Adherence to secondary preventive treatment following myocardial infarction with and without obstructive coronary artery disease

Adherence to secondary preventive treatment following myocardial infarction with and without obstructive coronary artery disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Adherence to secondary preventive treatment following myocardial infarction with and without obstructive coronary artery disease Anna M Nordenskjöld, Miriam Qvarnström, Björn Wettermark, Bertil Lindahl This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3792322/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Secondary preventive medications following myocardial infarction (MI) reduce the risk of new cardiovascular events. Discontinuation and suboptimal adherence are common and affect prognosis. However, there is limited knowledge regarding adherence in patients with myocardial infarction with non-obstructive coronary arteries (MINOCA). We therefore aim to evaluate the adherence to guideline recommended medications in patients with MINOCA and myocardial infarction with obstructive coronary arteries (MI-CAD). Methods This was a Swedish nationwide observational study of MI patients recorded in the SWEDEHEART registry between 2006─2017. A total of 9,138 MINOCA and 107,240 MI-CAD patients were followed for a mean 5.9 years. Initiation of therapy, implementation determined using medication possession rate, and persistence rates during different time periods were calculated. Results Patients with MINOCA were less frequently prescribed secondary preventive medications than MI-CAD. The percentage of patients taking medication as prescribed were lower in MINOCA than in MI-CAD at all time points; during months 6─12 after discharge: aspirin 94.8% vs 97.2% (p < 0.001), statins 90.3% vs 94.7% (p < 0.001), and ACEI/ARBs 97.7% vs 98.5% (p = 0.002) and at 12 months: aspirin 84.4% vs 93.7% (p < 0.001), statins 83.8% vs 94.8% (p < 0.001), ACEI/ARBs 85.0% vs 92.2% (p < 0.001) and beta blockers 80.4% vs 89.6% (p < 0.001). Conclusion The rates of initiation, implementation, and persistence of secondary preventive medications were high in both MINOCA and MI-CAD patients during the first 5 years after MI. The lower rates in patients with MINOCA may be partially due to uncertainties regarding the diagnosis of MINOCA, differences in patient characteristics, and psychosocial factors. Medical adherence cardiovascular disease myocardial infarction with non-obstructive coronary arteries (MINOCA) Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Outcomes after acute myocardial infarction (MI) can be improved by lifestyle changes; control of cardiovascular risk factors; and treatment with secondary preventive medications, such as aspirin, P2Y12-inhibitors, statins, beta blockers, angiotensin-converting enzyme inhibitors (ACEIs), and/or angiotensin-receptor blockers (ARBs), all of which are recommended in international guidelines [ 1 – 3 ]. Suboptimal treatment after MI has been repeatedly observed, with too few patients initiated on recommended secondary preventive treatments and many patients showing insufficient adherence to medication [ 4 – 13 ]. Poor adherence to prescribed secondary preventive drugs has been found to adversely affect patient prognosis [ 6 , 9 – 12 ]. About 6–8% of patients who experience MI are diagnosed with myocardial infarction with non-obstructive coronary arteries (MINOCA) [ 14 , 15 ]. Although this disorder was first recognized in the early 1980’s [ 16 – 18 ], diagnostic criteria and treatment recommendations for MINOCA have only recently been established [ 19 , 2 , 20 ]. An AHA scientific statement from 2019 suggests that secondary preventive therapies might be considered on an individual basis in patients with MINOCA [ 20 ]. The guidelines from European Society of cardiology from 2020 recommend that patients with MINOCA, of unknown cause, might be followed-up similarly to patients diagnosed with MI with obstructive coronary arteries (MI-CAD), and be treated according to secondary prevention guidelines for atherosclerotic disease (class IIb recommendation) [ 2 ]. Recommendation on duration of the treatment is however scarce. The percentage prescribed secondary preventive drugs has been shown to be lower in patients with MINOCA than in those with MI-CAD in clinical routine [ 21 , 22 ]. However, knowledge is lacking regarding adherence to medical treatment in patients with MINOCA and whether the adherence differ between patients with MINOCA and MI-CAD. The present study therefore compared prescribing and different medication adherence measures, including initiation, implementation, and persistence rates of secondary preventive drug treatment in patients with MINOCA and MI-CAD. Methods Patient selection The present study is a Swedish nationwide register-based cohort study, based on the 155,518 unique patients in the SWEDEHEART registry [ 23 ], who were hospitalised because of acute MI and discharged between January 1, 2006 and December 31, 2017. Patient with at least one coronary stenos ≥ 50% at coronary angiography were labelled MI-CAD and patients without were labelled MINOCA. Patients were excluded if they did not undergo in-hospital diagnostic coronary angiography, if their result of the coronary angiography was unknown, died within 30 days after discharge, or were receiving automatically dispensed doses of medication before admission to hospital. Patients who previously underwent percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) were included in the MI-CAD group independently on findings at the latest coronary angiography. The final study cohort consisted of 116,378 individuals, 9138 with MINOCA and 107,240 with MI-CAD (Fig. 1). Patient were followed from the date of hospital discharge to the date of death or end of the study period, whichever occurred first. Patients were censored at death or and at the end of the study period. Figure 1 Study population Caption: Patients were excluded if they did not undergo in-hospital diagnostic coronary angiography, if their result of the coronary angiography is unknown, died within 30 days after discharge, or were automatically dispensed doses of medication. Patients with previous PCI or CABG were considered to have a MI-CAD. Data sources This study used data from three Swedish national registries linked through the unique social security number that all Swedish citizens have. The data from SWEDEHEART were merged with census data (migration and death) for the Swedish population and two Swedish population-based mandatory national registries maintained by the National Board of Health and Welfare: the ‘Patient Register,’ which includes all ICD-codes for all hospital admissions [ 24 ], and the ‘Prescribed Drug Register,’ which contains data from pharmacies on drugs prescribed to individual patients [ 25 ]. Data on medication at hospital admission and hospital discharge were retrieved from the SWEDEHEART registry. Data regarding filled prescriptions for medications 6 months before hospital admission, and 1 and 6 months and 1–3 and 5 years after hospital admission, were retrieved from the Prescribed Drug Register. Data on prescriptions for the following pharmaceuticals were included: acetylsalicylic acid (ATC-code B01AC06); P2Y12-inhibitors (B01AC04, B01AC22 and B01AC24); statins (C10AA and C10BA); beta blockers (C07); ACEs/ARBs including fixed combinations with thiazides (C09); Vitamin K antagonists (B01AA03); and novel oral anticoagulants (B01AE07, B01AF01, B01AF02 and B01AF03). Assessment of prescribing and medication adherence All three constructs of adherence to medication, namely initiation, implementation and persistence, were evaluated [ 26 ]. In assessing adherence to medication only patients who received their first prescription for the above-mentioned drugs at hospital discharge were included, to minimize selection bias, as the prevalence of medications at admission differed significantly in the MINOCA and MI-CAD cohorts. Patients with ongoing use of a certain drug class and those prescribed a certain drug class within 6 months prior to MI were excluded from analyses on that particular drug class; however, these patients were eligible for inclusion and analysis regarding prescription of other drug classes. The time of follow-up was divided into six periods, 2–6 months, 6–12 months, 1–2 years, 2–3 years and 3–5 years (Fig. 2). Figure 2 Study design Caption: Time line demonstrating the times for initiation, implementation, and persistence of secondary preventive medications. Initiation; a filled prescription within 30 days after discharge. Persistence; the length of time between initiation and discontinuation of medical treatment (> 45 days without refilled prescription). Non-persistent; patients discontinued treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients. Implementation; the extent to which a patient’s actual dosing regimen corresponded to the prescribed dosing regimen. Initiation Initiation was defined as the percentage of patients who had a drug prescription from a physician and dispensed the drug at a pharmacy within 30 days after discharge. Only patients who initiated the drug therapy were included in further analyses of implementation, discontinuation and persistence of that drug class. Implementation Drug implementation, defined as the extent to which a patient’s actual dosing regimen corresponded to the prescribed dosing regimen, was estimated by determining the medication possession ratio (MPR) [ 27 , 26 ]. Briefly, for each time-period, the number of days a drug was available was divided by the number of days in that time-period. Stockpiling was included. The proportion of days with drug available was categorized as < 50%, 50–80% and 80–100%, with an MPR ≥ 80% defined as high implementation [ 6 , 9 , 28 , 11 , 12 , 26 , 29 ]. Persistence Persistence in the present study was defined as the length of time between initiation and discontinuation of medical treatment. Patients were regarded as taking a drug as long as the prescription was refilled within the estimated time of the previous prescription, including drugs carried over from previous prescriptions. A grace period of 45 days was allowed, in which patients were considered continuously exposed to a drug if they refilled a prescription within 45 days after the estimated completion of previous prescriptions (Fig. 2). The 45-day grace period were used to establish a reasonable balance between the need for monitoring short-term implementation and long-term persistence [ 27 ]. Patients were allowed to switch between drugs within the same drug class and still be considered persistent. If a patient failed to fill a new prescription within a given time, the date of non-persistence was defined as the calculated end of supply from the most recent prescription, including any stockpiling. On the first day of each interval, the proportion of persistent patients was calculated by dividing the number of persistent patients by the number of patients remaining in the cohort. Patients who discontinued treatment were labeled non-persistent. Those who restarted treatment after being considered non-persistent were followed as a separate restarter group. The group users was defined as the sum of persistent and restarting patients. This provided an opportunity to capture patients restarting treatment after non-persistence and to calculate the actual proportion of patients receiving treatment at a certain time. Implementation was assessed only in patients who were persistent or users, to avoid confusing low implementation with non-persistence. Patients who discontinued treatment and didn´t refill their prescription within 45 days were labeled non-persistent, whereas patients who continued to refill their prescription but took their medication less than 80% of the days were labeled persistent with low implementation. . Statistics Normally distributed