Secondary Prevention of Coronary Heart Disease. Global Perspectives PhD thesis, Utrecht University, the Netherlands, with a summary in Dutch. Author: Anna Marzà Florensa Cover design: Anna Marzà Florensa Layout: Anna Marzà Florensa Printing: Ridderprint | www.ridderprint.nl ISBN: 978-94-6506-419-2 Copyright © 2024 Anna Marza Florensa All rights reserved. No part of this thesis may be reproduced, stored or transmitted in a way or by any means without the prior permission of the author, or when applicable, the publishers of the specific papers. Financial support by the Julius Center for Health Sciences and Primary Care and the Dutch Heart Foundation for the publication of this thesis is gratefully acknowledged.
Secondary prevention of coronary heart disease Global perspectives Secundaire preventie van coronaire hartziekten: Wereldwijde perspectieven (met een samenvatting in het Nederlands) Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof. dr. H.R.B.M. Kummeling, ingevolge het besluit van het College voor Promoties in het openbaar te verdedigen op donderdag 3 oktober 2024 des ochtends te 10.15 uur door Anna Marza Florensa geboren op 31 mei 1994 te Santa Margarida de Montbui, Spanje
Promotor: Prof. dr. D.E. Grobbee Copromotoren: Dr. C.H. Vaartjes Dr. K. Klipstein-Grobusch Beoordelingscommissie: Prof. dr. M.L. Bots Prof. dr. O.H. Franco Duran Prof. dr. P. van der Harst Prof. dr. F.M.A.C. Martens Prof. dr. ir. H.M. den Ruijter (voorzitter)
CONTENTS Chapter 1 General introduction 7 Chapter 2 Prevalence of cardioprotective medication use in patients with established coronary heart disease in South America: systematic review and meta-analysis 13 Chapter 3 Risk factor clustering in men and women with CHD in the Southern Cone of Latin America 59 Chapter 4 Medication use by insurance coverage in subjects with coronary heart disease in the Southern Cone of Latin America 83 Chapter 5 Hypertension awareness, treatment, and control in coronary heart disease patients: results of the EUROASPIRE V survey conducted in 27 countries 101 Chapter 6 A global perspective on cardiovascular risk factors in patients with CHD and different educational level: SURF CHD II 137 Chapter 7 General discussion 173 Chapter 8 Summary 190 Samenvatting 192 Resumen 194 Appendices Aknowledgements 198 About the author 202 List of publications 204
Chapter 1
General introduction
8 Chapter 1 CORONARY HEART DISEASE BURDEN AND RISK FACTORS Coronary heart disease (CHD) is the leading cause of morbidity and mortality worldwide (1). In 2019, 9.14 million people died of CHD, and it is estimated that there were 189 million prevalent CHD cases (2). The prevalence of CHD is expected to increase due to population aging and high prevalence of cardiovascular risk factors (2). Most CHD deaths and disease burden are related to cardiovascular risk factors, many of which can potentially be changed, treated, and controlled (4). Patients with established CHD are at very high cardiovascular risk (5), and are two to five times more likely to experience a recurrent cardiovascular event and die due to a cardiovascular cause compared with patients without CHD (6). During the first year after a myocardial infarction, 13-34% of CHD patients will experience a recurrent event or cardiovascular death (7–9). Risk factor control is of major importance to reduce the risks of re-occurrence of cardiovascular events and mortality. Clinical guidelines recommend that patients with CHD change health behaviors, use medication to modify and control cardiovascular risk factors, and participate in cardiac rehabilitation programs (9,10). Despite these recommendations, risk factor control in secondary prevention of CHD is poor. Several studies have shown poor attainment of the targets defined by clinical guidelines: approximately 1 in 5 CHD patients smoke tobacco, 66% do not exercise enough, more than 79% are overweight and more than 35% obese, 42-46% have high blood pressure levels, and 29% high LDL cholesterol (10,11). Recent studies show that most patients use the recommended cardioprotective medications (10,11). However, lower rates of medication use have been reported in low-and middle-income countries and community settings (12,13). PATIENT CHARACTERISTICS AND SECONDARY PREVENTION OF CHD Levels of risk factor control and medication use also differ according to patient’s characteristics, and multiple surveys have reported health inequities in secondary prevention of CHD. Women, ethnic minorities, and patients with a lower socioeconomic position generally have worse risk factor control and lower use of recommended medications (13– 18). These differences may partly be attributed to factors like educational level, income, and insurance coverage. Patients with a high educational attainment tend to have better risk factor awareness and healthy literacy (19,20), which may improve their motivation to change health behaviors and adhere to treatments (11,21,22). In some countries, having private health insurance can facilitate access to care and medications for patients with a high socioeconomic position (23). GLOBAL PERSPECTIVE Globally, the burden of CHD, risk factors and their management differs by region (10,24,25). CHD death rates and age-standardized disease burden are higher in low- and middle-income countries (LMICs) compared to high income countries (HICs). Exposure to cardiovascular risk factors have increased worldwide, but also with regional variations: HICs present the
9 General Introduction 1 larger increases in high blood pressure and reductions in smoking; while LMICs face larger increases of in high body mass index (BMI) and alcohol use (26). In secondary prevention, the STABILITY and SURF I studies show geographical variation in risk factor burden, with highest rates of smoking in Eastern Europe and high BMI in North America and the Middle East (10,24). Nevertheless, surveys focusing on risk factor management in secondary prevention have been conducted mainly on HICs and hence miss regions with a high burden of CHD (9). To illustrate differences and similarities between high- and lower-income settings we have focused on South America as a case example. In this region, the prevalence and mortality of CHD have increased in the past decades, and currently it is the leading cause of mortality, causing 10.2% to 19.4% of deaths (27). Cardiovascular risk factors are highly prevalent in the general population (28) and there are marked disparities in risk factors and access to care (28–30). Despite the high burden of CHD and risk factors in this region, literature on cardiovascular risk factors is limited and fragmented (31), especially for secondary prevention in clinical settings. This highlights the need for research on secondary prevention to better understand the challenges of risk factor control, and eventually design preventive strategies that are contextualized to high burden populations in this and similar regions. RATIONALE Given the variation in CHD burden and cardiovascular risk factors in different world regions, especially low resource settings, it is necessary to explore risk factor target attainment, treatment, and patient’s characteristics in secondary prevention with a wider international perspective. In addition, there is very limited evidence on the occurrence of multiple risk factors, risk factor awareness, and health inequities related to insurance coverage in the context of secondary prevention. Achieving a wide, representative picture of secondary prevention of CHD while capturing relevant information requires tools that allow research in settings with limited resources. SURF CHD II is a survey on secondary prevention with a simplified design that requires minimal staff or time to be conducted, purposely designed to facilitate its implementation in centers with limited resources. The design of surveys determines their informativeness, representativeness and quality, directly affecting the impact they have secondary prevention of CHD. The goals of this thesis are to present an overview of the state of secondary prevention of CHD, to explore determinants of risk factor control, and to discuss the challenges and opportunities of surveys in secondary prevention. We address these topics with global perspectives and with South America as a case example. Specifically, we evaluate the use of cardioprotective medication in CHD patients and its potential determinants, with a focus on insurance coverage. We further explore potential hypertension awareness, treatment and control, and assess the role of sex and educational level on cardiovascular risk factors in CHD patients. Finally, we address the content, representativeness, and quality of surveys in secondary prevention. Here, we refer to
10 Chapter 1 the experiences working with SURF CHD II and reflect on the strengths and limitations of the survey, as well as on potential improvements in surveys to increase their impact on secondary prevention.
