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Heart failure care in low- and middle-income countries: a systematic review and meta-analysis.
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PMID:  25117081     Owner:  NLM     Status:  In-Data-Review    
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BACKGROUND: Heart failure places a significant burden on patients and health systems in high-income countries. However, information about its burden in low- and middle-income countries (LMICs) is scant. We thus set out to review both published and unpublished information on the presentation, causes, management, and outcomes of heart failure in LMICs.
METHODS AND FINDINGS: Medline, Embase, Global Health Database, and World Health Organization regional databases were searched for studies from LMICs published between 1 January 1995 and 30 March 2014. Additional unpublished data were requested from investigators and international heart failure experts. We identified 42 studies that provided relevant information on acute hospital care (25 LMICs; 232,550 patients) and 11 studies on the management of chronic heart failure in primary care or outpatient settings (14 LMICs; 5,358 patients). The mean age of patients studied ranged from 42 y in Cameroon and Ghana to 75 y in Argentina, and mean age in studies largely correlated with the human development index of the country in which they were conducted (r = 0.71, p<0.001). Overall, ischaemic heart disease was the main reported cause of heart failure in all regions except Africa and the Americas, where hypertension was predominant. Taking both those managed acutely in hospital and those in non-acute outpatient or community settings together, 57% (95% confidence interval [CI]: 49%-64%) of patients were treated with angiotensin-converting enzyme inhibitors, 34% (95% CI: 28%-41%) with beta-blockers, and 32% (95% CI: 25%-39%) with mineralocorticoid receptor antagonists. Mean inpatient stay was 10 d, ranging from 3 d in India to 23 d in China. Acute heart failure accounted for 2.2% (range: 0.3%-7.7%) of total hospital admissions, and mean in-hospital mortality was 8% (95% CI: 6%-10%). There was substantial variation between studies (p<0.001 across all variables), and most data were from urban tertiary referral centres. Only one population-based study assessing incidence and/or prevalence of heart failure was identified.
CONCLUSIONS: The presentation, underlying causes, management, and outcomes of heart failure vary substantially across LMICs. On average, the use of evidence-based medications tends to be suboptimal. Better strategies for heart failure surveillance and management in LMICs are needed. Please see later in the article for the Editors' Summary.
Authors:
Thomas Callender; Mark Woodward; Gregory Roth; Farshad Farzadfar; Jean-Christophe Lemarie; Stéphanie Gicquel; John Atherton; Shadi Rahimzadeh; Mehdi Ghaziani; Maaz Shaikh; Derrick Bennett; Anushka Patel; Carolyn S P Lam; Karen Sliwa; Antonio Barretto; Bambang Budi Siswanto; Alejandro Diaz; Daniel Herpin; Henry Krum; Thomas Eliasz; Anna Forbes; Alastair Kiszely; Rajit Khosla; Tatjana Petrinic; Devarsetty Praveen; Roohi Shrivastava; Du Xin; Stephen MacMahon; John McMurray; Kazem Rahimi
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Type:  Journal Article     Date:  2014-08-12
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Title:  PLoS medicine     Volume:  11     ISSN:  1549-1676     ISO Abbreviation:  PLoS Med.     Publication Date:  2014 Aug 
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Created Date:  2014-08-13     Completed Date:  -     Revised Date:  -    
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Nlm Unique ID:  101231360     Medline TA:  PLoS Med     Country:  United States    
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Languages:  eng     Pagination:  e1001699     Citation Subset:  IM    
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Journal ID (nlm-ta): PLoS Med
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ISSN: 1549-1676
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Copyright: 2014 Callender et al
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Received Day: 19 Month: 12 Year: 2013
Accepted Day: 24 Month: 6 Year: 2014
collection publication date: Month: 8 Year: 2014
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DOI: 10.1371/journal.pmed.1001699