continuous variables were presented as mean ± standard deviation (SD) and compared by Students’ t-tests, whereas non normally distributed continuous variables were presented as median and inter quartile range (IQR) and compared by Mann Whitney U-tests. Categorical variables were presented as frequencies and compared by Chi-square test. Multivariable logistic regression analyses were performed to investigate the association between MINOCA/MI-CAD status and the persistence of included medications at 12 months, adjusted for relevant covariates. Statistical analyses were performed using SAS Software Version 9.4 (SAS Institute, Cary, NC, USA) and the Predictive Analytical SoftWare (PASW statistics 17.03) program (SPSS Inc, Chicago, IL, USA). All statistical tests were two-tailed, with p < 0.05 regarded as statistically significant. Results A total of 9,138 patients diagnosed with MINOCA and 107,240 diagnosed with MI-CAD were followed-up for a mean 5.9 years. A comparison of their baseline characteristics showed that patients with MINOCA were more often younger women with fewer risk factors for cardiovascular disease (Table 1 ). Table 1 Baseline demographic and clinical characteristics of the study population. MINOCA MI-CAD p-value* Total, n 9138 107240 Demographics Female, n (%) 5774 (63.2%) 30191 (28.2%) < 0.001 Age, y, mean (± SD) 66 (11.6) 67 (11.4) 0.013 Risk factors, n (%) Smoking < 0.001 Never 4099 (44.9%) 40742 (38.0%) Previous 2986 (32.7%) 35004 (32.7%) Current 1672 (18.3%) 27464 (25.6%) Unknown 374 (4.1%) 3936 (3.7%) Diabetes 1144 (12.5%) 20008 (18.7%) < 0.001 Hypertension 1815 (19.9%) 21397 (20.0%) 0.836 BMI kg/m 2 , mean (± SD) 26.9 (9.3) 27.2 (5.2) < 0.001 Medical history, n (%) COPD 805 (8.8%) 5162 (4.8%) < 0.001 Kidney failure 101 (1.1%) 1690 (1.6%) < 0.001 Heart failure 301 (3.3%) 2805 (2.6%) < 0.001 Previous MI 137 (1.5%) 4030 (3.8%) < 0.001 Previous CABG 0 2845 (2.7%) < 0.001 Previous PCI 0 2654 (2.5%) < 0.001 PVD 169 (1.8%) 3208 (3.0%) < 0.001 Stroke 405 (4.4%) 5678 (5.3%) < 0.001 Laboratory findings Non-HDL mmol/L, mean (± SD) 3.6 (1.1) 3.9 (1.2) < 0.001 ECG at presention, n (%) ST-elevation 1234 (13.6%) 44502 (41.7%) < 0.001 Atrial fibrillation 728 (8.0%) 6131 (5.7%) < 0.001 LVEF during hospital stay, n (%) < 0.001 ≥ 50% 5639 (74.3%) 55556 (60.6%) 40–49% 1074 (14.1%) 20306 (22.2%) 30–39% 566 (7.5%) 11222 (12.2%) < 30% 247 (3.3%) 3754 (4.1%) Unknown 66 (0.9%) 823 (0.9%) Medication prior admission, n (%) Aspirin 1666 (18.2%) 22662 (21.1%) < 0.001 ACE-inhibitor or ARB 2679 (29.3%) 29463 (27.5%) < 0.001 Beta blocker 2184 (23.9%) 25500 (23.8%) < 0.001 DAPT 116 (6.6%) 1795 (7.6%) 0.134 Non-vitamin K anticoagulant 68 (0.7%) 591 (0.6%) 0.018 P2Y12-inhibitor 207 (2.3%) 2805 (2.6%) 0.043 Statin 1649 (18.1%) 20752 (19.4%) < 0.001 Warfarin 380 (4.2%) 2958 (2.8%) < 0.001 Medication at discharge, n (%) Aspirin 8053 (88.1%) 103177 (96.2%) < 0.001 ACEI/ARB 5914 (64.7%) 86166 (80.3%) < 0.001 Beta blocker 7335 (80.3%) 97288 (90.7%) < 0.001 DAPT 5950 (65.1%) 92553 (86.3%) < 0.001 Non-vitamin K anticoagulant 230 (2.5%) 1818 (1.7%) < 0.001 P2Y12-inhibitor 6264 (68.5%) 95506 (89.1%) < 0.001 Statin 7741 (84.7%) 102383 (95.5%) < 0.001 Warfarin 708 (7.8%) 5534 (5.2%) < 0.001 New prescriptions at discharge, n (%)** Aspirin 6474/7418 (87.3%) 80303/83604 (96.1%) < 0.001 ACEI/ARB 3320/6401 (51.9%) 57099/76513 (74.6%) < 0.001 Beta blocker 5209/6894 (75.6%) 71593/80461 (89.0%) < 0.001 Statin 6102/7444 (82.0%) 81218/85538 (94.9%) < 0.001 P2Y12-inhibitor 6053/8857 (68.3%) 91792/103034 (89.1%) < 0.001 * P-value: difference between MI-CAD and MINOCA. ** Prescriptions in patients without ongoing treatment or prescriptions 6 months prior myocardial infarction. ACEI/ARB, ACE-inhibitor or angiotensin-receptor blocker; BMI, body mass index; CABG, coronary bypass grafting; COPD, chronic obstructive pulmonary disease; DAPT, dual antiplatelet therapy; LVEF, left ventricular ejection fraction; MI, myocardial infarction; PCI, percutaneous coronary intervention; PVD, peripheral vascular disease. Prescription and initiation Patients with MINOCA were as expected less often prescribed and initiated on treatment with all assessed drug classes than patients with MI-CAD (Supplemental table 1 ). Implementation Implementation, defined as the extent to which a patient’s actual dosing regimen corresponded to the prescribed dosing regimen, was highest at the beginning of follow-up and declined slowly over time. However, the proportions of patients with high implementation to treatment with aspirin, ACEI/ARBs, and beta blockers during all time periods were high in both the MINOCA and MI-CAD groups. The proportion of patients with high implementation to treatment with statins was lower in both the MINOCA and MI-CAD groups (Fig. 3, Supplemental table 2 ). Figure 3 Implementation of secondary preventive treatment Caption: Implementation of aspirin, statins, ACEI/ARBs, and beta blockers in patients with MINOCA and MI-CAD. A medication possession ratio (MPR) ≥ 80% was defined as high implementation. Persistence Patients with MINOCA had lower persistence to all studied drug classes than patients with MI-CAD (Fig. 4, Supplemental table 1 ). The addition of restarting to persistent patients increased the rates of users of all classes of drugs, thus the difference between MINOCA and MI-CAD remained. Multivariable logistic regression analyses, after adjustment for relevant covariates, showed that persistence at 12 months remained significantly lower in the MINOCA than in the MI-CAD group (Table 2 ). Table 2 Logistic regression models of factors associated with persistence of the investigated medications at 12 months. Univariate regression P-value Multivariable regression P-value OR (95% CI) OR (95% CI) Aspirin MI-CAD 68576 Ref. Ref. MINOCA 5556 0.365 (0.338–0.395) < 0.001 0.324 (0.299–0.358) < 0.001 Statins MI-CAD 69730 Ref. Ref. MINOCA 5227 0.285 (0.263–0.309) < 0.001 0.327 (0.294–0.363) < 0.001 ACEI/ARBs MI-CAD 2810 Ref. Ref. MINOCA 49015 0.478 (0.429–0.532) < 0.001 0.519 (0.461–0.584) < 0.001 Betablockers MI-CAD 61734 Ref. Ref. MINOCA 4521 0.477 (0.441–0.515) < 0.001 0.467 (0.428–0.509) < 0.001 All multivariate analyses were adjusted for MINOCA/MI-CAD status, gender, age, BMI, smoking, previous MI, hypertension, heart failure, diabetes, kidney failure, PVD, stroke, and COPD. The model for statins was also adjusted for non-HLD cholesterol. Figure 4 Persistence of treatment Caption: Persistence; the length of time between initiation and discontinuation of medical treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients. Implementation and persistence in women A subgroup analysis of women showed that rates of implementation of aspirin and statins were significantly higher in patients with MI-CAD than in those with MINOCA, whereas there were no difference in implementation rates of ACE/ARBs and beta blockers (Supplementary Table 3). Persistence remained significantly higher in women with MI-CAD than in those with MINOCA (Supplemental Table 4). Discussion This nationwide registry-based study investigated and compared the initiation, implementation and persistence rates of secondary preventive medications in patients with MINOCA and MI-CAD. Patients with MINOCA were less frequently prescribed secondary preventive medications at discharge, showed a lower rate of filling of their first prescriptions, and had lower implementation and persistence rates than patients with MI-CAD. The proportion of patients with high implementation decreased slowly over time, although > 90% of patients in both groups initiated on aspirin, beta blockers, and ACEI/ARBs maintained a MPR ≥ 80% during the entire follow-up period. The decreasing proportion of patients taking these medications over time is in agreement with several previous studies in patients with MI [ 6 , 9 , 10 , 12 ]. A recent study of statin implementation among patients with atherosclerotic cardiovascular disease showed that only 21.4% had high implementation during the first year, decreasing to 19.8% at 3 years [ 28 ]. The different results between our study and this study may be due in part to different compositions of study cohorts and methodological differences in assessing implementation. The present study only measured implementation in patients who were persistent or labeled as users both at the beginning and the end of a time period, to avoid mix up non-implementation and non-persistence, whereas previous studies did not. Furthermore, implementation in the present study was calculated using shorter time intervals at the start of follow-up because change of medications, side effects, and subsequent discontinuation may be more frequent at the beginning of treatment. The present study found that the persistence of aspirin and statins in patients with MINOCA was in agreement with the results of previous studies assessing the persistence in MI patients at 12–18 months [ 5 , 7 , 8 ]. The rates of persistence of all medications throughout the entire follow-up period were higher in the present MI-CAD cohort than in previous studies [ 5 , 7 , 8 ]. The latter results are in agreement with a previous Swedish study investigating the long-term use of low-dose aspirin for both primary- and secondary prevention, with approximately 15% of those patients discontinuing long-term aspirin treatment after 3 years [ 30 ]. In contrast, the proportion of MINOCA patients in the present study who discontinued aspirin treatment was higher. However, the previous study found that patients who discontinued aspirin had a 37% higher rate of cardiovascular events after 3 years than those who were persistent [ 30 ]. The applicability of these findings to patients with MINOCA remains to be determined. Several principal differences between patients with MINOCA and MI-CAD may affect the initiation, implementation, and persistence of secondary preventive medical treatment. First, the uncertainty of the diagnosis of MINOCA may affect both the attending physicians and patients’ willingness to prescribe and take medicine, respectively. The cause of MINOCA still remains unclear in many patients [ 2 , 31 , 32 , 20 ]. Thus, patients with MINOCA are less likely to be prescribed secondary preventive medications, less often undergo structured follow-up, and less frequently achieve secondary preventive targets than patients with MI-CAD [ 33 , 34 ]. Second, the characteristics of patients with MINOCA differ from those with traditional MI. MINOCA patients tend to be younger, are more often women, and have fewer traditional risk factors for atherosclerotic heart disease [ 35 , 14 , 15 ]. Women with MI were found to be less likely than men to receive evidence-based therapies and have lower referral rates for cardiac rehabilitation [ 36 , 5 , 37 , 13 ]. Subgroup analysis showed that women and men had similarly high implementation and persistence rates for aspirin, ACEI/ARBs, and beta blockers, indicating that factors other than gender are important. Gender, however, may have a larger impact on the implementation and persistence of statins as perceived muscle symptoms associated with statin use are more common in women than in men [ 38 , 39 ]. None of the MINOCA patients in the present study had undergone a coronary intervention. MI patients treated without PCI are less frequently prescribed secondary preventive drugs than patients who undergo PCI [ 7 ]. Prior cardiovascular treatment has also been associated with high long-term implementation of secondary preventive treatment [ 40 ]. In contrast, patients with asymptomatic disease may be less adherent [ 13 , 41 ]. Psychosocial factors may differ in patients with MINOCA and MI-CAD. Previous Swedish studies have indicated that pre-existing psychiatric disorders are more common in patients with MINOCA [ 42 , 43 ]. Moreover, patients with MINOCA were found to have lower rates in the dimensions of vitality and mental health at 3 months follow-up than patients with MI-CAD [ 