11 General Introduction 1 REFERENCES 1. Abbafati C, Abbas KM, Abbasi-Kangevari M, Abd-Allah F, Abdelalim A, Abdollahi M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396(10258):1204–22. 2. Visseren FLJ, MacH F, Smulders YM, Carballo D, Koskinas KC, Bäck M, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J. 2021;42(34):3227–337. 3. Johansson S, Rosengren A, Young K, Jennings E. Mortality and morbidity trends after the first year in survivors of acute myocardial infarction: A systematic review. BMC Cardiovasc Disord. 2017 Feb 7;17(1). 4. Nedkoff L, Briffa T, Murray K, Gaw J, Yates A, Sanfilippo FM, et al. Risk of early recurrence and mortality in highrisk myocardial infarction patients: A population-based linked data study. 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Lifestyle and impact on cardiovascular risk factor control in coronary patients across 27 countries: Results from the European Society of Cardiology ESC-EORP EUROASPIRE V registry. Eur J Prev Cardiol. 2019;26(8):824–35. 9. Murphy A, Palafox B, O’Donnell O, Stuckler D, Perel P, AlHabib KF, et al. Inequalities in the use of secondary prevention of cardiovascular disease by socioeconomic status: evidence from the PURE observational study. Lancet Glob Health. 2018 Mar 1;6(3):e292–301. 10. Avezum A, Oliveira GBF, Lanas F, Lopez-Jaramillo P, Diaz R, Miranda JJ, et al. Secondary CV Prevention in South America in a Community Setting: The PURE Study. Glob Heart. 2017;12(4):305–13. 11. Zhao M, Vaartjes I, Graham I, Grobbee D, Spiering W, Klipstein-Grobusch K, et al. Sex differences in risk factor management of coronary heart disease across three regions. Heart. 2017;103(20):1587–94. 12. Vynckier P, Ferrannini G, Ryden L, Jankowski P, De Backer T, Gevaert S, et al. Gender gap in risk factor control of coronary patients far from closing: Results from the European Society of Cardiology EUROASPIRE V registry. Eur J Prev Cardiol. 2022 Jan 1;29(2):344–51. 13. Schultz WM, Kelli HM, Lisko JC, Varghese T, Shen J, Sandesara P, et al. Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation. 2018;137(20):2166–78. 14. Bruthans J, Mayer O, De Bacquer D, De Smedt D, Reiner Z, Kotseva K, et al. Educational level and risk profile and risk control in patients with coronary heart disease. Eur J Prev Cardiol. 2016;23(8):881–90. 15. Minneboo M, Lachman S, Snijder MB, Vehmeijer JT, Jørstad HT, Peters RJG. Risk factor control in secondary prevention of cardiovascular disease: results from the multi-ethnic HELIUS study. Netherlands Heart Journal. 2017 Apr 8;25(4):250–7. 16. Bruthans J, Mayer O, De Bacquer D, De Smedt D, Reiner Z, Kotseva K, et al. Educational level and risk profile and risk control in patients with coronary heart disease. Eur J Prev Cardiol. 2016 May 1;23(8):881–90. 17. Ghisi GL de M, Chaves GS da S, Britto RR, Oh P. Health literacy and coronary artery disease: A systematic review. Vol. 101, Patient Education and Counseling. Elsevier Ireland Ltd; 2018. p. 177–84. 18. Peltzer S, Hellstern M, Genske A, Jünger S, Woopen C, Albus C. Health literacy in persons at risk of and patients with coronary heart disease: A systematic review. Vol. 245, Social Science and Medicine. Elsevier Ltd; 2020. 19. Tchicaya A, Lorentz N, Demarest S, Beissel J. Persistence of socioeconomic inequalities in the knowledge of cardiovascular risk factors five years after coronary angiography. European Journal of Cardiovascular Nursing. 2018 Feb 1;17(2):136–47. 20. Harrison MA, Marfo AFA, Annan A, Ankrah DNA. Access to cardiovascular medicines in low- and middle-income countries: a mini review. Vol. 8, Global Health Research and Policy. BioMed Central Ltd; 2023. 21. Zhao M, Cooney MT, Klipstein-Grobusch K, Vaartjes I, De Bacquer D, De Sutter J, et al. Simplifying the audit of risk factor recording and control: A report from an international study in 11 countries. Eur J Prev Cardiol. 2016;23(11):1202–10. 22. World-Heart-Report-2023. 23. Lopez-Jaramillo P, Joseph P, Lopez-Lopez JP, Lanas F, Avezum A, Diaz R, et al. Risk factors, cardiovascular disease, and mortality in South America: a PURE substudy. Eur Heart J. 2022 Aug 7;43(30):2841–51.
Chapter 2
Prevalence of cardioprotective medication use in patients with established coronary heart disease in South America: systematic review and meta-analysis Anna Marzà-Florensa Elizabeth Drotos Pablo Gulayin Diederick E. Grobbee Vilma Irazola Kerstin Klipstein-Grobusch Ilonca Vaartjes Glob Heart. 2022 Jun 8;17(1):37.
