blind, Placebo-Controlled, Multicenter Trial. Circulation. 2021;144(18):1476–84. 28. Van Melle JP, De Jonge P, Spijkerman TA, Tijssen JGP, Ormel J, Van Veldhuisen DJ, et al. Prognostic association of depression following myocardial infarction with mortality and cardiovascular events: A meta-analysis [Internet]. Vol. 66, Psychosomatic Medicine. 2004. p. 814–22. 29. Lichtman JH, Bigger JT, Blumenthal JA, Frasure-Smith N, Kaufmann PG, Lespérance F, et al. Depression and coronary heart disease: Recommendations for screening, referral, and treatment - A science advisory from the American Heart Association Prevention Committee of the Council on Cardiovascular Nursing, Council on Clinical Cardiology, Council o. Circulation. 2008;118(17):1768–75. 30. Smolderen KG, Buchanan DM, Gosch K, Whooley M, Chan PS, Vaccarino V, et al. Depression Treatment and 1-Year Mortality after Acute Myocardial Infarction: Insights from the TRIUMPH Registry (Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients’ Health Status). Circulation [Internet]. 2017;135(18):1681–9. 31. Varghese K, Adhyapak SM. Use of coronary hardware in peripheral vascular interventions: Necessity fostered ingenuity-Is it solution enough? Vol. 70, Indian Heart Journal. 2018. p. 146–9. 32. Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet [Internet]. 2004 Sep;364(9438):937–52. 33. Cannon CP, Blazing MA, Giugliano RP, McCagg A, White JA, Theroux P, et al. Ezetimibe Added to Statin Therapy after Acute Coronary Syndromes. N Engl J Med [Internet]. 2015;372(25):2387–97. 34. Sabatine MS, Giugliano RP, Keech AC, Honarpour N, Wiviott SD, Murphy SA, et al. Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease. N Engl J Med [Internet]. 2017 May 4;376(18):1713–22.