42 , 43 ]. Other psychosocial factors, such as perceived social support and sense of coherence, have been associated with long-term adherence to secondary preventive measures in patients with MI [ 44 ]. Psychological belief and attitude are important in unintentional non-adherence, and beliefs about medication are important in intentional non-adherence [ 45 ]. A recent consensus document discussing adherence to secondary preventive therapy after cardiovascular diseases, recommended focus on all the five dimensions of adherence to therapy simultaneously; including the patient, the disease, the therapy, the healthcare provider and the healthcare system [ 13 ]. Thus, improving medical adherence requires both time and commitment. Strengths and limitations This nationwide registry-based study included data from almost all patients hospitalized in Sweden for acute MI in 2006 − 2017, allowing analyses of complete and unselected patient cohorts. These findings reflect real-life practice as opposed to the setting of randomized controlled trials, thereby increasing the generalizability of the results. The use of registry reduces potential selection bias associated with studies of patients at selected hospitals or enrolled in health care insurance systems. Furthermore, restricting the assessment of implementation and persistence only to patients who had a de novo prescription for each indicated class of drugs reduced the influence of on-going prescriptions on long-term persistence. However, this registry-based analysis had several limitations. The analysis relied on ICD-codes and the possibility of coding errors cannot be ruled out. Diagnostic criteria for MINOCA were not proposed until 2017 [ 19 ], making it impossible to determine how many patients, who today would meet the criteria for MINOCA, were diagnosed with a non-MI related condition. Furthermore, cardiac magnetic resonance imaging was not used to the same extent during the study period as today and it is possible some of the patients labelled as MINOCA in this study in fact had an undiagnosed Takotsubo cardiomyopathy or myocarditis. In addition, the lack of information on patient socioeconomic status, education, and previous psychiatric illnesses may have resulted in residual confounding. The differences between this study and previous studies in the methods used to measure implementation and persistence make it difficult to compare results. Compared with many previous studies, the present study applied a stricter initial definition, measuring implementation and persistence only in patients with primary adherence to treatment, but a less rigid follow-up approach including patients who restarted treatment in the user group. Both of these factors may have resulted in higher levels of persistence at later time points than observed with other approaches, but may better reflect real world conditions. Conclusions This nationwide study demonstrated that the rates of initiation, implementation, and persistence of secondary preventive medications were high in both MINOCA and MI-CAD patients during the first 5 years after MI. These rates, however, were lower in patients with MINOCA, a difference that may be partially due to uncertainties regarding the diagnosis of MINOCA, differences in patient characteristics, and psychosocial factors. Abbreviations ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; MI-CAD, myocardial infarction with obstructive coronary arteries; MINOCA, myocardial infarction with non-obstructive coronary arteries. Declarations Funding This study was supported by a grant from the Swedish Foundation for Strategic Research. The Swedish Foundation for Strategic Research had no role in the design of the study; the collection, management, analysis, and interpretation of the data; the preparation or review of the manuscript; or the decision to submit the manuscript for publication. Competing interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the study conception and design. Material preparation, data management and analysis were performed by Anna M Nordenskjöld, Miriam Qvarnström, Björn Wettermark and Bertil Lindahl. The first draft of the manuscript was written by Anna M Nordenskjöld and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Ethics approval The study was approved by the Regional Ethical Review Board 2012/60-31/2. Consent to participate and publish Swedish law does not require written informed consent for registration in the SWEDEHEART registry, but all patients must be informed about their participation and their right to not participate and erase their data upon request. Data Availability Statement The data underlying this article will be shared on reasonable request to the corresponding author. References Amsterdam EA, Wenger NK, Brindis RG et al. 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;130(25):2354-94. doi:10.1161/CIR.0000000000000133. Collet JP, Thiele H, Barbato E et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289-367. doi:10.1093/eurheartj/ehaa575. Ibanez B, James S, Agewall S et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2018;39(2):119-77. doi:10.1093/eurheartj/ehx393. Bansilal S, Castellano JM, Garrido E et al. Assessing the Impact of Medication Adherence on Long-Term Cardiovascular Outcomes. J Am Coll Cardiol. 2016;68(8):789-801. doi:10.1016/j.jacc.2016.06.005. Eindhoven DC, Hilt AD, Zwaan TC, Schalij MJ, Borleffs CJW. Age and gender differences in medical adherence after myocardial infarction: Women do not receive optimal treatment - The Netherlands claims database. Eur J Prev Cardiol. 2018;25(2):181-9. doi:10.1177/2047487317744363. Greenland M, Knuiman MW, Hung J et al. Cardioprotective medication adherence in Western Australians in the first year after myocardial infarction: restricted cubic spline analysis of adherence-outcome relationships. Sci Rep. 2020;10(1):4315. doi:10.1038/s41598-020-60799-5. Halvorsen S, Jortveit J, Hasvold P, Thuresson M, Oie E. Initiation of and long-term adherence to secondary preventive drugs after acute myocardial infarction. BMC Cardiovasc Disord. 2016;16:115. doi:10.1186/s12872-016-0283-6. Hambraeus K, Tyden P, Lindahl B. Time trends and gender differences in prevention guideline adherence and outcome after myocardial infarction: Data from the SWEDEHEART registry. Eur J Prev Cardiol. 2016;23(4):340-8. doi:10.1177/2047487315585293. Khalaf K, Johnell K, Austin PC et al. Low adherence to statin treatment during the 1st year after an acute myocardial infarction is associated with increased 2nd-year mortality risk-an inverse probability of treatment weighted study on 54 872 patients. Eur Heart J Cardiovasc Pharmacother. 2021;7(2):141-7. doi:10.1093/ehjcvp/pvaa010. Khan R, Kaul P, Islam S et al. Drug Adherence and Long-Term Outcomes in Non-Revascularized Patients Following Acute Myocardial Infarction. Am J Cardiol. 2021;152:49-56. doi:10.1016/j.amjcard.2021.04.031. Rodriguez F, Maron DJ, Knowles JW et al. Association of Statin Adherence With Mortality in Patients With Atherosclerotic Cardiovascular Disease. JAMA Cardiol. 2019;4(3):206-13. doi:10.1001/jamacardio.2018.4936. Shang P, Liu GG, Zheng X et al. Association Between Medication Adherence and 1-Year Major Cardiovascular Adverse Events After Acute Myocardial Infarction in China. J Am Heart Assoc. 2019;8(9):e011793. doi:10.1161/JAHA.118.011793. Pedretti RFE, Hansen D, Ambrosetti M et al. How to optimize the adherence to a guideline-directed medical therapy in the secondary prevention of cardiovascular diseases: a clinical consensus statement from the European Association of Preventive Cardiology. Eur J Prev Cardiol. 2023;30(2):149-66. doi:10.1093/eurjpc/zwac204. Nordenskjold AM, Baron T, Eggers KM, Jernberg T, Lindahl B. Predictors of adverse outcome in patients with myocardial infarction with non-obstructive coronary artery (MINOCA) disease. Int J Cardiol. 2018;261:18-23. doi:10.1016/j.ijcard.2018.03.056. Pasupathy S, Lindahl B, Litwin P et al. Survival in Patients With Suspected Myocardial Infarction With Nonobstructive Coronary Arteries: A Comprehensive Systematic Review and Meta-Analysis From the MINOCA Global Collaboration. Circ Cardiovasc Qual Outcomes. 2021;14(11):e007880. doi:10.1161/CIRCOUTCOMES.121.007880. Brecker SJ. Myocardial infarction in patients with normal coronary arteries. Ann Med. 1994;26(6):383-4. doi:10.3109/07853899409148356. DeWood MA, Spores J, Notske R et al. Prevalence of total coronary occlusion during the early hours of transmural myocardial infarction. N Engl J Med. 1980;303(16):897-902. doi:10.1056/NEJM198010163031601. DeWood MA, Stifter WF, Simpson CS et al. Coronary arteriographic findings soon after non-Q-wave myocardial infarction. N Engl J Med. 1986;315(7):417-23. doi:10.1056/NEJM198608143150703. Agewall S, Beltrame JF, Reynolds HR et al. ESC working group position paper on myocardial infarction with non-obstructive coronary arteries. Eur Heart J. 2017;38(3):143-53. doi:10.1093/eurheartj/ehw149. Tamis-Holland JE, Jneid H, Reynolds HR et al. Contemporary Diagnosis and Management of Patients With Myocardial Infarction in the Absence of Obstructive Coronary Artery Disease: A Scientific Statement From the American Heart Association. Circulation. 2019;139(18):e891-e908. doi:10.1161/CIR.0000000000000670. Eggers KM, Hjort M, Baron T et al. Morbidity and cause-specific mortality in first-time myocardial infarction with nonobstructive coronary arteries. J Intern Med. 2019;285(4):419-28. doi:10.1111/joim.12857. Paolisso P, Bergamaschi L, Saturi G et al. Secondary Prevention Medical Therapy and Outcomes in Patients With Myocardial Infarction With Non-Obstructive Coronary Artery Disease. Front Pharmacol. 2019;10:1606. doi:10.3389/fphar.2019.01606. Jernberg T, Attebring MF, Hambraeus K et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Heart. 2010;96(20):1617-21. doi:10.1136/hrt.2010.198804. Ludvigsson JF, Andersson E, Ekbom A et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11:450. doi:10.1186/1471-2458-11-450. Wettermark B, Hammar N, Fored CM et al. The new Swedish Prescribed Drug Register--opportunities for pharmacoepidemiological research and experience from the first six months. Pharmacoepidemiol Drug Saf. 2007;16(7):726-35. doi:10.1002/pds.1294. Vink NM, Klungel OH, Stolk RP, Denig P. Comparison of various measures for assessing medication refill adherence using prescription data. Pharmacoepidemiol Drug Saf. 2009;18(2):159-65. doi:10.1002/pds.1698. Parker MM, Moffet HH, Adams A, Karter AJ. An algorithm to identify medication nonpersistence using electronic pharmacy databases. J Am Med Inform Assoc. 2015;22(5):957-61. doi:10.1093/jamia/ocv054. May HT, Knowlton KU, Anderson JL et al. High-statin adherence over 5 years of follow-up is associated with improved cardiovascular outcomes in patients with atherosclerotic cardiovascular disease: results from the IMPRES study. Eur Heart J Qual Care Clin Outcomes. 2022;8(3):352-60. doi:10.1093/ehjqcco/qcab024. Baumgartner PC, Haynes RB, Hersberger KE, Arnet I. A Systematic Review of Medication Adherence Thresholds Dependent of Clinical Outcomes. Front Pharmacol. 2018;9:1290. doi:10.3389/fphar.2018.01290. Sundstrom J, Hedberg J, Thuresson M et al. Low-Dose Aspirin Discontinuation and Risk of Cardiovascular Events: A Swedish Nationwide, Population-Based Cohort Study. Circulation. 2017;136(13):1183-92. doi:10.1161/CIRCULATIONAHA.117.028321. Machanahalli Balakrishna A, Ismayl M, Thandra A et al. Diagnostic Value of Cardiac Magnetic Resonance Imaging and Intracoronary Optical Coherence Tomography in Patients With a Working Diagnosis of Myocardial Infarction With Non-obstructive Coronary Arteries - A Systematic Review and Meta-analysis. Curr Probl Cardiol. 2022:101126. doi:10.1016/j.cpcardiol.2022.101126. Sorensson P, Ekenback C, Lundin M et al. Early Comprehensive Cardiovascular Magnetic Resonance Imaging in Patients With Myocardial Infarction With Nonobstructive Coronary Arteries. JACC Cardiovasc Imaging. 