14 ABSTRACT BACKGROUND Coronary heart disease (CHD) is the most common cause of death globally, and clinical guidelines recommend cardioprotective medications for patients with established CHD. Suboptimal use of these medications has been reported, but information from South America is scarce. METHODS We conducted a systematic review on prevalence of secondary prevention medication in South America. We pooled prevalence estimates, analysed time-trends and guideline compliance, and identified factors associated with medication use with meta-regression models. RESULTS Seventy-three publications were included. Medication prevalence varied by class: betablockers 73.4% (95%CI 66.8%–79.1%), ACEI/ARBs 55.8%(95%CI 49.7%–61.8), antiplatelets 84.6%(95%CI 79.6%–88.5%), aspirin 85.1%(95%CI 79.7%–89.3%) and statins 78.9%(95%CI 71.2%–84.9%). The use of beta-blockers, ACEI/ARBs and statins increased since 1993. Ten publications reported low medication use and nine reported adequate use. Medication use was lower in community, public and rehabilitation settings compared to tertiary centres. CONCLUSION Cardioprotective medication use has increased, but could be further improved particularly in community settings. KEYWORDS Coronary heart disease, secondary prevention, South America, time-trends, meta-analysis
2 15 Prevalence of secondary prevention medication use in South America INTRODUCTION Coronary heart disease (CHD) is the main cause of death and one of the most important causes of disability worldwide and in South America (1). Cardioprotective medications, including antiplatelet, anti-hypertensive, lipid-lowering and hypoglycaemic medication, are effective in preventing CHD morbidity and mortality (2–4) and their long-term use in patients with established CHD is recommended by international guidelines (5). Despite guidelines for secondary prevention of CHD recommending the use of antiplatelets, statins, beta-blockers and angiotensin-converting-enzyme inhibitors (2), research shows that the use of these medications in CHD patients is suboptimal (3,6,7). This gap between guideline recommendations and clinical use has been described in high-income countries (4,8–11), but information from middle-and and low income countries, including the South American region (12), is limited. Meta-analyses have been conducted to explore this problem in North America, Europe (9) and China (13), and there is high variability by region (14) in the use of guideline-recommended medications for secondary prevention. To date, an overview and general picture of secondary prevention medication and its determinants in South America is lacking. Therefore, the aim of this systematic review is to summarize evidence on the prevalence of cardioprotective medication use for secondary prevention of CHD in South America. The secondary aims of this work are to summarize the findings on guideline compliance, examine time trends and identify potential factors associated with use of medication in patients with established CHD. METHODS Search strategy This review was registered with PROSPERO (registration number CRD42020206657) and conducted in accordance with the PRISMA guidelines (15) (Supplementary File 1). We conducted a systematic search on April 28th, 2021 on the following databases: PubMed, Embase, Cochrane, LILACS and SciELO. The search strategy contained information on the CHD diagnosis of the patients, the country where the study was performed and the most common classes of cardioprotective medications in the outpatient clinic setting. Studies published between 2000 and 2020 in English, Spanish or Portuguese and conducted in South America (Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Guyana, Paraguay, Peru, Suriname, Uruguay, Venezuela, and Guyana) reporting the prevalence of cardioprotective medications in CHD patients were included. Broad terms were included for the diagnosis of CHD: ‘coronary artery disease’, ‘myocardial infarction’, ‘ST-elevation myocardial infarction’, ‘non-ST-elevation myocardial infarction’, ‘acute coronary syndrome’, ‘angina pectoris’, ‘acute coronary syndrome’, ‘coronary atherosclerosis’, interventions such as ‘coronary artery bypass graft’ and ‘percutaneous coronary intervention’, and commonly used acronyms for these terms. For details on the search strategy and PROSPERO registration see Supplementary File 2. Eligibility criteria
16 Chapter 2 The classes of cardioprotective medications taken into account were anti-platelet drugs, lipid-lowering drugs, antihypertensive agents (beta-blockers, ACE-inhibitors, ARBs, diuretics, and nitrates), oral hypoglycaemics and insulin. Intervention studies (randomized clinical trials and non-randomized interventions) and observational studies (cross-sectional, cohort and case-control studies) were included. Case reports, case series, reviews, as well as publication types other than original articles were excluded. Study selection The publications resulting from the search were screened by the above eligibility criteria on their titles and abstracts using the platform Rayyan CQRI (16). Screening was conducted by two reviewers (ED, AMF). Each reviewer screened half of the articles, and an additional 10% of the articles was screened by the other reviewer to avoid interpersonal bias. The reviewers discussed discrepancies and unclear include/exclude decisions until consensus was reached. The publications that fulfilled the inclusion and exclusion criteria were screened on their fulltext following the same strategy. Data extraction Relevant data was extracted from the selected publications. Data extraction was performed using the electronic data capture system REDCap (17) by two reviewers (ED, AMF). Each reviewer extracted data from the articles that the other reviewer had previously screened to minimize potential bias. Collected data included information on authors, publication year, publication title, name of the study, language, period in which the study was conducted, country, study design; participants characteristics including specific diagnosis like CHD, acute coronary syndrome (ACS), coronary artery bypass graft (CABG) or percutaneous coronary intervention (PCI); percentage of women, age range, mean age, socioeconomic status (including percentage of participants in the highest income and education categories as well as percentage of employment), and cardiovascular risk factors (blood pressure, body mass index, lipids and glucose levels), care setting information (type of hospital or healthcare centre, e.g. primary care, academic hospital, tertiary hospital, rehabilitation, and whether the centre was public or private), and urbanicity. Outcome data included the prevalence of medication per medication class. In the case of drug intervention studies, we extracted data on medication prevalence at baseline. In publications with an observational design that reported medication prevalence at multiple time-points, we extracted data from the earliest time-point in order to facilitate comparison with intervention studies. If not reported directly, medication prevalence was calculated when possible. Secondary outcome data included guideline compliance (report of compliance or noncompliance), time trends (starting year of the study) and determinants associated with use of medication in patients with established CHD (outcomes reported in stratified analysis or coefficients reported in regression models). Quality assessment