Heart Failure Care in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis Alternate Title:Heart Failure in Low- and Middle-Income Countries
Thomas Callender1
Mark Woodward12
Gregory Roth3
Farshad Farzadfar45
Jean-Christophe Lemarie6
Stéphanie Gicquel6
John Atherton7
Shadi Rahimzadeh48
Mehdi Ghaziani45
Maaz Shaikh19
Derrick Bennett10
Anushka Patel2
Carolyn S. P. Lam11
Karen Sliwa12
Antonio Barretto13
Bambang Budi Siswanto14
Alejandro Diaz15
Daniel Herpin16
Henry Krum17
Thomas Eliasz1
Anna Forbes1
Alastair Kiszely1
Rajit Khosla1
Tatjana Petrinic18
Devarsetty Praveen29
Roohi Shrivastava1
Du Xin19
Stephen MacMahon12
John McMurray20
Kazem Rahimi1*
Peter Byassedit1 Role: Academic Editor
1The George Institute for Global Health, University of Oxford, Oxford, United Kingdom
2The George Institute for Global Health, University of Sydney, Sydney, Australia
3Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
4Non-Communicable Diseases Research Centre, Tehran University of Medical Sciences, Tehran, Iran
5Endocrinology and Metabolism Research Centre, Tehran University of Medical Sciences, Tehran, Iran
6Effi-Stat, Paris, France
7Department of Cardiology, Royal Brisbane and Women's Children Hospital and University of Queensland School of Medicine, Brisbane, Australia
8Department of Epidemiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
9The George Institute for Global Health, Hyderabad, India
10Clinical Trials Service Unit, University of Oxford, Oxford, United Kingdom
11National University of Singapore, Singapore
12Hatter Institute for Cardiovascular Research in Africa, University of Cape Town, Cape Town, South Africa
13Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
14National Cardiovascular Centre University Indonesia, Jakarta, Indonesia
15Universidad Nacional del Centro de la Provincia de Buenos Aires, Buenos Aires, Argentina
16Centre Hospitalier Universitaire de Poitiers, Poitiers Cedex, France
17Centre of Cardiovascular Research & Education in Therapeutics, Monash University, Melbourne, Australia
18Bodleian Healthcare Libraries, University of Oxford, Oxford, United Kingdom
19The George Institute for Global Health, Peking University, Beijing, China
20University of Glasgow, Glasgow, United Kingdom
Umeå Centre for Global Health Research, Umeå University, Sweden
Correspondence: * E-mail: kazem.rahimi@georgeinstitute.ox.ac.uk
[conflict] CL is funded by a Clinician Scientist Award from the National Medical Research Council of Singapore; receives research grants from Boston scientific, Medtronic, and Vifor Pharma; and serves as a consultant for Bayer and Novartis. JML is employed by the contract research organization Effi-Stat, which receives funding from pharmaceutical and biotechnology companies. In 2009 and 2010 Effi-Stat received financial support from Sanofi-Aventis for providing statistical analysis and programming for the I-Prefer study included in this review (reference [70]). SG is employed by the contract research organization Effi-Stat, which receives research funding from pharmaceutical and biotechnology companies. AP is a member of the Editorial Board of PLOS Medicine.
Contributed by footnote: Analyzed the data: TC KR MW. Wrote the first draft of the manuscript: TC KR. Contributed to the writing of the manuscript: TC KR MW GR JM FF. ICMJE criteria for authorship read and met: TC MW GR FF JM KR JCL SG JA SR MG SM MS DB AP CSPL KS AB BBS AD DH HK TE AF AK RK TP DP RS DX. Agree with manuscript results and conclusions: TC MW GR FF JM KR JCL SG JA SR MG SM MS DB AP CSPL KS AB BBS AD DH HK TE AF AK RK TP DP RS DX. Designed the study: KR DB. Provided input on study design: DX AP SM. Designed the search strategy, and contributed to abstract reviews and data extraction plans: TE AF AK RK TP DP RS. Completed data extraction and coordinated the collection of unpublished data: KR TC. Provided input on writing of the manuscript and analyzing of the data: MW GR FF JM. Contributed significantly to reviewing the manuscript: JA HK KS DB AP CSPL. Contributed data: JCL SG SR MG FF MS JA BBS AB AD DH. TC had full access to all the data in the study and he takes responsibility for the integrity of the data and the accuracy of the data analysis.

Introduction

In high-income countries (HICs), heart failure is a well-recognized public health problem representing a significant burden for patients and healthcare systems [1],[2]. For example, in the UK and US, heart failure is one of the leading causes of hospitalisation, and despite recent advances, outcomes remain poor [3][6]. Of those hospitalised for heart failure in the UK, about 10% will die during admission [6]. In the US, between 20% and 27% of those who survive to discharge will be re-admitted within 30 d [7], whilst 5-y mortality rates range between 40% and 65% amongst the US, UK, Netherlands, and Sweden [2][4],[8],[9]. The costs associated with heart failure care are also substantial. In many HICs, heart failure typically consumes 1%–2% of healthcare resources [2], mainly because of repeated admissions to hospitals and prolonged inpatient stays.

With demographic changes and the epidemiological transition to non-communicable diseases [10],[11], heart failure is expected to become a major public health issue in low- and middle-income countries (LMICs). Yet systematic evidence for its current burden to patients and health services is limited [1],[2],[12]. In fact, the last review of the burden of heart failure in LMICs, conducted over ten years ago, found no population studies and concluded that published data on heart failure epidemiology were almost entirely absent from most populations across the world [12]. As a result, many of our assumptions regarding the current burden of this condition worldwide are based on extrapolations from studies conducted in HICs, which may not be appropriate [1],[2].

Therefore, we sought to conduct a systematic review of both published and unpublished data regarding the patterns of heart failure presentation, management, and outcomes in LMICs.


Methods

This systematic review was designed and undertaken according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [13]. A study protocol describing the methodology has been published previously [14]. In brief, we searched Medline, Embase, Global Health Database, and WHO regional databases for articles published between 1 January 1995 and 30 March 2014 with the subject terms “heart failure” or “cardiomyopathies” or any related terms AND “incidence”, “prevalence”, “cause*”, “etiology”, “aetiology”, “epidemiolog*”, “burden”, “management”, “treatment”, “prevent*”, “population based”, “community”, “trends”, “survey”, “surveillance”, “mortality”, “morbidity”, “fatalit*”, or “attack rate”. Relevant studies from LMICs on the epidemiology, diagnosis, management, and outcomes of heart failure were included. There were no language restrictions. We also scrutinised the reference lists of study reports and review articles, and inquired among our collaborators and international heart failure experts about any additional databases or studies of which they may be aware. We further searched the Institute for Health Metrics and Evaluation's Global Health Data Exchange as well as the websites of regional and country-specific societies of cardiology to identify further datasets.