2021;14(9):1774-83. doi:10.1016/j.jcmg.2021.02.021. Eggers KM, Hadziosmanovic N, Baron T et al. Myocardial Infarction with Nonobstructive Coronary Arteries: The Importance of Achieving Secondary Prevention Targets. Am J Med. 2018;131(5):524-31 e6. doi:10.1016/j.amjmed.2017.12.008. Sharaf B, Wood T, Shaw L et al. Adverse outcomes among women presenting with signs and symptoms of ischemia and no obstructive coronary artery disease: findings from the National Heart, Lung, and Blood Institute-sponsored Women's Ischemia Syndrome Evaluation (WISE) angiographic core laboratory. Am Heart J. 2013;166(1):134-41. doi:10.1016/j.ahj.2013.04.002. Lindahl B, Baron T, Erlinge D et al. Medical Therapy for Secondary Prevention and Long-Term Outcome in Patients With Myocardial Infarction With Nonobstructive Coronary Artery Disease. Circulation. 2017;135(16):1481-9. doi:10.1161/CIRCULATIONAHA.116.026336. Chandrasekhar J, Gill A, Mehran R. Acute myocardial infarction in young women: current perspectives. Int J Womens Health. 2018;10:267-84. doi:10.2147/IJWH.S107371. Hyun K, Negrone A, Redfern J et al. Gender Difference in Secondary Prevention of Cardiovascular Disease and Outcomes Following the Survival of Acute Coronary Syndrome. Heart Lung Circ. 2021;30(1):121-7. doi:10.1016/j.hlc.2020.06.026. Karalis DG, Wild RA, Maki KC et al. Gender differences in side effects and attitudes regarding statin use in the Understanding Statin Use in America and Gaps in Patient Education (USAGE) study. J Clin Lipidol. 2016;10(4):833-41. doi:10.1016/j.jacl.2016.02.016. Ruscica M, Ferri N, Banach M, Sirtori CR, Corsini A. Side effects of statins-from pathophysiology and epidemiology to diagnostic and therapeutic implications. Cardiovasc Res. 2022. doi:10.1093/cvr/cvac020. Campain A, Hockham C, Sukkar L et al. Prior Cardiovascular Treatments-A Key Characteristic in Determining Medication Adherence After an Acute Myocardial Infarction. Front Pharmacol. 2022;13:834898. doi:10.3389/fphar.2022.834898. Sewitch MJ, Abrahamowicz M, Barkun A et al. Patient nonadherence to medication in inflammatory bowel disease. Am J Gastroenterol. 2003;98(7):1535-44. doi:10.1111/j.1572-0241.2003.07522.x. Daniel M, Agewall S, Berglund F et al. Prevalence of Anxiety and Depression Symptoms in Patients with Myocardial Infarction with Non-Obstructive Coronary Arteries. Am J Med. 2018;131(9):1118-24. doi:10.1016/j.amjmed.2018.04.040. Daniel M, Agewall S, Caidahl K et al. Effect of Myocardial Infarction With Nonobstructive Coronary Arteries on Physical Capacity and Quality-of-Life. Am J Cardiol. 2017;120(3):341-6. doi:10.1016/j.amjcard.2017.05.001. Nachshol M, Lurie I, Benyamini Y, Goldbourt U, Gerber Y. Role of psychosocial factors in long-term adherence to secondary prevention measures after myocardial infarction: a longitudinal analysis. Ann Epidemiol. 2020;52:35-41. doi:10.1016/j.annepidem.2020.09.016. Park Y, Park YH, Park KS. Determinants of Non-Adherences to Long-Term Medical Therapy after Myocardial Infarction: A Cross-Sectional Study. Int J Environ Res Public Health. 2020;17(10). doi:10.3390/ijerph17103585. Supplementary Files Supplementaltable120231016.docx Supplementaltable220231016.docx Supplementaltable320231212.docx Supplementaltable420231212.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3792322","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":270122040,"identity":"b0648b38-dcb7-4a7d-858b-2ec701dd0198","order_by":0,"name":"Anna M Nordenskjöld","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0002-6531-1024","institution":"Örebro University School of Medical Sciences: Orebro Universitet Institutionen for Medicinska Vetenskaper","correspondingAuthor":true,"prefix":"","firstName":"Anna","middleName":"M","lastName":"Nordenskjöld","suffix":""},{"id":270122041,"identity":"fe1b99f5-029a-4d07-a25f-7b13731efa6c","order_by":1,"name":"Miriam Qvarnström","email":"","orcid":"","institution":"Uppsala University Faculty of Pharmacy: Uppsala Universitet Farmaceutiska fakulteten","correspondingAuthor":false,"prefix":"","firstName":"Miriam","middleName":"","lastName":"Qvarnström","suffix":""},{"id":270122042,"identity":"e81346d2-50ea-47f8-80b4-f613cf118baa","order_by":2,"name":"Björn Wettermark","email":"","orcid":"","institution":"Uppsala University Faculty of Pharmacy: Uppsala Universitet Farmaceutiska fakulteten","correspondingAuthor":false,"prefix":"","firstName":"Björn","middleName":"","lastName":"Wettermark","suffix":""},{"id":270122043,"identity":"a9cc77a1-6ae5-4a05-b7b6-3e4b3253d383","order_by":3,"name":"Bertil Lindahl","email":"","orcid":"","institution":"Uppsala University: Uppsala Universitet","correspondingAuthor":false,"prefix":"","firstName":"Bertil","middleName":"","lastName":"Lindahl","suffix":""}],"badges":[],"createdAt":"2023-12-22 13:46:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3792322/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3792322/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50514979,"identity":"9be0aa5e-3609-44e8-85c0-071ccbb7a3c9","added_by":"auto","created_at":"2024-02-01 16:39:54","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":25341,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaption:\u003cstrong\u003e \u003c/strong\u003ePatients were excluded if they did not undergo in-hospital diagnostic coronary angiography, if their result of the coronary angiography is unknown, died within 30 days after discharge, or were automatically dispensed doses of medication. Patients with previous PCI or CABG were considered to have a MI-CAD.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/c8b49d7b6cb3a64bce215eab.png"},{"id":50515579,"identity":"fc681450-e9d9-4750-940a-39cc0aa7141e","added_by":"auto","created_at":"2024-02-01 16:47:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":28295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaption: Time line demonstrating the times for initiation, implementation, and persistence of secondary preventive medications. Initiation; a filled prescription within 30 days after discharge. Persistence; the length of time between initiation and discontinuation of medical treatment (\u0026gt;45 days without refilled prescription). Non-persistent; patients discontinued treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients. Implementation; the extent to which a patient’s actual dosing regimen corresponded to the prescribed dosing regimen.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/2a8b58ba0416acd0cc69ba67.png"},{"id":50515577,"identity":"4c47b218-6800-4d7c-9b1f-befef7af0e02","added_by":"auto","created_at":"2024-02-01 16:47:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":125275,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImplementation of secondary preventive treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaption: Implementation of aspirin, statins, ACEI/ARBs, and beta blockers in patients with MINOCA and MI-CAD. A medication possession ratio (MPR) ≥ 80% was defined as high implementation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/143af5b0f5a4719c5089e30f.png"},{"id":50515578,"identity":"fd0def22-9168-4dfa-86c6-88d333c953c1","added_by":"auto","created_at":"2024-02-01 16:47:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56950,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePersistence of treatment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaption: Persistence; the length of time between initiation and discontinuation of medical treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/7ad95edc32893cbef8a5bebf.png"},{"id":51876081,"identity":"05f3e778-5c1b-46ee-b6ea-6b999b2ca29b","added_by":"auto","created_at":"2024-03-01 18:49:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":814000,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/bb013727-02dd-4341-86ce-7225238dfb59.pdf"},{"id":50514984,"identity":"0e0ffda6-acfd-4560-b63d-f10f77e9c4c7","added_by":"auto","created_at":"2024-02-01 16:39:54","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":19439,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaltable120231016.docx","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/f50403d0dbe1d410c293bc1c.docx"},{"id":50514983,"identity":"5544bb47-f376-48ba-be2a-7ddd7a662edd","added_by":"auto","created_at":"2024-02-01 16:39:54","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":17205,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaltable220231016.docx","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/91928e6a568f27a864b90299.docx"},{"id":50514981,"identity":"9d4422df-46cd-4b90-8bab-e5ab5cd7e499","added_by":"auto","created_at":"2024-02-01 16:39:54","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":18076,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaltable320231212.docx","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/2b65d9cca4cd2734c153438f.docx"},{"id":50514986,"identity":"50738ee7-5dcb-447d-bc65-1c228c049243","added_by":"auto","created_at":"2024-02-01 16:39:54","extension":"docx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":20888,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaltable420231212.docx","url":"https://assets-eu.researchsquare.com/files/rs-3792322/v1/062f07149b859a6e0a17254b.docx"}],"financialInterests":"","formattedTitle":"Adherence to secondary preventive treatment following myocardial infarction with and without obstructive coronary artery disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOutcomes after acute myocardial infarction (MI) can be improved by lifestyle changes; control of cardiovascular risk factors; and treatment with secondary preventive medications, such as aspirin, P2Y12-inhibitors, statins, beta blockers, angiotensin-converting enzyme inhibitors (ACEIs), and/or angiotensin-receptor blockers (ARBs), all of which are recommended in international guidelines [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSuboptimal treatment after MI has been repeatedly observed, with too few patients initiated on recommended secondary preventive treatments and many patients showing insufficient adherence to medication [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Poor adherence to prescribed secondary preventive drugs has been found to adversely affect patient prognosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAbout 6\u0026ndash;8% of patients who experience MI are diagnosed with myocardial infarction with non-obstructive coronary arteries (MINOCA) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Although this disorder was first recognized in the early 1980\u0026rsquo;s [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], diagnostic criteria and treatment recommendations for MINOCA have only recently been established [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. An AHA scientific statement from 2019 suggests that secondary preventive therapies might be considered on an individual basis in patients with MINOCA [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The guidelines from European Society of cardiology from 2020 recommend that patients with MINOCA, of unknown cause, might be followed-up similarly to patients diagnosed with MI with obstructive coronary arteries (MI-CAD), and be treated according to secondary prevention guidelines for atherosclerotic disease (class IIb recommendation) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Recommendation on duration of the treatment is however scarce. The percentage prescribed secondary preventive drugs has been shown to be lower in patients with MINOCA than in those with MI-CAD in clinical routine [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, knowledge is lacking regarding adherence to medical treatment in patients with MINOCA and whether the adherence differ between patients with MINOCA and MI-CAD. The present study therefore compared prescribing and different medication adherence measures, including initiation, implementation, and persistence rates of secondary preventive drug treatment in patients with MINOCA and MI-CAD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient selection\u003c/h2\u003e \u003cp\u003eThe present study is a Swedish nationwide register-based cohort study, based on the 155,518 unique patients in the SWEDEHEART registry [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], who were hospitalised because of acute MI and discharged between January 1, 2006 and December 31, 2017. Patient with at least one coronary stenos\u0026thinsp;\u0026ge;\u0026thinsp;50% at coronary angiography were labelled MI-CAD and patients without were labelled MINOCA. Patients were excluded if they did not undergo in-hospital diagnostic coronary angiography, if their result of the coronary angiography was unknown, died within 30 days after discharge, or were receiving automatically dispensed doses of medication before admission to hospital. Patients who previously underwent percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) were included in the MI-CAD group independently on findings at the latest coronary angiography. The final study cohort consisted of 116,378 individuals, 9138 with MINOCA and 107,240 with MI-CAD (Fig.