17 Prevalence of secondary prevention medication use in South America 2 A tool for the quality assessment of studies reporting prevalence estimates was adapted from the previous work by Zhao et al (13), and Li et al (18) (Supplementary File 3A). For overall risk of bias assessment, we summarized risk of bias as follows: for risk of bias in each domain (study design, study population, participation rate, participants’ characteristics and outcome) 2 points were given for low risk, 1 point for moderate risk and 0 points for high or unclear risk. Publications with a score lower than 6 out of 10 were excluded. The remaining publications were classified as following: moderately low risk of bias (6-7 points), low risk of bias (8-9 points) and very low risk of bias (10 points). Reviewers ED and AMF assessed the quality of articles for which they extracted the data, and additionally they assessed the quality of 10% of the articles examined by the other reviewer. Discrepancies were discussed until consensus was achieved. Data analysis Data analysis was conducted using R Studio (19). Data on medication prevalence is expressed in percentages by class of medication. We reported the prevalence of each kind of medication separately. We presented separate categories for those articles reporting general classes of medications instead of specific drugs. In the case of antiplatelet drugs, we additionally showed the estimates of articles reporting the prevalence of aspirin, clopidogrel, and not-specified antiplatelet drugs combined because of the shared indication for these medications, and to be able to explore the use of this medication class in general. Meta-analysis was performed using a mixed model from the R package “metafor” (20) for each class of medication. The results were expressed as pooled prevalence with 95% confidence intervals (CI) and random effects, and displayed in forest plots by care setting. Heterogeneity was quantified with the I2 test. The same statistical package was used in a sensitivity analysis to analyse potential differences in prevalence between studies conducted in Brazil and in other countries. In order to explore time trends in medication use, mixed meta-regression models were fitted with the starting year of the study as covariate for each medication class. The reported prevalence of medication and the model prediction were plotted against the year the studies commenced using bubble plots to illustrate time-trends in medication use. Meta-regression models were performed to discern potential factors contributing to medication use. A mixed meta-regression model was run for each class of medication, including the following covariates: the proportion of women included, time of outcome measurement since the start of the study, diagnosis of the patients included in the study, urban region, and care setting. The full models were reduced and simpler models were compared against the full models and among them with the AIC fitting statistic. Models with the lowest AIC were selected. Results were expressed as odds ratios (OR) and 95% CI. RESULTS Study selection The search strategy resulted in 7388 publications: 2660 in LILACS, 1810 in Embase, 1538
18 Chapter 2 in SciELO, 729 in Cochrane and 651 in PubMed. After removing 1606 duplicates, 5782 publications were screened on their title and abstract. 4405 publications did not fulfil the inclusion criteria and were excluded, resulting in 1377 publications eligible for full-text screening. 1218 articles were excluded during full-text screening (Figure 1). Of the remaining 159 publications, 86 did not reach the quality threshold during the quality assessment, and therefore 73 publications were finally included in the review. Study characteristics Table 1 describes the main characteristics of the included studies. All articles included were published between 2000 and 2020, referring to studies conducted between 1993 and 2017. Most studies were conducted in Brazil (3,21–58). Six studies were conducted in Argentina (59–64), four in Chile (65–68), four in Colombia (69–72), three in Uruguay (73–75) and two were multi-country studies conducted in Argentina, Brazil, Chile and Colombia (12) and Brazil and Suriname (76). The most common language of the articles was English (58 articles), followed by Spanish (11 articles) and Portuguese (4 articles). In terms of study design, most publications reported on cohort studies (23 articles), crosssectional studies (20 publications), and baseline data of randomized clinical trials (17 articles). The number of participants included in each study ranged from 20 to 2475, with a mean of 328 (SD 424). Most studies were conducted in urban areas (39 studies). Regarding the clinical setting, the majority of studies were conducted in academic or tertiary hospitals (42 articles), six in rehabilitation centres, three in primary care or community settings, two in secondary level hospitals, two in public hospitals, and 12 in other settings.
19 Prevalence of secondary prevention medication use in South America 2 7388 publications (LILACS 2660, Embase 1810, SciELO 1538, Cochrane 729, Pubmed 651) 1377 publications eligible for full-text screening 5782 publications 1475 duplicates Search Screening 4405 excluded during title and abstract screening 1218 excluded in full-text screening: 1092 No information on outcome; 53 duplicate; 42 Full text or abstract unavailable; 45 Country; 38 Publication type; 21 wrong population; 7 wrong study design, 6 because data were used in another article (reasons for exclusion overlap) 159 publications for data extraction 86 excluded because of high risk of bias 73 publications included Data extraction Figure 1. Study selection flow-chart.
20 Chapter 2 Publication Study duration Country Study Design N Care Setting Diagnosis category Urban setting % women Age Socioeconomic Status Castillo y Costa, 2018 NA-2015 Argentina Cohort 210 MI, CABG, PCI Unclear 17.0 59.0 (9); 61.0 (9.0) Fernandes, 2012 2003-2004 Brazil RCT 45 PCI 38.0 62.7 (9.9), 26-89 Gurfinkel, 2004 2001-NA Argentina RCT 301 ACS Urban 59 (8.7), 59 (7.9) Ladeia, 2003 1995-1997 Brazil Cross-sectional 104 CHD Urban 32.7 60.9 (8.1) Education: 10.6 Lima-Filho, 2010 2001-2002 Brazil Cohort 70 PCI 22.9 57.6 (13.9), 59.4 (7.6) Lorenzo, 2014 2008-2010 Brazil Cohort 228 CHD Urban 46.1 63.15 (12.26) Baptista, 2012 2009-2011 Brazil Cohort 97 Academic or Tertiary Hospital CABG 33.3 63.5 (9.4), 42-81 Bohatch, 2015 2011-2013 Brazil Cohort 230 Academic or Tertiary Hospital CABG 24.3 Brasil, 2013 NA-NA Brazil Cross-sectional 710 Academic or Tertiary Hospital CHD Urban 57.4 (4.1) Breda, 2008 2008-2005 Brazil RCT 50 Academic or Tertiary Hospital CABG Urban 42.0 62.1 (12) Chaves, 2004 2001-2002 Brazil RCT 96 Academic or Tertiary Hospital CHD Urban 51.0 65.07 (12.49) Chaves, 2019 2015-2017 Brazil RCT 115 Academic or Tertiary Hospital CABG, PCI Urban 28.7 63.9 (10. 9), 63(12.1) Employmnent: 40 Cruz, 2009 2004-2005 Brazil Cross-sectional 103 Academic or Tertiary Hospital CHD 67.9 (12.3) Dayan, 2018 2006-2014 Uruguay retrospective 282 Academic or Tertiary Hospital CABG 26.6 65.58( 9.5) ; 61.75(9.6) Feguri, 2017 2014-2016 Brazil RCT 574 Academic or Tertiary Hospital CABG Urban 33.0 62.12 (9.63), 60.93(8.91) Fernandez, 2011 2006-2007 Colombia RCT 400 Academic or Tertiary Hospital PCI Urban 45.0 58.0 (9.0) Furuya, 2014 2011-2012 Brazil RCT 60 Academic or Tertiary Hospital PCI Urban 43.0 56.9 (10.8), 34-85 Employment: 35.0 Gomes, 2011 2002-2006 Brazil Cohort 504 Academic or Tertiary Hospital PCI Urban 35.9 63.7 (11.0) Hueb, 2004 1995-2000 Brazil RCT 611 Academic or Tertiary Hospital CHD Urban 15.0 60.25 (9.26), 58.92: (6.04) Kimura, 2018 2007-2013 Brazil Cohort 520 Academic or Tertiary Hospital CABG Urban 72.1 Table 1. Characteristics of the studies included in the review.