Figure 1 summarises the retrieval and selection process for studies and relevant databases. After removing duplicate reports, two reviewers independently screened all titles and abstracts for their potential eligibility and extracted data using a pre-designed form. Studies were eligible for inclusion if they reported on heart failure patients from LMICs as defined by the World Bank [15]. Studies must have reported on at least 100 cases and contained relevant information on demographic characteristics, prevalence, case fatality, underlying aetiology, or management of patients with heart failure. Studies confined to subgroups of patients with heart failure (for example, those that included only dilated cardiomyopathy or heart failure as a complication of acute myocardial infarction) were excluded, as were studies that clearly did not include a representative sample of patients from the setting chosen (for example, studies that selected people referred to an echocardiography department, or studies that excluded adult populations) [14]. Investigators of multinational studies that had not reported findings by country were contacted for country-specific data.

Quality Assessment

In order to capture a comprehensive overview of heart failure in LMICs, a wide range of studies, each with differing objectives and designs, were included. Studies meeting the minimum quality requirement, as specified below, for inclusion were analysed for both methodological limitations and reporting quality, using items from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines [16] (Tables 16). Specifically, the sample size of each study, the location and type of healthcare facility, diagnostic methods used, and patient selection criteria were documented. In addition, we assessed each study's specific methodological strengths and weaknesses as well as likely external validity.

Statistical Analysis

Study-specific data on percentages are presented as forest plots with exact binomial 95% confidence intervals (CIs). These percentages were pooled, by World Health Organization region (Table 7) and across regions, using the random effects method of DerSimonian and Laird [17]. Heterogeneity between studies was quantified by the I2 statistic and tested using Cochran's Q test. Means were rarely reported with an estimate of variability, and, consequently, we weighted individual means by study size in pooled analyses, and present the pooled mean and the range of means.

Patients presenting acutely to hospitals may differ in many respects from those that are seen in clinics for chronic management. When pooling the data we therefore indicate the setting of each study in all forest plots. Studies from community primary care or outpatient clinics were designated as non-acute, and studies from inpatient populations, acute. Studies reporting both inpatient and outpatient data were included in the non-acute category. Additional subgroup analyses were performed by level of country income and by study time period. For income level analyses, studies were divided into low-income, low-middle-income, and upper-middle-income groups according to World Bank [15] country classification at the final year of the recruitment period of the study. The relationship between a study's mean age at admission for heart failure and the human development index (HDI) [18] for the country involved was estimated with linear regression analysis; the HDI was taken for the closest year to the final year of patient recruitment for the studies representing each country. The HDI is a composite measure of development produced by the United Nations Development Programme that incorporates life expectancy, education, and gross national income per capita [18]. Random effects meta-regression was performed to investigate study year as an explanation for the between-study heterogeneity in causes of heart failure, management, and in-hospital mortality. Corresponding bubble plots were drawn, with the size of each bubble inversely proportional to the estimated variance in the respective study.

Statistical analyses were done using R version 3.0.2 and Stata version 11.2.


Results
Geographic Distribution and Study Description

Overall, 49 published studies [19][67] and four unpublished datasets ([68][70]; S. Rahimzadeh, F. Farzadfar F, M. Ghaziani, unpublished data) were included; their geographical distribution is presented in Figure 2, and key study characteristics, divided by WHO region, are summarised in Tables 16. We obtained unpublished country datasets from the Acute Decompensated Heart Failure Registry (ADHERE)–International [68] regarding Malaysia and the Philippines, as well as the Identification of Patients with Heart Failure and Preserved Systolic Function (I PREFER) registry [70] including Iran, Lebanon, Egypt, Tunisia, Algeria, Chile, Colombia, and Mexico. Additional unpublished data were contributed from Iran (S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data) and India [69].

Most studies were based in a single hospital, although 21 datasets documented multi-centre studies in Algeria [70], Argentina [21],[43],[44], Brazil [40],[45], Chile [41],[70], Colombia [70], China [55],[57],[62], Egypt [70], Indonesia [20], India [69], Iran (S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data; [70]), Lebanon [70], Thailand [52], Malaysia [68], Mexico [70], Philippines [68], Romania [50], Tunisia [70], Turkey [49],[63],[64], and a further nine countries in sub-Saharan Africa [35]. Four studies involved both inpatient and outpatient data [22],[24],[26],[36], six studies referred solely to patients seen at outpatient clinics [27],[39],[61],[66],[67],[70], three studies described heart failure in primary care settings [62][64], and the remainder reported solely on inpatient populations. One study was a population-based assessment of the prevalence of heart failure in Turkey [63].