\u0026nbsp;1). Patient were followed from the date of hospital discharge to the date of death or end of the study period, whichever occurred first. Patients were censored at death or and at the end of the study period.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1 Study population\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCaption: Patients were excluded if they did not undergo in-hospital diagnostic coronary angiography, if their result of the coronary angiography is unknown, died within 30 days after discharge, or were automatically dispensed doses of medication. Patients with previous PCI or CABG were considered to have a MI-CAD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eThis study used data from three Swedish national registries linked through the unique social security number that all Swedish citizens have. The data from SWEDEHEART were merged with census data (migration and death) for the Swedish population and two Swedish population-based mandatory national registries maintained by the National Board of Health and Welfare: the \u0026lsquo;Patient Register,\u0026rsquo; which includes all ICD-codes for all hospital admissions [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], and the \u0026lsquo;Prescribed Drug Register,\u0026rsquo; which contains data from pharmacies on drugs prescribed to individual patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eData on medication at hospital admission and hospital discharge were retrieved from the SWEDEHEART registry. Data regarding filled prescriptions for medications 6 months before hospital admission, and 1 and 6 months and 1\u0026ndash;3 and 5 years after hospital admission, were retrieved from the Prescribed Drug Register.\u003c/p\u003e \u003cp\u003eData on prescriptions for the following pharmaceuticals were included: acetylsalicylic acid (ATC-code B01AC06); P2Y12-inhibitors (B01AC04, B01AC22 and B01AC24); statins (C10AA and C10BA); beta blockers (C07); ACEs/ARBs including fixed combinations with thiazides (C09); Vitamin K antagonists (B01AA03); and novel oral anticoagulants (B01AE07, B01AF01, B01AF02 and B01AF03).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of prescribing and medication adherence\u003c/h2\u003e \u003cp\u003eAll three constructs of adherence to medication, namely initiation, implementation and persistence, were evaluated [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In assessing adherence to medication only patients who received their first prescription for the above-mentioned drugs at hospital discharge were included, to minimize selection bias, as the prevalence of medications at admission differed significantly in the MINOCA and MI-CAD cohorts. Patients with ongoing use of a certain drug class and those prescribed a certain drug class within 6 months prior to MI were excluded from analyses on that particular drug class; however, these patients were eligible for inclusion and analysis regarding prescription of other drug classes.\u003c/p\u003e \u003cp\u003eThe time of follow-up was divided into six periods, 2\u0026ndash;6 months, 6\u0026ndash;12 months, 1\u0026ndash;2 years, 2\u0026ndash;3 years and 3\u0026ndash;5 years (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2 Study design\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCaption: Time line demonstrating the times for initiation, implementation, and persistence of secondary preventive medications. Initiation; a filled prescription within 30 days after discharge. Persistence; the length of time between initiation and discontinuation of medical treatment (\u0026gt;\u0026thinsp;45 days without refilled prescription). Non-persistent; patients discontinued treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients. Implementation; the extent to which a patient\u0026rsquo;s actual dosing regimen corresponded to the prescribed dosing regimen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eInitiation\u003c/h2\u003e \u003cp\u003eInitiation was defined as the percentage of patients who had a drug prescription from a physician and dispensed the drug at a pharmacy within 30 days after discharge. Only patients who initiated the drug therapy were included in further analyses of implementation, discontinuation and persistence of that drug class.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eImplementation\u003c/h2\u003e \u003cp\u003eDrug implementation, defined as the extent to which a patient\u0026rsquo;s actual dosing regimen corresponded to the prescribed dosing regimen, was estimated by determining the medication possession ratio (MPR) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Briefly, for each time-period, the number of days a drug was available was divided by the number of days in that time-period. Stockpiling was included. The proportion of days with drug available was categorized as \u0026lt;\u0026thinsp;50%, 50\u0026ndash;80% and 80\u0026ndash;100%, with an MPR\u0026thinsp;\u0026ge;\u0026thinsp;80% defined as high implementation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePersistence\u003c/h2\u003e \u003cp\u003ePersistence in the present study was defined as the length of time between initiation and discontinuation of medical treatment. Patients were regarded as taking a drug as long as the prescription was refilled within the estimated time of the previous prescription, including drugs carried over from previous prescriptions. A grace period of 45 days was allowed, in which patients were considered continuously exposed to a drug if they refilled a prescription within 45 days after the estimated completion of previous prescriptions (Fig.\u0026nbsp;2). The 45-day grace period were used to establish a reasonable balance between the need for monitoring short-term implementation and long-term persistence [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePatients were allowed to switch between drugs within the same drug class and still be considered persistent. If a patient failed to fill a new prescription within a given time, the date of non-persistence was defined as the calculated end of supply from the most recent prescription, including any stockpiling. On the first day of each interval, the proportion of persistent patients was calculated by dividing the number of persistent patients by the number of patients remaining in the cohort.\u003c/p\u003e \u003cp\u003ePatients who discontinued treatment were labeled non-persistent. Those who restarted treatment after being considered non-persistent were followed as a separate restarter group. The group users was defined as the sum of persistent and restarting patients. This provided an opportunity to capture patients restarting treatment after non-persistence and to calculate the actual proportion of patients receiving treatment at a certain time. Implementation was assessed only in patients who were persistent or users, to avoid confusing low implementation with non-persistence.\u003c/p\u003e \u003cp\u003ePatients who discontinued treatment and didn\u0026acute;t refill their prescription within 45 days were labeled non-persistent, whereas patients who continued to refill their prescription but took their medication less than 80% of the days were labeled persistent with low implementation. .\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eNormally distributed continuous variables were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and compared by Students\u0026rsquo; t-tests, whereas non normally distributed continuous variables were presented as median and inter quartile range (IQR) and compared by Mann Whitney U-tests. Categorical variables were presented as frequencies and compared by Chi-square test. Multivariable logistic regression analyses were performed to investigate the association between MINOCA/MI-CAD status and the persistence of included medications at 12 months, adjusted for relevant covariates. Statistical analyses were performed using SAS Software Version 9.4 (SAS Institute, Cary, NC, USA) and the Predictive Analytical SoftWare (PASW statistics 17.03) program (SPSS Inc, Chicago, IL, USA). All statistical tests were two-tailed, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 regarded as statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 9,138 patients diagnosed with MINOCA and 107,240 diagnosed with MI-CAD were followed-up for a mean 5.9 years. A comparison of their baseline characteristics showed that patients with MINOCA were more often younger women with fewer risk factors for cardiovascular disease (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic and clinical characteristics of the study population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMI-CAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal, n\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e107240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5774 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e30191 (28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, y, mean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (11.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e67 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRisk factors, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4099 (44.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e40742 (38.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2986 (32.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e35004 (32.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1672 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e27464 (25.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e374 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3936 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1144 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e20008 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1815 (19.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e21397 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI kg/m\u003csup\u003e2\u003c/sup\u003e, mean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.9 (9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e27.2 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical history, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e805 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5162 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1690 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e301 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2805 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e4030 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious CABG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2845 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious PCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2654 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e169 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3208 (3.