21 Prevalence of secondary prevention medication use in South America 2 Publication Study duration Country Study Design N Care Setting Diagnosis category Urban setting % women Age Socioeconomic Status Liberato , 2016 2010-2011 Brazil Cross-sectional 190 Academic or Tertiary Hospital ACS Urban 36.1 64.9, 32-93 Employment: 31.0 Nazzal, 2013 2008-2008 Chile Registry 416 Academic or Tertiary Hospital ACS Urban 23.4 Income: 20.0 Neira, 2013 2011-2011 Chile Cross-sectional 202 Academic or Tertiary Hospital CHD Urban 29.7 58.9(9.8); 60.6(8.5) Education: 17.4, Employment: 45.0 Nery, 2015 2009-2012 Brazil RCT 61 Academic or Tertiary Hospital ACS Urban 27.9 59.5 (9.4) Neves, 2012 NA-NA Brazil descriptive, crosssectional 20 Academic or Tertiary Hospital CHD 0.0 Noriega, 2008 NA-NA Chile Non-randomized intervention 64 Academic or Tertiary Hospital CABG, PCI 20.3 64.0 (11.0); 63(12.0) Oliveira, 2019 2013-2015 Brazil Retrospective cohort 536 Academic or Tertiary Hospital ACS Urban 36.0 65.6 Education: 49.2; Income:34.0 Pantoni, 2016 NA-NA Brazil Non-randomized intervention 27 Academic or Tertiary Hospital CABG Urban 44.4 60.0 95% CI 51-68), 63.0 (95% CI 55-70), 61.0 (95% CI 53-73) Pellegrini, 2014 2002-2007 Brazil Cohort 611 Academic or Tertiary Hospital ACS Rural 28.6 61.4 (11.6) Pesaro , 2012 2006-2009 Brazil RCT 78 Academic or Tertiary Hospital CHD Urban 38.5 64.0 (12.0), 65.0 (12.0), 61.0 (12.0) Portal, 2003 1998-1999 Brazil RCT 39 Academic or Tertiary Hospital CHD 43.6 62,7 (10.7), 61.6 (11.1) Ribeiro , 2015 2007-2008 Brazil Cross-sectional 153 Academic or Tertiary Hospital PCI Urban 49.0 61.9 (11.9) Ribeiro, 2018 2014-2016 Brazil Cohort 169 Academic or Tertiary Hospital Urban 16.0 63.7 (9.6) Rossi, 2014 2006-2006 Argentina Cohort 125 Academic or Tertiary Hospital ACS Urban 34.4 56.0 (9.0), 60.0 (9.0) Rueda-Clausen, 2010 2005-2006 Colombia Cross-sectional 34 Academic or Tertiary Hospital CHD Urban 23.5 64.0, 61.0 Saffi, 2013 2008-2010 Brazil RCT 74 Academic or Tertiary Hospital CHD 26.0 60.9(10.6), 63.4 (8.56), 59.9(11.8 ), 62.7(10.9) Income: 58.0 Santos, 2015 2007-2010 Brazil Cohort 198 Academic or Tertiary Hospital PCI 30.3 55.0 (8.0), 52.0 (7.0), 54.0 (10.0) Scherr, 2010 1997-2002 Brazil Non-randomized intervention 2337 Academic or Tertiary Hospital CHD Urban 39.2 64.3(10.7), 64.5(10.9) Table 1. Characteristics of the studies included in the review (continued).