Case Identification and Ascertainment

The studies together included 237,908 episodes of heart failure hospitalisation. The median number of cases across all studies was 386 (range: 100–194,098). Diagnosis of heart failure was established according to the Framingham criteria [71] in 12 studies [21],[22],[24],[28][31],[42],[48],[55],[62],[70]. European Society of Cardiology guidelines were used in eight studies [25][27],[41],[50],[54],[60],[61], the Boston criteria [72] in three studies [39],[40],[47], and the American Heart Association guidelines in two studies [49],[53], and the diagnosis was left to the investigator's or examining physician's discretion in 26 studies ([19],[20],[23],[32][38],[43][46],[51],[52],[56][58],[64],[65],[67][69]; S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data). One study diagnosed all cases of heart failure solely using echocardiography [59]. Information on the use of additional investigative tools, including echocardiography, chest radiography, and electrocardiography, was provided in 28 studies [19][21],[24][26],[28],[31],[35],[39],[41][43],[46],[48][50],[51],[54],[56],[57],[59],[61],[63],[64],[66],[70],[73]. Of these, 14 studies performed echocardiography on all patients [19],[24][26],[28],[35],[46],[48],[53],[54],[59],[61],[63],[66]. The mean left ventricular ejection fraction (LVEF) was documented in 18 studies, reporting data from Algeria [70], Egypt [70], Tunisia [70], Cameroon [24], Ethiopia [35], Sudan [35], Mozambique [35], Kenya [35], Uganda [35], Senegal [35], South Africa [25], Nigeria [26],[28], Brazil [19],[39],[42],[46],[66], Chile [41],[70], Colombia [70], Mexico [70], Romania [50], Serbia [61], Turkey [49], Iran [70], Lebanon [70], Indonesia [20], Thailand [52], and China [53]. Across all studies, mean LVEF was 40% (range: 27%–57%) (Table 8). Hospitalised patients had a mean LVEF of 38% (27%–57%), with a corresponding figure of 48% (29%–55%) in non-acute settings.

Demographic Characteristics

The demographic characteristics of patients and outcomes by region are shown in Table 8. The corresponding data by country are shown in Table 9. Men made up 58% (95% CI: 54%–62%) of study participants (Figure 3). The mean age of patients for each region ranged from just over 52 y (range: 42–64) in Africa to 70 y (range: 53–77) in the Americas, and when combined across all regions was 63 y (range: 42–77). The mean age of patients on admission rose with the country income level. In low-income countries, the corresponding figure was 50 y (range: 42–58), rising to 60 y (range: 50–74) in low-middle-income countries, and reaching 70 y (range: 54–77) in upper-middle-income countries. Mean age also correlated with the HDI across countries (r = 0.71, p<0.001) (Figure 4).

Causes of Heart Failure

Although most studies made a clear distinction between aetiologies and co-morbidities, the categories reported were highly variable, and multiple causes were often attributed to individual cases of heart failure. Across all LMICs, non-communicable diseases, and in particular ischaemic heart disease (IHD) and hypertension, are the leading causes of heart failure (Table 10). However, there is heterogeneity between the regions. IHD is the most commonly reported cause of heart failure in all regions except Africa and the Americas (Figures 5 and 6). In the Americas hypertension and IHD are responsible for a similar percentage of documented cases, at 31% (95% CI: 19%–43%, I2 99%, p for heterogeneity <0.001) and 33% (95% CI: 27%–38%, I2 96%, p<0.001), respectively. In Africa, 8% (95% CI: 5%–11%, I2 98%, p<0.001) of heart failure is due to IHD, with hypertension the dominant cause, responsible for 46% (95% CI: 36%–55%, I2 98%, p<0.001) of cases. Cardiomyopathies cause 24% (95% CI: 20%–29%, I2 99%, p<0.001) of heart failure cases across LMICs taken together (Figure 7). Idiopathic, hypertrophic, and restrictive cardiomyopathies are reported across all countries; however, other specific types of cardiomyopathies showed substantial regional variation. Peri-partum and HIV-associated cardiomyopathies were reported only in Africa. By contrast, Chagas cardiomyopathy remains a Latin American phenomenon [21],[43]. Valvular heart disease is responsible for 18% (95% CI: 15%–22%, I2 98%, p<0.001) of cases of heart failure across LMICs (Figure 8).

Management of Heart Failure

Amongst all studies, the management of heart failure varies considerably between regions and within regions, as well as between studies from the same country (Table 11). The most commonly prescribed treatments are loop and/or thiazide diuretics, prescribed for 69% (95% CI: 60%–78%, I2 100%, p<0.001) of individuals in LMICs worldwide (Figure 9). Angiotensin-converting enzyme inhibitors (ACEIs) are used in 57% (95% CI: 49%–64%, I2 100%, p<0.001) of cases, beta-blockers in 34% (95% CI: 28%–41%, I2 100%, p<0.001), and mineralocorticoid receptor antagonists in 32% (95% CI: 25%–39%, I2 100%, p<0.001) (Figures 1012).

Outcomes

Across LMICs, patients admitted with heart failure remained in hospital for a mean of 10 d (Table 8). The mean hospital stay ranged from 3 d in India to 23 d amongst studies from China. Wide differences were observed amongst Argentinian and Brazilian studies. In Argentina, length of stay varied between studies from 5 d to 25 d, with an overall mean of 7 d. In Brazil, the range was between 9 and 25 d, with an overall mean of 10 d (see Table 9 for individual study data).