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e405 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5678 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-HDL mmol/L, mean (\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.6 (1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3.9 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eECG at presention, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST-elevation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1234 (13.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e44502 (41.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtrial fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e728 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e6131 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLVEF during hospital stay, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5639 (74.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e55556 (60.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1074 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e20306 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e566 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e11222 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e247 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e3754 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e823 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication prior admission, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1666 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e22662 (21.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACE-inhibitor or ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2679 (29.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e29463 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2184 (23.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e25500 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1795 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-vitamin K anticoagulant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e591 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2Y12-inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2805 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1649 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e20752 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWarfarin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e380 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2958 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication at discharge, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8053 (88.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e103177 (96.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5914 (64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e86166 (80.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7335 (80.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e97288 (90.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDAPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5950 (65.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e92553 (86.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-vitamin K anticoagulant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e230 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1818 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2Y12-inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6264 (68.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e95506 (89.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7741 (84.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e102383 (95.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWarfarin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e708 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e5534 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNew prescriptions at discharge, n (%)**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6474/7418 (87.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e80303/83604 (96.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3320/6401 (51.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e57099/76513 (74.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5209/6894 (75.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e71593/80461 (89.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6102/7444 (82.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e81218/85538 (94.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2Y12-inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6053/8857 (68.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e91792/103034 (89.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e* P-value: difference between MI-CAD and MINOCA.\u003c/p\u003e \u003cp\u003e** Prescriptions in patients without ongoing treatment or prescriptions 6 months prior myocardial infarction.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eACEI/ARB, ACE-inhibitor or angiotensin-receptor blocker; BMI, body mass index; CABG, coronary bypass grafting; COPD, chronic obstructive pulmonary disease; DAPT, dual antiplatelet therapy; LVEF, left ventricular ejection fraction; MI, myocardial infarction; PCI, percutaneous coronary intervention; PVD, peripheral vascular disease.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePrescription and initiation\u003c/h2\u003e \u003cp\u003ePatients with MINOCA were as expected less often prescribed and initiated on treatment with all assessed drug classes than patients with MI-CAD (Supplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eImplementation\u003c/h2\u003e \u003cp\u003eImplementation, defined as the extent to which a patient\u0026rsquo;s actual dosing regimen corresponded to the prescribed dosing regimen, was highest at the beginning of follow-up and declined slowly over time. However, the proportions of patients with high implementation to treatment with aspirin, ACEI/ARBs, and beta blockers during all time periods were high in both the MINOCA and MI-CAD groups. The proportion of patients with high implementation to treatment with statins was lower in both the MINOCA and MI-CAD groups (Fig.\u0026nbsp;3, Supplemental table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;3 Implementation of secondary preventive treatment\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCaption: Implementation of aspirin, statins, ACEI/ARBs, and beta blockers in patients with MINOCA and MI-CAD. A medication possession ratio (MPR)\u0026thinsp;\u0026ge;\u0026thinsp;80% was defined as high implementation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePersistence\u003c/h2\u003e \u003cp\u003ePatients with MINOCA had lower persistence to all studied drug classes than patients with MI-CAD (Fig.\u0026nbsp;4, Supplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The addition of restarting to persistent patients increased the rates of users of all classes of drugs, thus the difference between MINOCA and MI-CAD remained. Multivariable logistic regression analyses, after adjustment for relevant covariates, showed that persistence at 12 months remained significantly lower in the MINOCA than in the MI-CAD group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression models of factors associated with persistence of the investigated medications at 12 months.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnivariate regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultivariable regression\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMI-CAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.365 (0.338\u0026ndash;0.395)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.324 (0.299\u0026ndash;0.358)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMI-CAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.285 (0.263\u0026ndash;0.309)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.327 (0.294\u0026ndash;0.363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI/ARBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMI-CAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.478 (0.429\u0026ndash;0.532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.519 (0.461\u0026ndash;0.584)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBetablockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMI-CAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMINOCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.477 (0.441\u0026ndash;0.515)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.467 (0.428\u0026ndash;0.509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAll multivariate analyses were adjusted for MINOCA/MI-CAD status, gender, age, BMI, smoking, previous MI, hypertension, heart failure, diabetes, kidney failure, PVD, stroke, and COPD. The model for statins was also adjusted for non-HLD cholesterol.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;4 Persistence of treatment\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCaption: Persistence; the length of time between initiation and discontinuation of medical treatment. Restarter; patients restarting treatment after being considered non-persistent. Users; the sum of persistent and restarting patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImplementation and persistence in women\u003c/h2\u003e \u003cp\u003eA subgroup analysis of women showed that rates of implementation of aspirin and statins were significantly higher in patients with MI-CAD than in those with MINOCA, whereas there were no difference in implementation rates of ACE/ARBs and beta blockers (Supplementary Table\u0026nbsp;3). Persistence remained significantly higher in women with MI-CAD than in those with MINOCA (Supplemental Table\u0026nbsp;4).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis nationwide registry-based study investigated and compared the initiation, implementation and persistence rates of secondary preventive medications in patients with MINOCA and MI-CAD. Patients with MINOCA were less frequently prescribed secondary preventive medications at discharge, showed a lower rate of filling of their first prescriptions, and had lower implementation and persistence rates than patients with MI-CAD.\u003c/p\u003e \u003cp\u003eThe proportion of patients with high implementation decreased slowly over time, although \u0026gt;\u0026thinsp;90% of patients in both groups initiated on aspirin, beta blockers, and ACEI/ARBs maintained a MPR\u0026thinsp;\u0026ge;\u0026thinsp;80% during the entire follow-up period. The decreasing proportion of patients taking these medications over time is in agreement with several previous studies in patients with MI [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A recent study of statin implementation among patients with atherosclerotic cardiovascular disease showed that only 21.4% had high implementation during the first year, decreasing to 19.8% at 3 years [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The different results between our study and this study may be due in part to different compositions of study cohorts and methodological differences in assessing implementation. The present study only measured implementation in patients who were persistent or labeled as users both at the beginning and the end of a time period, to avoid mix up non-implementation and non-persistence, whereas previous studies did not. Furthermore, implementation in the present study was calculated using shorter time intervals at the start of follow-up because change of medications, side effects, and subsequent discontinuation may be more frequent at the beginning of treatment.