22 Chapter 2 Publication Study duration Country Study Design N Care Setting Diagnosis category Urban setting % women Age Socioeconomic Status Silva, 2005 1995-1998 Brazil RCT 210 Academic or Tertiary Hospital CHD Urban 32.4 60.2(10), 28- 87 Silveira, 2007 2002-2003 Brazil RCT 24 Academic or Tertiary Hospital CABG 37.5 58.5(9.4) Silveira, 2008 1998-2005 Brazil Cohort 310 Academic or Tertiary Hospital CHD Unclear 39.0 Simon, 2019 2014-2015 Brazil RCT 48 Academic or Tertiary Hospital ACS 35.4 Siniawski, 2019 2014-2017 Argentina Cross-sectional 351 Academic or Tertiary Hospital ACS, CABG Urban 26.5 63.3 (12.4), 60.0 (87) Smidt, 2009 2002-2007 Brazil Registry 611 Academic or Tertiary Hospital ACS 36.6 60.9 (10.3), 31-81 Souza Groia Veloso, 2020 NA-NA Brazil, Suriname Cross-sectional 148 Academic or Tertiary Hospital CHD Unclear 29.7 Median 61.0 (IQR 54-68) Souza, 2013 2008-2010 Brazil Registry 103 Academic or Tertiary Hospital ACS Urban 16.5 62.6(9.3), 63.3(11.3) Uchoa, 2015 NA-NA Brazil Cohort 67 Academic or Tertiary Hospital CHD, CABG Urban 25.0 61.2(10.0), 68.6(9.0) Vilar, 2015 2009-2010 Brazil Cross-sectional 155 Academic or Tertiary Hospital CHD 18.7 60.0(9.0) Villacorta, 2012 2006-2008 Brazil Cohort 209 Academic or Tertiary Hospital PCI Urban 26 Median 62.0 [IQR 17.0] Abreu-Silva, 2011 2008-2010 Brazil Registry 535 Other PCI 32.0 67.0 (10.4) Alvarez, 2016 1993-2013 Argentina Cross-sectional 866 Other ACS 24.0 62.7 (11.1) Berwanger, 2013 NA-NA Brazil Cross-sectional 681 Other ACS Fernandez, 2009 2003-2006 Colombia Cohort 395 Other CHD 32.7 64.4 (12.9), 66.8 (10.9) Finimundi, 2007 NA-NA Brazil RCT 40 Other ACS Urban 43.0 60.1 (2.2), 63.21 (2.21) Gaedke, 2015 NA-NA Brazil Cohort 138 Other ACS Urban 44.4 62.5 (11.1) Education: 54.8, Income: 33.3 Gowdak, 2007 1998-2004 Brazil Cohort 119 Other CHD Urban 57.4 (5.9), 58.3 (8.6) Mattos, 2012 2010-2011 Brazil Registry 2475 Other ACS 32.2 64 (8.0); 65 (9.0), 66 (8.0) Mendis, 2005 2002-2003 Brazil Cross-sectional 836 Other CHD Both 56.0 (10.0) Vazquez , 2011 2008-2009 Uruguay Cohort 154 Other ACS 21.4 Vesga, 2006 NA-NA Colombia Cross-sectional 71 Other CHD Urban 28.2 58.4 (7.9) Table 1. Characteristics of the studies included in the review (continued).
23 Prevalence of secondary prevention medication use in South America 2 Publication Study duration Country Study Design N Care Setting Diagnosis category Urban setting % women Age Socioeconomic Status Avezum, 2017 2003-2009 Argentina, Brazil, Chile, Colombia Cross-sectional 910 Primary Care, Community CHD Both 61.3 62.20 (11.60) Vianna, 2012 2008-2008 Brazil Cross-sectional 295 Primary Care, Community ACS Urban Birck, 2019 2008-2010 Brazil Cross-sectional 405 Primary Care, Community CHD Urban 36.5 61.6 (9.4) Education: 48.6, Income: 38.3 Stockins, 2011 2005-2006 Chile Cohort 233 Publi Hospital ACS 30.6 68.0 Aguiar, 2010 1999-2007 Brazil Cohort 377 Public Hospital ACS 37.9 62.3 (9.3) Carvalho, 2007 1992-2000 Brazil Retrospective cohort 381 Rehabilitation 19.4 Gambogi, 2009 2004-2006 Uruguay Cohort 900 Rehabilitation Both 25.3 57.9 (9.9), 61.3 (7.7) Education: 9.5, Employment: 44.6 Garlet, 2017 2015-2016 Brazil Cross-sectional 102 Rehabilitation CHD 31.4 61.7 (10.0), 64.5 (9.0) Lelys, 2019 2015-2017 Brazil Cross-sectional 115 Rehabilitation CHD 28.7 59.9(8.6); 57.2 (9.0) Employment: 40.0 Pantoni, 2014 2006-2008 Brazil Non-randomized intervention 28 Rehabilitation CABG Urban 32.1 56.0 Fuchs, 2009 2005-2006 Brazil Cross-sectional 39 Rehbilitation CHD Urban 10.3 63.7(95% CI 56.6-73.9) Castro, 2018 2018-NA Brazil Cohort 525 Secondary Hospital ACS Urban 39.8 61.6 (11.9) Trivi, 2018 2010-2011 Argentina Cohort 438 Secondary Hospital ACS 24.2 59.2 (7.9) Table 1. Characteristics of the studies included in the review (continued).
24 Chapter 2 Participants’ characteristics The most common diagnosis of the patients included was coronary heart disease (26 articles), followed by ACS (21 articles), PCI (9 articles), CABG (9 articles) and some articles included patients with more than one diagnosis (5). Most articles included a majority of male participants. The mean percentage of female participants was 32.0% (SD 11.4%). 12 articles provided information on the socioeconomic status (SES) of participants. Educational attainment was reported by 7 publications and the proportion of participants with highest educational attainment ranged from of 9.5% to 49.2%. The percentage of employed participants was reported by 5 articles and ranged from 33.5% to 45.0%; and the proportion of participants in the highest income category (reported in 6 articles) varied from 20.0% to 58.0%. Regarding the risk factors of the study populations, 54 articles reported the prevalence of hypertension (range 45.0-96.0%) and 42 articles provided prevalence values for dyslipidaemia (36.0-96.8%). The prevalence of diabetes was reported in 56 articles (range 7.7% to 100%). The prevalence of overweight was reported in 11 of the included studies (range 28.2% to 93.5%), Five articles reported the prevalence of obesity (range 15.0%- 33.7%); and 16 articles included mean or median BMI values, ranging from 26.1 to 29.0 kg/m2. Quality assessment The risk of bias varied by domain of the quality assessment tool: study population was the field in which more articles had a high risk of bias (13.7%), whereas most articles had low risk of bias in the fields of study design (79.5%) and participation rate (72.6%) (Figure 2). The results of the quality assessment of all included publications is displayed in Supplementary Figure 1, and of included and excluded publications in Supplementary File 3B. Supplementary file 3C details the reasons for exclusion of publications with a risk of bias score lower than 6.
25 Prevalence of secondary prevention medication use in South America 2 Figure 2. Risk of bias results. Prevalence of medication The prevalence of medication for each study as well as the pooled prevalence estimate per medication is displayed in Figures 3-5 and summarized in Table 2. The prevalence of beta-blockers was reported in 53 studies, with a pooled estimate of 73.4% (95%CI 66.8% – 79.1%) (Figure 3). 44 articles reported the prevalence of ACEI/ARB use, with a pooled estimate of 55.8% (95%CI 49.7% – 61.8%) (Figure 3). The overall prevalence of antiplatelet drugs (including aspirin, clopidogrel, and articles that didn’t specify the antiplatelet drug) was retrieved from 51 studies, and the pooled prevalence estimate was 84.6% (95%CI 79.6% – 88.5%) (Figure 4). The prevalence of aspirin specifically was retrieved from 44 studies and their pooled estimate was 85.1% (95%CI 79.7% – 89.3%) (Figure 4). The prevalence of statins was reported in 50 articles and the estimated pooled prevalence was 78.9% (95%CI 71.2% – 84.9%) (Figure 5). Total heterogeneity in the meta-analysis models high, ranging from 97.8% (ACEI/ARBs model) to 99.0% (antiplatelet model). No significant differences were observed in the prevalence of any medication classes between Brazil and other countries.