In-hospital mortality was 8% (95% CI: 6%–10%, I2 99%, p<0.001) (Figure 13) across the 23 studies that reported this measure ([20],[21],[23],[29],[31],[33][35],[40],[41],[43][46],[48],[50],[52],[56][58],[68][69]; S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data), with no significant association with the country-level length of stay. Four studies reported longer-term outcome data, showing comparable mortality rates post-discharge: THESUS-HF, a multi-centre study of heart failure across nine countries of sub-Saharan Africa, found that mortality from heart failure was 4.2% in hospital and 17.8% at 6 mo after hospital discharge [35]. In Brazil, Barretto and colleagues reported a mortality rate of 8.8% in hospital and 25.8% at 1 y [19], whilst in Pakistan, after almost a year of follow-up, a similar mortality rate of 27.5% was recorded [47]. Of the Brazilian cohort studied by de Campos Lopes and colleagues, 44% were alive at 21 mo of follow-up [42].

Data relating to heart failure as a proportion of total hospital admissions were available for five countries. Across these countries, heart failure accounted for 2.2% (range: 0.3%–7.7%) of total admissions. Brazil was the only LMIC with nationwide registry data compiled for all patients with heart failure treated by its public health system [74]. Here, heart failure was responsible for 2.2% of total hospitalisations across the country [74]. In India, heart failure accounted for only 0.37% of cases from a sample of 1,551,410 hospitalisations, as derived from billing data in Andhra Pradesh [69]. Out of a representative sample of 38,926 hospital admissions in Iran, 0.3% were identified as having heart failure as the primary cause of admission (S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data). By contrast, 5.8% of total hospital admissions in Cameroon were due to heart failure [24],[29], and 7.7% in Argentina [23].

In sub-Saharan Africa, the total number of cardiovascular admissions was reported, rather than total hospital admissions. In Nigeria, heart failure accounted for 31% of cardiovascular cases presenting to hospital [27], with corresponding figures of 38% in Senegal [38] and 47% in Soweto, South Africa [75].

Population-level data regarding the prevalence of heart failure were available in only one study, from Turkey [63]. Here an absolute prevalence of 2.9% for heart failure was found across the sample [63].

Effect of Time on Heterogeneity of Outcomes

Meta-regression was performed to investigate the potential effect of the time period in which each study was undertaken on between-study heterogeneity in the causes, management, and outcomes of heart failure.

A statistically significant effect was observed between the study time period and hypertension as a cause of heart failure, which rose by 2.5% per year (95% CI: 1.4%–3.6%, p<0.001) between 1990 and the late 2000s (Figure 14). There was no evidence to suggest that study time period had a significant effect on the other main causes of heart failure (IHD: 0.05%, 95% CI: −1.4% to 1.5%, p<0.95; cardiomyopathies: 0.65%, 95% CI: −0.3% to 1.6%, p<0.19; valvular heart disease: −0.04%, 95% CI: −0.7% to 0.6%, p<0.89) (Figures 1517).

The reported utilization rates for medical treatments of heart failure did not differ significantly over time, with the exception of beta-blockers, which showed an increase of 2.8% per year (95% CI: 1.5%–4.1%, p<0.001) (Figure 18). Corresponding figures were −0.4% per year (95% CI: −1.8% to 0.98%, p = 0.56) for ACEI use and 0.67% (95% CI: −0.9% to 2.2%, p = 0.38) for mineralocorticoid receptor antagonist use, with loop and/or thiazide diuretic use changing by −0.49% per year (95% CI: −1.9% to 0.9%, p = 0.49) (Figures 1921).

There was also some evidence to suggest in-hospital mortality rate declined by 0.28% per year between 1990 and 2010 (95% CI: −0.54% to −0.012%, p = 0.042) (Figure 22).


Discussion

Our study presents, to our knowledge, the most comprehensive review to date and the first pooled analysis of the burden of heart failure in LMICs worldwide, collating data on over 230,000 episodes from 31 countries, with representation from all world regions. We found that heart failure is already a major burden to populations and health services in LMICs, where it makes up an average of 2.2% of hospital admissions, affecting more men than women. Reflecting the broad range of countries included and their differing levels of socio-economic development, there are wide variations in patient characteristics and the causes of heart failure and its management. Nonetheless, noticeable similarities can be discerned both between the included LMICs themselves and between these LMICs and HICs.

Across all LMICs from which data were available, the mean age of patients was 63 y, which is over a decade younger than in studies from HICs [76],[77]. The observed differences in age between the countries correlated strongly with the differences in HDI across them. Alongside this is the graded rise in the mean age of patients from represented low-income, low-middle-income, and upper-middle-income countries, from 50 y in the former to 60 y and 70 y, respectively. Thus, the age of presentation in upper-middle-income countries comes close to that in HICs (70 y in the EuroHeart Failure Survey II across 30 countries in Europe [76] and 72 y in ADHERE in the US [77]).

Substantial inter-regional variation is present in the causes ascribed to individual cases of heart failure. Heart failure is a syndrome made up of a constellation of signs and symptoms, with additional features present on further investigation. Given that a number of its aetiological underpinnings are often potential co-morbidities, disentangling one from the other is fraught with challenges, particularly in low-resource environments without recourse to a broad range of investigative tools [31]. Although 80% of studies from the Americas, Western Pacific, and Europe reporting aetiologies for heart failure documented the use of additional investigative tools, only 50% of studies from Africa did so. Nevertheless, our results are broadly consistent with the patterns of risk factors reported by Khatibzadeh and colleagues in their recent review of the worldwide risk factors for heart failure [78], as well as those of the Global Burden of Disease Study [10]. It is of note that preventable non-communicable diseases, in particular IHD and hypertension, are responsible for the large majority of cases worldwide.