\u003c/p\u003e \u003cp\u003eThe present study found that the persistence of aspirin and statins in patients with MINOCA was in agreement with the results of previous studies assessing the persistence in MI patients at 12\u0026ndash;18 months [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The rates of persistence of all medications throughout the entire follow-up period were higher in the present MI-CAD cohort than in previous studies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. The latter results are in agreement with a previous Swedish study investigating the long-term use of low-dose aspirin for both primary- and secondary prevention, with approximately 15% of those patients discontinuing long-term aspirin treatment after 3 years [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In contrast, the proportion of MINOCA patients in the present study who discontinued aspirin treatment was higher. However, the previous study found that patients who discontinued aspirin had a 37% higher rate of cardiovascular events after 3 years than those who were persistent [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The applicability of these findings to patients with MINOCA remains to be determined.\u003c/p\u003e \u003cp\u003eSeveral principal differences between patients with MINOCA and MI-CAD may affect the initiation, implementation, and persistence of secondary preventive medical treatment. First, the uncertainty of the diagnosis of MINOCA may affect both the attending physicians and patients\u0026rsquo; willingness to prescribe and take medicine, respectively. The cause of MINOCA still remains unclear in many patients [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Thus, patients with MINOCA are less likely to be prescribed secondary preventive medications, less often undergo structured follow-up, and less frequently achieve secondary preventive targets than patients with MI-CAD [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSecond, the characteristics of patients with MINOCA differ from those with traditional MI. MINOCA patients tend to be younger, are more often women, and have fewer traditional risk factors for atherosclerotic heart disease [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Women with MI were found to be less likely than men to receive evidence-based therapies and have lower referral rates for cardiac rehabilitation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Subgroup analysis showed that women and men had similarly high implementation and persistence rates for aspirin, ACEI/ARBs, and beta blockers, indicating that factors other than gender are important. Gender, however, may have a larger impact on the implementation and persistence of statins as perceived muscle symptoms associated with statin use are more common in women than in men [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNone of the MINOCA patients in the present study had undergone a coronary intervention. MI patients treated without PCI are less frequently prescribed secondary preventive drugs than patients who undergo PCI [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Prior cardiovascular treatment has also been associated with high long-term implementation of secondary preventive treatment [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In contrast, patients with asymptomatic disease may be less adherent [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePsychosocial factors may differ in patients with MINOCA and MI-CAD. Previous Swedish studies have indicated that pre-existing psychiatric disorders are more common in patients with MINOCA [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Moreover, patients with MINOCA were found to have lower rates in the dimensions of vitality and mental health at 3 months follow-up than patients with MI-CAD [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Other psychosocial factors, such as perceived social support and sense of coherence, have been associated with long-term adherence to secondary preventive measures in patients with MI [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Psychological belief and attitude are important in unintentional non-adherence, and beliefs about medication are important in intentional non-adherence [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA recent consensus document discussing adherence to secondary preventive therapy after cardiovascular diseases, recommended focus on all the five dimensions of adherence to therapy simultaneously; including the patient, the disease, the therapy, the healthcare provider and the healthcare system [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Thus, improving medical adherence requires both time and commitment.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis nationwide registry-based study included data from almost all patients hospitalized in Sweden for acute MI in 2006 \u0026minus;\u0026thinsp;2017, allowing analyses of complete and unselected patient cohorts. These findings reflect real-life practice as opposed to the setting of randomized controlled trials, thereby increasing the generalizability of the results. The use of registry reduces potential selection bias associated with studies of patients at selected hospitals or enrolled in health care insurance systems. Furthermore, restricting the assessment of implementation and persistence only to patients who had a de novo prescription for each indicated class of drugs reduced the influence of on-going prescriptions on long-term persistence.\u003c/p\u003e \u003cp\u003eHowever, this registry-based analysis had several limitations. The analysis relied on ICD-codes and the possibility of coding errors cannot be ruled out. Diagnostic criteria for MINOCA were not proposed until 2017 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], making it impossible to determine how many patients, who today would meet the criteria for MINOCA, were diagnosed with a non-MI related condition. Furthermore, cardiac magnetic resonance imaging was not used to the same extent during the study period as today and it is possible some of the patients labelled as MINOCA in this study in fact had an undiagnosed Takotsubo cardiomyopathy or myocarditis. In addition, the lack of information on patient socioeconomic status, education, and previous psychiatric illnesses may have resulted in residual confounding.\u003c/p\u003e \u003cp\u003eThe differences between this study and previous studies in the methods used to measure implementation and persistence make it difficult to compare results. Compared with many previous studies, the present study applied a stricter initial definition, measuring implementation and persistence only in patients with primary adherence to treatment, but a less rigid follow-up approach including patients who restarted treatment in the user group. Both of these factors may have resulted in higher levels of persistence at later time points than observed with other approaches, but may better reflect real world conditions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis nationwide study demonstrated that the rates of initiation, implementation, and persistence of secondary preventive medications were high in both MINOCA and MI-CAD patients during the first 5 years after MI. These rates, however, were lower in patients with MINOCA, a difference that may be partially due to uncertainties regarding the diagnosis of MINOCA, differences in patient characteristics, and psychosocial factors.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin-receptor blocker; MI-CAD, myocardial infarction with obstructive coronary arteries; MINOCA, myocardial infarction with non-obstructive coronary arteries.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis study was supported by a grant from the Swedish Foundation for Strategic Research. The Swedish Foundation for Strategic Research had no role in the design of the study; the collection, management, analysis, and interpretation of the data; the preparation or review of the manuscript; or the decision to submit the manuscript for publication.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data management and analysis were performed by Anna M Nordenskj\u0026ouml;ld, Miriam Qvarnstr\u0026ouml;m, Bj\u0026ouml;rn Wettermark and Bertil Lindahl. The first draft of the manuscript was written by Anna M Nordenskj\u0026ouml;ld and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe study was approved by the Regional Ethical Review Board 2012/60-31/2.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eConsent to participate and publish\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eSwedish law does not require written informed consent for registration in the SWEDEHEART registry, but all patients must be informed about their participation and their right to not participate and erase their data upon request.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe data underlying this article will be shared on reasonable request to the corresponding author.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmsterdam EA, Wenger NK, Brindis RG et al. 2014 AHA/ACC guideline for the management of patients with non-ST-elevation acute coronary syndromes: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014;130(25):2354-94. doi:10.1161/CIR.0000000000000133.\u003c/li\u003e\n\u003cli\u003eCollet JP, Thiele H, Barbato E et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289-367. doi:10.1093/eurheartj/ehaa575.\u003c/li\u003e\n\u003cli\u003eIbanez B, James S, Agewall S et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: The Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2018;39(2):119-77. doi:10.1093/eurheartj/ehx393.\u003c/li\u003e\n\u003cli\u003eBansilal S, Castellano JM, Garrido E et al. Assessing the Impact of Medication Adherence on Long-Term Cardiovascular Outcomes. J Am Coll Cardiol. 2016;68(8):789-801. doi:10.1016/j.jacc.2016.06.005.\u003c/li\u003e\n\u003cli\u003eEindhoven DC, Hilt AD, Zwaan TC, Schalij MJ, Borleffs CJW. Age and gender differences in medical adherence after myocardial infarction: Women do not receive optimal treatment - The Netherlands claims database. Eur J Prev Cardiol. 2018;25(2):181-9. doi:10.1177/2047487317744363.\u003c/li\u003e\n\u003cli\u003eGreenland M, Knuiman MW, Hung J et al. Cardioprotective medication adherence in Western Australians in the first year after myocardial infarction: restricted cubic spline analysis of adherence-outcome relationships. Sci Rep. 2020;10(1):4315. doi:10.1038/s41598-020-60799-5.\u003c/li\u003e\n\u003cli\u003eHalvorsen S, Jortveit J, Hasvold P, Thuresson M, Oie E. Initiation of and long-term adherence to secondary preventive drugs after acute myocardial infarction. BMC Cardiovasc Disord. 2016;16:115. doi:10.1186/s12872-016-0283-6.\u003c/li\u003e\n\u003cli\u003eHambraeus K, Tyden P, Lindahl B. Time trends and gender differences in prevention guideline adherence and outcome after myocardial infarction: Data from the SWEDEHEART registry. Eur J Prev Cardiol. 2016;23(4):340-8. doi:10.1177/2047487315585293.\u003c/li\u003e\n\u003cli\u003eKhalaf K, Johnell K, Austin PC et al. Low adherence to statin treatment during the 1st year after an acute myocardial infarction is associated with increased 2nd-year mortality risk-an inverse probability of treatment weighted study on 54 872 patients. Eur Heart J Cardiovasc Pharmacother. 2021;7(2):141-7. doi:10.1093/ehjcvp/pvaa010.\u003c/li\u003e\n\u003cli\u003eKhan R, Kaul P, Islam S et al. Drug Adherence and Long-Term Outcomes in Non-Revascularized Patients Following Acute Myocardial Infarction. Am J Cardiol. 2021;152:49-56. doi:10.1016/j.amjcard.2021.04.031.\u003c/li\u003e\n\u003cli\u003eRodriguez F, Maron DJ, Knowles JW et al. Association of Statin Adherence With Mortality in Patients With Atherosclerotic Cardiovascular Disease. JAMA Cardiol. 2019;4(3):206-13. doi:10.1001/jamacardio.2018.4936.\u003c/li\u003e\n\u003cli\u003eShang P, Liu GG, Zheng X et al. Association Between Medication Adherence and 1-Year Major Cardiovascular Adverse Events After Acute Myocardial Infarction in China. J Am Heart Assoc. 2019;8(9):e011793. doi:10.1161/JAHA.118.011793.