26 Chapter 2 Variable Number of studies Pooled prevalence Beta-blockers 53 73.4 (66.8- 79.1) ACE inhibitors 44 55.8 (49.7 – 61.8) Aspirin 44 85.1 (79.7 – 89.3) Aspirin, clopidogrel or antiplatelet drugs 51 84.6 (79.6 – 88.5) Statins 50 78.9 (71.2 – 84.9) Insulin 9 11.6 (7.0 – 18.8) Antihypertensives (without specification) 8 46.5 (33.7 – 59.8) Diuretics 8 30.1 (24.3 – 36.6) Calcium chanel blockers 6 34.0 (19.4- 52.5) Nitrates 6 36.7 (24.1 – 51.5) Antiplatelet (without specification) 14 75.1 (55.5 – 87.9) Clopidogrel 13 50.0 (22.9 – 78.1) Dual antiplatelet therapy 3 80.0 (55.3 – 92.8) Lipid-lowering drugs 2 34.4 (9,1 – 73.4) Fibrates 2 73.1 (69.5 – 76.5) Note: Pooled prevalence results are expressed in percentage and 95% confidence interval. Table 2. Summary of the meta-analysis results. Time trends The prevalence of beta-blockers, ACEI/ARBs and statins use significantly increased with time. The use of all antiplatelet drugs and aspirin in particular remained relatively stable over time and the association between medication use and year of the study was not significant (Fig 6). The changes in use for other classes of medications were not significant, and they are shown in Supplementary Figure 6. There were too few observations in the lipid-lowering drugs (without specification) and fibrates to analyse time-trends.
27 Prevalence of secondary prevention medication use in South America 2 Figure 3. Pooled prevalence of antihypertensive medication use.
28 Chapter 2 Figure 3.Pooled prevalence of antihypertensive medication use (continued).
29 Prevalence of secondary prevention medication use in South America 2 Figure 4. Pooled prevalence of antiplatelet medication use.
30 Chapter 2 Figure 4. Pooled prevalence of antiplatelet medication use.
31 Prevalence of secondary prevention medication use in South America 2 Figure 5. Pooled prevalence of statin use.
32 Chapter 2 The pooled prevalence estimates of medications and medication classes reported by fewer articles is displayed in supplementary figures 3-5 and summarized in Table 2. This includes antihypertensive drugs (without specification), diuretics, nitrates, antiplatelet drugs (without specification), calcium channel blockers, clopidogrel, dual antiplatelet therapy, lipid-lowering drugs (without specification), and fibrates. Figure 6. Time trends in medication use. Note: Each circle represents a study and the size of the circle is proportional to the number of participants in the study. Guideline compliance From the publications included, 19 articles reported whether the prevalence of medication use was adequate. Half of them reported that medication use was low (59,62,76–78) or insufficient compared to guideline recommendations (2,12,48,61,79). Other articles reported that cardioprotective Guideline compliance From the publications included, 19 articles reported whether the prevalence of medication use was adequate. Half of them reported that medication use was low (59,62,76–78) or insufficient compared to guideline recommendations (2,12,48,61,79). Other articles reported that cardioprotective medication use was adequate or high (32,60,66,67,73,75), or in line with guideline recommendations (38,65,80). Determinants of medication use Determinants reported in publications Variables independently associated with medication use included sex, age, socio-economic status, residency, prevalence of cardiovascular risk factors, diagnosis category of CHD
33 Prevalence of secondary prevention medication use in South America 2 patients and health care setting. It was a common finding that prevalence of cardioprotective medication use was lower in women (2,12,48,77), younger individuals (12,81). For example, male patients had an OR ranging from 1.29, (95%CI 1.11-1.49) to 1.54 (95%CI 1.06 – 2.24) for statin use compared to females (12,77); and patients aged 60 or older presented an OR ranging from 1.42 (95%CI,1.05-1.92) for the use of antiplatelet drugs (12) and 1.94 (1.07-3.50) for the use of cardioprotective medication in general (81). The presence of cardiovascular risk factors associated with higher medication use. The odds of medication use were higher for overweight (OR of ACEI/ARB use 2.56, 95%CI 1.74-3.77), obese (OR of ACEI/ARB use 2.96, 95%CI 2.00-4.38) and diabetic patients (OR of statin use 1.60, 95%CI 1.08-2.37) (12). Higher use of aspirin was identified among current (77) and former smokers (81), with OR of 1.83 (95%CI 1.35-2.50) and 1.41 (95%CI 1.03-1.93) respectively compared to non-smokers. High blood pressure was associated with higher use of betablockers and ACEI (OR 1.36, 95%CI 1.21-1.52, and 1.74, 95%CI 1.55-1.95 respectively), and high cholesterol with higher use of statins (OR 4.34, 95%CI 3.77-4.99) (77). A few articles identified the diagnosis category of CHD patients as determinant for medication use. Having a previous PCI was an independent determinant for higher use of antiplatelet drugs (OR 2.00, 95%CI 1.30-2.31) (2), and previous PCI or CABG were associated with higher use of statins (or 2.37, 95%CI 2.07-2.72) (77). One publication reported that patients who attended public centres (OR 1.99, 95%CI 1.54-2.59), or centres that are a combination of public and private (1.96, 95%CI 1.51-2.53) had higher odds of cardioprotective medication use (3) compared to those attending private centres. Lower SES (2,12,48,81) and living in rural areas (12) were also associated with lower medication use. In particular, participants from the wealthiest group had an OR of medication use of 2.54 (95%CI 1.08 – 5.95) for use of cardioprotective medication in general, to 5.94 (95%CI 2.80 – 12.6) for statin use compared to the least wealthy group (12,48); and urban dwellers had an OR of 1.41 (95%CI 1.04-1.92) for use of ACEI/ARB compared to participants from a rural location (12). Meta-regression results The health care setting, i.e. type of centre where the study had been conducted had a significant effect on medication prevalence for beta-blockers, statins, overall antiplatelet drugs and aspirin: the odds of medication use were lower in studies conducted in primary care and community settings compared to academic and tertiary centres. Further, the odds of overall antiplatelet drugs use were lower in public centres, and the odds of aspirin use were lower in cardiac rehabilitation settings, compared to academic and tertiary centres (Table 3).The use of ACEI/ARBs was not significantly associated with any of the covariates in the meta-regression models. The remaining medications or medication classes presented too few observations and thus meta-regression models could not be fit. The percentage of women included in the study and the previous CHD diagnosis category of the patient were not significantly associated with the use of any medication class. The