Current guidelines worldwide stress the importance of ACEIs, beta-blockers, and mineralocorticoid receptor antagonists in the management of heart failure with reduced LVEF, with loop/thiazide diuretics given for symptom relief. Across the 29 studies from which management data were available, few studies reported the LVEF of patients, and fewer still separated data by LVEF. Overall mean LVEF was 40%: 38% amongst inpatients and 48% amongst those in non-acute settings. Consequently, it is not possible to make strong conclusions about the adherence of practice to evidence-based practices worldwide, but it is evident that management diverges considerably between regions and remains suboptimal on average. Data from the EuroHeart Failure Survey II of 30 high-income European countries also demonstrated poor medical management [76]. In this study, the mean LVEF of patients was 38%, and just over one-third of patients had a LVEF>45% [76]. Here, 71% of individuals were prescribed ACEIs, 48% a mineralocorticoid receptor antagonist, and 61% a beta-blocker at discharge [76]. The corresponding figures across our dataset are 57%, 32%, and 34%, respectively.

Across represented LMICs, patients admitted with heart failure had a poorer immediate prognosis than those in many HICs. However, as is the case for HICs, the estimates from LMICs varied substantially, although we found the difference between the two outlying regions in terms of prognosis, the Americas and South East Asia, was not statistically significant (p = 0.27). On average, the in-hospital mortality rate was 8.3% in LMICs, compared to 6.7% in the EuroHeart Failure II Survey [76] and 4% in ADHERE in the US [77]. Such differences, and the wide heterogeneity both within LMICs and between LMICs and HICs, may be due to different thresholds for hospitalisation or differences in patient characteristics, treatment strategies, or hospital characteristics. Reports of outcomes after hospital discharge were available from some studies, and these were more comparable to estimates from HICs [4],[6],[19],[42],[47].

Remarkable regional variation exists in the incidence of heart failure admissions to hospital. Of particular note is the low rate of reported admissions for heart failure in India and Iran. Unpublished data from India, based on the hospital billing codes assigned to patients from a sample of just under 1,551,410 admissions, showed an incidence of 0.37% [69]. Similarly, 0.3% of all hospital admissions were attributed to heart failure in a registry of over 80,000 hospitalisations across a number of hospitals in Iran (S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data). These figures are an order of magnitude smaller than what is reported in HICs. There are several possible reasons for this observation. For example, it may be that in these countries, hospitals are still largely used for procedure-related activities, as opposed to pure medical management. In such a setting, treatment of medical conditions, such as heart failure, is much more likely to take place in the outpatient setting, for which data from India and Iran are lacking. Overall, the population-level incidence and prevalence of heart failure, despite its significance and dominance amongst cardiovascular diseases presenting to hospitals worldwide, remains largely unknown. Similarly, few data regarding the direct and indirect costs of heart failure are available in LMICs, information that is vital in understanding and measuring the value of different health service configurations and novel interventions.

This review collates data over a time period of almost 20 y, which may be one explanation for the degree of heterogeneity in results between studies. However, when study period was analysed using meta-regression against the causes, management, and outcomes of heart failure, only three statistically significant effects were found. These included a rising percentage of patients in whom hypertension was reported as a contributing cause of heart failure, an increasing trend in the reported prescription of beta-blockers over time, and a substantial decline in in-hospital death rates (see Figures 14, 18, and 22). Although these associations are plausible and—in case of beta-blocker use and mortality rates—encouraging, they should be interpreted cautiously because of the potential for confounding.

Limitations

The data included are derived from a heterogeneous group of studies that set out with differing research goals. Variation in the methodologies used, particularly in methods of standardising the diagnosis and assessment of heart failure, may impact on some of the findings. These factors likely explain the high estimates of between-study variation that we found. Such variation may lead to underestimation of the true prevalence of heart failure, as well as inaccuracies in the causes ascribed to cases of heart failure. Our study includes individuals from three groups: those with their first presentation with acute heart failure, those with acute decompensation of chronic heart failure, and those with stable chronic heart failure seen in the outpatient clinic setting. Differences between healthcare systems may mean that the characteristics of patients seen in various settings may differ between countries, whilst adherence to gold-standard management may be more common amongst those with stable chronic heart failure seen in outpatient settings staffed by cardiologists than amongst those with acute heart failure treated in hospitals staffed by general internal physicians. In analysing these patients we have focussed on the evidence-based medical management methods common to all three groups. Combining data from 1995 to 2014, this study summarises management techniques over an almost 20-y period, an approach that may underestimate adherence to current management standards. However, when evaluated with meta-regression, the heterogeneity in a management variable was rarely found to be explained by changes over time. Another limitation of our study is that our data are derived from studies conducted for the most part in urban tertiary referral centres, which may not reflect the broader picture of heart failure in other hospitals and the community. Finally, despite the large number of studies included, information from some regions and for some outcomes was limited. In countries where few data are available, these results may not be truly reflective of the population and should therefore be interpreted as only a guide to the true prevalence, causes, and management of heart failure.