\u003c/li\u003e\n\u003cli\u003ePedretti RFE, Hansen D, Ambrosetti M et al. How to optimize the adherence to a guideline-directed medical therapy in the secondary prevention of cardiovascular diseases: a clinical consensus statement from the European Association of Preventive Cardiology. Eur J Prev Cardiol. 2023;30(2):149-66. doi:10.1093/eurjpc/zwac204.\u003c/li\u003e\n\u003cli\u003eNordenskjold AM, Baron T, Eggers KM, Jernberg T, Lindahl B. Predictors of adverse outcome in patients with myocardial infarction with non-obstructive coronary artery (MINOCA) disease. Int J Cardiol. 2018;261:18-23. doi:10.1016/j.ijcard.2018.03.056.\u003c/li\u003e\n\u003cli\u003ePasupathy S, Lindahl B, Litwin P et al. Survival in Patients With Suspected Myocardial Infarction With Nonobstructive Coronary Arteries: A Comprehensive Systematic Review and Meta-Analysis From the MINOCA Global Collaboration. Circ Cardiovasc Qual Outcomes. 2021;14(11):e007880. doi:10.1161/CIRCOUTCOMES.121.007880.\u003c/li\u003e\n\u003cli\u003eBrecker SJ. Myocardial infarction in patients with normal coronary arteries. Ann Med. 1994;26(6):383-4. doi:10.3109/07853899409148356.\u003c/li\u003e\n\u003cli\u003eDeWood MA, Spores J, Notske R et al. Prevalence of total coronary occlusion during the early hours of transmural myocardial infarction. N Engl J Med. 1980;303(16):897-902. doi:10.1056/NEJM198010163031601.\u003c/li\u003e\n\u003cli\u003eDeWood MA, Stifter WF, Simpson CS et al. Coronary arteriographic findings soon after non-Q-wave myocardial infarction. N Engl J Med. 1986;315(7):417-23. doi:10.1056/NEJM198608143150703.\u003c/li\u003e\n\u003cli\u003eAgewall S, Beltrame JF, Reynolds HR et al. ESC working group position paper on myocardial infarction with non-obstructive coronary arteries. Eur Heart J. 2017;38(3):143-53. doi:10.1093/eurheartj/ehw149.\u003c/li\u003e\n\u003cli\u003eTamis-Holland JE, Jneid H, Reynolds HR et al. Contemporary Diagnosis and Management of Patients With Myocardial Infarction in the Absence of Obstructive Coronary Artery Disease: A Scientific Statement From the American Heart Association. Circulation. 2019;139(18):e891-e908. doi:10.1161/CIR.0000000000000670.\u003c/li\u003e\n\u003cli\u003eEggers KM, Hjort M, Baron T et al. Morbidity and cause-specific mortality in first-time myocardial infarction with nonobstructive coronary arteries. J Intern Med. 2019;285(4):419-28. doi:10.1111/joim.12857.\u003c/li\u003e\n\u003cli\u003ePaolisso P, Bergamaschi L, Saturi G et al. Secondary Prevention Medical Therapy and Outcomes in Patients With Myocardial Infarction With Non-Obstructive Coronary Artery Disease. Front Pharmacol. 2019;10:1606. doi:10.3389/fphar.2019.01606.\u003c/li\u003e\n\u003cli\u003eJernberg T, Attebring MF, Hambraeus K et al. The Swedish Web-system for enhancement and development of evidence-based care in heart disease evaluated according to recommended therapies (SWEDEHEART). Heart. 2010;96(20):1617-21. doi:10.1136/hrt.2010.198804.\u003c/li\u003e\n\u003cli\u003eLudvigsson JF, Andersson E, Ekbom A et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11:450. doi:10.1186/1471-2458-11-450.\u003c/li\u003e\n\u003cli\u003eWettermark B, Hammar N, Fored CM et al. The new Swedish Prescribed Drug Register--opportunities for pharmacoepidemiological research and experience from the first six months. Pharmacoepidemiol Drug Saf. 2007;16(7):726-35. doi:10.1002/pds.1294.\u003c/li\u003e\n\u003cli\u003eVink NM, Klungel OH, Stolk RP, Denig P. Comparison of various measures for assessing medication refill adherence using prescription data. Pharmacoepidemiol Drug Saf. 2009;18(2):159-65. doi:10.1002/pds.1698.\u003c/li\u003e\n\u003cli\u003eParker MM, Moffet HH, Adams A, Karter AJ. An algorithm to identify medication nonpersistence using electronic pharmacy databases. J Am Med Inform Assoc. 2015;22(5):957-61. doi:10.1093/jamia/ocv054.\u003c/li\u003e\n\u003cli\u003eMay HT, Knowlton KU, Anderson JL et al. High-statin adherence over 5 years of follow-up is associated with improved cardiovascular outcomes in patients with atherosclerotic cardiovascular disease: results from the IMPRES study. Eur Heart J Qual Care Clin Outcomes. 2022;8(3):352-60. doi:10.1093/ehjqcco/qcab024.\u003c/li\u003e\n\u003cli\u003eBaumgartner PC, Haynes RB, Hersberger KE, Arnet I. A Systematic Review of Medication Adherence Thresholds Dependent of Clinical Outcomes. Front Pharmacol. 2018;9:1290. doi:10.3389/fphar.2018.01290.\u003c/li\u003e\n\u003cli\u003eSundstrom J, Hedberg J, Thuresson M et al. Low-Dose Aspirin Discontinuation and Risk of Cardiovascular Events: A Swedish Nationwide, Population-Based Cohort Study. Circulation. 2017;136(13):1183-92. doi:10.1161/CIRCULATIONAHA.117.028321.\u003c/li\u003e\n\u003cli\u003eMachanahalli Balakrishna A, Ismayl M, Thandra A et al. Diagnostic Value of Cardiac Magnetic Resonance Imaging and Intracoronary Optical Coherence Tomography in Patients With a Working Diagnosis of Myocardial Infarction With Non-obstructive Coronary Arteries - A Systematic Review and Meta-analysis. Curr Probl Cardiol. 2022:101126. doi:10.1016/j.cpcardiol.2022.101126.\u003c/li\u003e\n\u003cli\u003eSorensson P, Ekenback C, Lundin M et al. Early Comprehensive Cardiovascular Magnetic Resonance Imaging in Patients With Myocardial Infarction With Nonobstructive Coronary Arteries. JACC Cardiovasc Imaging. 2021;14(9):1774-83. doi:10.1016/j.jcmg.2021.02.021.\u003c/li\u003e\n\u003cli\u003eEggers KM, Hadziosmanovic N, Baron T et al. Myocardial Infarction with Nonobstructive Coronary Arteries: The Importance of Achieving Secondary Prevention Targets. Am J Med. 2018;131(5):524-31 e6. doi:10.1016/j.amjmed.2017.12.008.\u003c/li\u003e\n\u003cli\u003eSharaf B, Wood T, Shaw L et al. Adverse outcomes among women presenting with signs and symptoms of ischemia and no obstructive coronary artery disease: findings from the National Heart, Lung, and Blood Institute-sponsored Women\u0026apos;s Ischemia Syndrome Evaluation (WISE) angiographic core laboratory. Am Heart J. 2013;166(1):134-41. doi:10.1016/j.ahj.2013.04.002.\u003c/li\u003e\n\u003cli\u003eLindahl B, Baron T, Erlinge D et al. Medical Therapy for Secondary Prevention and Long-Term Outcome in Patients With Myocardial Infarction With Nonobstructive Coronary Artery Disease. Circulation. 2017;135(16):1481-9. doi:10.1161/CIRCULATIONAHA.116.026336.\u003c/li\u003e\n\u003cli\u003eChandrasekhar J, Gill A, Mehran R. Acute myocardial infarction in young women: current perspectives. Int J Womens Health. 2018;10:267-84. doi:10.2147/IJWH.S107371.\u003c/li\u003e\n\u003cli\u003eHyun K, Negrone A, Redfern J et al. Gender Difference in Secondary Prevention of Cardiovascular Disease and Outcomes Following the Survival of Acute Coronary Syndrome. Heart Lung Circ. 2021;30(1):121-7. doi:10.1016/j.hlc.2020.06.026.\u003c/li\u003e\n\u003cli\u003eKaralis DG, Wild RA, Maki KC et al. Gender differences in side effects and attitudes regarding statin use in the Understanding Statin Use in America and Gaps in Patient Education (USAGE) study. J Clin Lipidol. 2016;10(4):833-41. doi:10.1016/j.jacl.2016.02.016.\u003c/li\u003e\n\u003cli\u003eRuscica M, Ferri N, Banach M, Sirtori CR, Corsini A. Side effects of statins-from pathophysiology and epidemiology to diagnostic and therapeutic implications. Cardiovasc Res. 2022. doi:10.1093/cvr/cvac020.\u003c/li\u003e\n\u003cli\u003eCampain A, Hockham C, Sukkar L et al. Prior Cardiovascular Treatments-A Key Characteristic in Determining Medication Adherence After an Acute Myocardial Infarction. Front Pharmacol. 2022;13:834898. doi:10.3389/fphar.2022.834898.\u003c/li\u003e\n\u003cli\u003eSewitch MJ, Abrahamowicz M, Barkun A et al. Patient nonadherence to medication in inflammatory bowel disease. Am J Gastroenterol. 2003;98(7):1535-44. doi:10.1111/j.1572-0241.2003.07522.x.\u003c/li\u003e\n\u003cli\u003eDaniel M, Agewall S, Berglund F et al. Prevalence of Anxiety and Depression Symptoms in Patients with Myocardial Infarction with Non-Obstructive Coronary Arteries. Am J Med. 2018;131(9):1118-24. doi:10.1016/j.amjmed.2018.04.040.\u003c/li\u003e\n\u003cli\u003eDaniel M, Agewall S, Caidahl K et al. Effect of Myocardial Infarction With Nonobstructive Coronary Arteries on Physical Capacity and Quality-of-Life. Am J Cardiol. 2017;120(3):341-6. doi:10.1016/j.amjcard.2017.05.001.\u003c/li\u003e\n\u003cli\u003eNachshol M, Lurie I, Benyamini Y, Goldbourt U, Gerber Y. Role of psychosocial factors in long-term adherence to secondary prevention measures after myocardial infarction: a longitudinal analysis. Ann Epidemiol. 2020;52:35-41. doi:10.1016/j.annepidem.2020.09.016.\u003c/li\u003e\n\u003cli\u003ePark Y, Park YH, Park KS. Determinants of Non-Adherences to Long-Term Medical Therapy after Myocardial Infarction: A Cross-Sectional Study. Int J Environ Res Public Health. 2020;17(10). doi:10.3390/ijerph17103585.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Medical adherence, cardiovascular disease, myocardial infarction with non-obstructive coronary arteries (MINOCA)","lastPublishedDoi":"10.21203/rs.3.rs-3792322/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3792322/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eSecondary preventive medications following myocardial infarction (MI) reduce the risk of new cardiovascular events. Discontinuation and suboptimal adherence are common and affect prognosis. However, there is limited knowledge regarding adherence in patients with myocardial infarction with non-obstructive coronary arteries (MINOCA). We therefore aim to evaluate the adherence to guideline recommended medications in patients with MINOCA and myocardial infarction with obstructive coronary arteries (MI-CAD).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a Swedish nationwide observational study of MI patients recorded in the SWEDEHEART registry between 2006─2017. A total of 9,138 MINOCA and 107,240 MI-CAD patients were followed for a mean 5.9 years. Initiation of therapy, implementation determined using medication possession rate, and persistence rates during different time periods were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePatients with MINOCA were less frequently prescribed secondary preventive medications than MI-CAD. The percentage of patients taking medication as prescribed were lower in MINOCA than in MI-CAD at all time points; during months 6─12 after discharge: aspirin 94.8% vs 97.2% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), statins 90.3% vs 94.7% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and ACEI/ARBs 97.7% vs 98.5% (p\u0026thinsp;=\u0026thinsp;0.002) and at 12 months: aspirin 84.4% vs 93.7% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), statins 83.8% vs 94.8% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ACEI/ARBs 85.0% vs 92.2% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and beta blockers 80.4% vs 89.6% (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe rates of initiation, implementation, and persistence of secondary preventive medications were high in both MINOCA and MI-CAD patients during the first 5 years after MI. The lower rates in patients with MINOCA may be partially due to uncertainties regarding the diagnosis of MINOCA, differences in patient characteristics, and psychosocial factors.\u003c/p\u003e","manuscriptTitle":"Adherence to secondary preventive treatment following myocardial infarction with and without obstructive coronary artery disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-01 16:39:49","doi":"10.21203/rs.3.rs-3792322/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23c452b0-3fad-4547-b82d-83905047f959","owner":[],"postedDate":"February 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-01T18:41:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-01 16:39:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3792322","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3792322","identity":"rs-3792322","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}