34 Chapter 2 number of publications reporting on age, SES and cardiovascular risk factors in a comparable format was low and thus they couldn’t be included in the meta-regression. Variable Beta-blockers ACEI-ARB Statin Antiplatlet drugs (overall) Aspirin Intercept 2.56 (0.89-7.37)* 0.84 (0.36-1.94) 3.55 (1.04-12.17) 6.57 (2.60-16.57)* 6.06 (2.18-16.87)* Sex 1.01 (0.98-1.04) 1.01 (0.98-1.04) 1.01 (0.97-1.04) 1.00 (0.97-1.03) 1.00 (0.97-1.03) Setting Primary care / community 0.18 (0.04-0.96)* 0.11 (0.02-0.62)* 0.12 (0.03-0.40)* 0.19 (0.04-0.96) § Public centre 0.35 (0.07-1.69) 0.28 (0.09-0.86)* Cardiac rehabilitation 0.92 (0.30-2.78) 1.87 (0.53-6.61) 0.38 (0.14 – 1.04) 0.07 (0.02-0.33) * Other 0.71 (0.27-1.88) 0.67 (0.27-1.64) 0.73 (0.37-1.44) 1.03 (0.36-2.92) Diagnosis ACS 1.41 (0.78-2.54) 1.65 (0.90-3.03) 1.73 (0.89-3.37) PCI 0.70 (0.21-2.28) 0.92 (0.30 – 2.82) 0.94 (0.29-3.08) CABG 1.21 (0.43-3.37) 0.85 (0.27 – 2.65) CABG, PCI 0.58 (0.11-2.97) 1.26 (0.38-4.21) 1.31 (0.37-4.64) Table 3. Results of the meta-regression models showing factors independently associated with medication use. Note: Results are expressed in odds ratios and 95% confidence intervals. Sex was treated as a numerical variable (percentage of women included in the study). The reference category for setting was “AcademicTertiary Hospital”, and the reference category for diagnosis was “coronary heart disease”. Abbreviations: acute coronary syndrome (ACS), coronary artery bypass graft (CABG), CHD, percutaneous coronary intervention (PCI percutaneous coronary intervention). §p=0.05. DISCUSSION Summary of main findings The current systematic review shows large variation in the use of cardioprotective medication among CHD patients, ranging from 55.8% for the use of ACEI/ARB drugs to 85.0% for the use of aspirin. A similar number of studies reported suboptimal and adequate guideline compliance. Time-trend analysis for the period 1993 to 2017, showed an increase in the use cardioprotective medication with the exception of the use of all antiplatelet drugs and aspirin. Use of beta-blockers, statins, overall antiplatelet drugs and aspirin in community settings was lower compared to academic and tertiary centres. The use of antiplatelet drugs
35 Prevalence of secondary prevention medication use in South America 2 in public centres and of aspirin in rehabilitation centres was also lower compared with tertiary centres. Prevalence of medication The prevalence of cardioprotective medication that we observe in South America varies per medication class and shows a general underuse of medications. We observe differences in the prevalence of medication use reported in Europe and North America (8,9,82). When comparing prevalence estimates found in this review, we observed that the prevalence of antiplatelet drugs and beta-blockers was higher than the estimates found for the PURE study (8) (55.4% of antiplatelet use and 45.4% of beta-blocker use in Europe and Canada) and a systematic review by Naderi et al (9) (65% of antiplatelet use and 62% of beta-blocker use). The prevalence of ACEI/ARBs we observed was higher than reported in the PURE Study (46.8% in Europe and North America), but lower than in the review by Naderi et al (70%) (9). Prevalence estimates from the international EUROASPIRE IV (82) registry were higher than the ones observed in our review for all medication classes (93.8% for antiplatelets, 82.6% for beta-blockers,58.9% for ACE inhibitors and 27% for insulin) except oral hypoglycaemics (oral sulphonylurea 24.9%) and lipid lowering drugs (fibrates 1.8%). The prevalence of statin use we observed was higher than reported in the PURE study (56.7% in Europe and North America), similar to the prevalence estimate described in a systematic review (76%) (9) and lower than the estimate from EUROASPIRE IV (85%) (82). However, direct comparison with these studies is challenging because they were conducted in different contexts, regions and time periods and other definitions of medication use. The PURE study was conducted entirely in community settings in high-, low- and middle-income countries and regions. The review by Naderi et al (9) included studies from high income countries in Europe, North America and Australia, and their definition of medication use was limited to prescription refills. EUROASPIRE IV included a majority of secondary and tertiary level centers and was conducted from 2012-2013, while the present review also included research from community settings and studies that started since 1993 (82). Guideline compliance Most publication included in this review reported that the prevalence of medication use is suboptimal, while others articles find it to be in compliance with guidelines. Despite some publications considering treatment rates high or adequate, we still find that a notable proportion of the patients do not receive guideline-recommended medications: for example, one third of CHD patients were not receiving beta-blockers and almost one fourth were not receiving statins (67), although these medications are recommended by guidelines. This low use of antihypertensives may be explained by individuals having adequate blood pressure levels or contraindications, despite guidelines recommending these drugs for all CHD patients. Statins, however, are generally well-tolerated drugs and they are recommended to all CHD patients regardless of cholesterol levels. Therefore, the fact that a substantial proportion of patients does not use them may respond to factors other than possible contraindications. Challenges to adhere to guidelines identified by clinicians include difficulties to change usual
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