Conclusion

This review shows that heart failure places a considerable burden on health systems in LMICs, and affects a wide demographic profile of patients in these countries. Non-communicable diseases dominate the causes of heart failure across LMICs, although infectious valvular diseases and cardiomyopathies continue to impose a significant burden. Together, this suggests a double burden of communicable and non-communicable diseases for countries in the midst of epidemiological transition. In addition, we have identified high in-hospital mortality and wide variation and significant suboptimal use of pharmacological therapies. Further population-level studies, with clear case and outcome definitions, are needed for a more accurate assessment of heart failure in LMICs.


Supporting Information Protocol S1

Study protocol: systematic review of the burden of heart failure in low- and middle-income countries.

(PDF)


Checklist S1

PRISMA 2009 checklist.

(DOC)


Click here for additional data file (pmed.1001699.s002.doc)


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Abbreviations
ACEI angiotensin-converting enzyme inhibitor
ADHERE Acute Decompensated Heart Failure Registry
CI confidence interval
HDI human development index
HICs high-income countries
IHD ischaemic heart disease
I PREFER Identification of Patients with Heart Failure and Preserved Systolic Function
LMICs low- and middle-income countries
LVEF left ventricular ejection fraction

Figures

[Figure ID: pmed-1001699-g001]
doi: 10.1371/journal.pmed.1001699.g001.
Figure 1  Data acquisition flowchart.

[Figure ID: pmed-1001699-g002]
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Figure 2  Geographic distribution of studies on heart failure in lowand middle-income countries.

[Figure ID: pmed-1001699-g003]
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Figure 3  Male patients by region.

[Figure ID: pmed-1001699-g004]
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Figure 4  Correlation of age and human development index, by country.

r = 0.71, p<0.001. The HDI is a measure produced by the United Nations Development Programme that incorporates gross national income per capita, life expectancy, and time spent in education. It serves as a single statistic that provides a comparable measure of development across nations. HF, heart failure.



[Figure ID: pmed-1001699-g005]
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Figure 5  Aetiology of heart failure: ischaemic heart disease by region.

Percentage of heart failure cases with a documented cause of IHD.



[Figure ID: pmed-1001699-g006]
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Figure 6  Aetiology of heart failure: hypertension by region.

Percentage of heart failure cases with a documented cause of hypertension.



[Figure ID: pmed-1001699-g007]
doi: 10.1371/journal.pmed.1001699.g007.
Figure 7  Aetiology of heart failure: cardiomyopathies by region.

Percentage of heart failure cases with a documented cause of cardiomyopathy.



[Figure ID: pmed-1001699-g008]
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Figure 8  Aetiology of heart failure: valvular heart disease by region.

Percentage of heart failure cases with a documented cause of valvular heart disease.



[Figure ID: pmed-1001699-g009]
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Figure 9  Diuretic use by region.

Loop and/or thiazide diuretics. ∧Rahimzadeh S, Farzadfar F, Ghaziani M (2013) Iranian hospital data project (unpublished data).



[Figure ID: pmed-1001699-g010]
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Figure 10  Angiotensin-converting enzyme inhibitor use by region.

∧Rahimzadeh S, Farzadfar F, Ghaziani M (2013) Iranian hospital data project (unpublished data).



[Figure ID: pmed-1001699-g011]
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Figure 11  Beta-blocker use by region.

∧Rahimzadeh S, Farzadfar F, Ghaziani M (2013) Iranian hospital data project (unpublished data).



[Figure ID: pmed-1001699-g012]
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Figure 12  Mineralocorticoid receptor antagonist use by region.

∧Rahimzadeh S, Farzadfar F, Ghaziani M (2013) Iranian hospital data project (unpublished data).



[Figure ID: pmed-1001699-g013]
doi: 10.1371/journal.pmed.1001699.g013.
Figure 13  In-hospital mortality rates by region.

∧Rahimzadeh S, Farzadfar F, Ghaziani M (2013) Iranian hospital data project (unpublished data).



[Figure ID: pmed-1001699-g014]
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Figure 14  Meta-regression of hypertension against study period.

[Figure ID: pmed-1001699-g015]
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Figure 15  Meta-regression of ischaemic heart disease against study period.

[Figure ID: pmed-1001699-g016]
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Figure 16  Meta-regression of cardiomyopathies against study period.

[Figure ID: pmed-1001699-g017]
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Figure 17  Meta-regression of valvular heart disease against study period.

[Figure ID: pmed-1001699-g018]
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Figure 18  Meta-regression of beta-blocker use against study period.

[Figure ID: pmed-1001699-g019]
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Figure 19  Meta-regression of angiotensin-converting enzyme inhibitor use against study period.

[Figure ID: pmed-1001699-g020]
doi: 10.1371/journal.pmed.1001699.g020.
Figure 20  Meta-regression of mineralocorticoid receptor antagonist use against study period.

[Figure ID: pmed-1001699-g021]
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Figure 21  Meta-regression of diuretic use against study period.

[Figure ID: pmed-1001699-g022]
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Figure 22  Meta-regression of in-hospital mortality rates against study period.

Tables
[TableWrap ID: pmed-1001699-t001] doi: 10.1371/journal.pmed.1001699.t001.
Table 1  Characteristics of Africa region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
Algeria [70], Prospective 2008–2009 All outpatients ≥21 y of age with either a previous or new diagnosis of heart failure.Exclusion: patients with acute decompensated heart failure, or those in another clinic trial. Clinical diagnosis on the basis of the Framingham criteria. [71].91% of participants had an echocardiogram. 400 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. >90% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Cameroon [24] Prospective and retrospective elements 1998–2001 Consecutive patients ≥15 y of age admitted to the cardiology clinic and/or the medical wards of Yaounde General Hospital. Those who had not had an echocardiogram were excluded.A prospective phase was carried out between September and November 2001, where all patients with suspected heart failure were included (39 patients).A retrospective phase involved the use of case notes of those with heart failure admitted to the hospital and undergoing echocardiography between 1998 and September 2001 (128 patients). Clinical diagnosis on the basis of the Framingham criteria [71].All patients had an echocardiogram. 167 Strengths: All patients had echocardiographic assessment.Limitations: This is a study of a single regional tertiary referral centre set in a rural area that may not be representative of the broader population. Patients who had not had an echocardiogram were excluded, but it is unclear how many patients with a clinical diagnosis of heart failure were thus excluded and to what extent this reduces the generalizability of the study findings. Missing data unreported.
Cameroon [29] Prospective 2002–2008 All consecutive patients diagnosed with congestive cardiac failure referred to the cardiac centre of St. Elizabeth Catholic General Hospital, Shisong, Cameroon. Clinical diagnosis on the basis of the Framingham criteria.Echocardiography used, but no indication if all patients underwent this investigation. 462 Strengths: Comprehensive prospective study encompassing all patients diagnosed within the study period. Loss to follow-up documented.Limitations: This is a study of a single regional cardiology referral centre that may not be representative of the broader population. Missing data not transparently accounted for.
Democratic Republic of the Congo [32] Prospective 2003–2004 Every fourth patient admitted with heart failure as an inpatient having been seen at the cardiology clinic of the Lomo Medical Centre of the Heart of Africa Cardiovascular Centre in Kinshasa. Echocardiography. 100 Strengths: All patients had echocardiographic assessment.Limitations: This is a study of a single urban outpatient cardiology referral centre that may not be representative of the broader population. Missing data not transparently accounted for.
Ghana [30] Prospective 1992–1995 Consecutive patients with heart failure referred to the National Cardiothoracic Centre, Accra, over 4 y. Framingham criteria.All patients had an echocardiogram performed. 572 Strengths: This centre receives referrals from all hospitals across the country, increasing the generalizability of the results. All patients had echocardiography.Limitations: Acknowledged potential for referral bias as patients at this single urban tertiary specialist centre may not be representative of heart failure management elsewhere. Unclear if there were missing data, and how they were accounted for.
Nigeria [36] Retrospective 1995–2005 The case notes of 202 patients with heart failure were randomly selected from the outpatient and inpatient departments of University College Hospital, Ibadan. New York Heart Association classification. 202 Limitations: Retrospective study with uncertain diagnostic accuracy. Inpatient and outpatient management were not separated. This is a study of a single urban tertiary referral centre that may not be representative of the broader population. Missing data not transparently accounted for.
Nigeria [34] Retrospective 1996–2005 All patients recorded as having a diagnosis of heart failure from the mortality records of the University of Ilorin Teaching Hospital Not specified. 228 Strengths: Comprehensive review of all deaths and their respective case notes from the hospital, limiting selection bias.Limitations: Uncertain diagnostic accuracy. This is a single urban teaching hospital providing services to north-central Nigeria. Although the hospital covers a large catchment area, the patients may nonetheless not be representative of the broader population.
Nigeria [33] Prospective 1997–2001 Records of all patients admitted with cardiovascular disease to the Obafemi Awolowo University Teaching Hospitals Complex in Ife, Nigeria. Not specified. 386 Strengths: Single tertiary referral centre providing services to 10 million individuals in the southwest of Nigeria, increasing the study's generalizability.Limitations: Single centre, though with a large catchment area, may not be representative of the broader population. No standardised diagnostic criteria used.
Nigeria [37] Retrospective 1998–2001 All patients admitted to the medical wards of the University of Uyo Teaching Hospital in southern Nigeria with heart failure during the dry seasons within the study period.Exclusion: Patients with renal disease or suspected coronary artery disease. Clinical features with the aid of blood results, chest radiography, electrocardiography, and echocardiography. The proportion receiving additional investigations is unknown. 245 Strengths: Comprehensive assessment of patients with heart failure as coded for by this hospital.Limitations: Single tertiary referral centre may not be representative of the broader population. Study was a retrospective study of case notes; consequently, diagnostic accuracy is uncertain. Proportions receiving additional gold-standard investigations, such as echocardiography, not documented.
Nigeria [31] Retrospective 2001–2005 All adults ≥18 y with congestive cardiac failure admitted to the medical wards of the University of Port Harcourt Teaching Hospital.Exclusion: patients whose condition did not meet the Framingham criteria or who died within 24 h of admission. Framingham criteria. 423 Strengths: Clear diagnostic criteria. Comprehensive assessment of patients with heart failure.Limitations: Single tertiary referral centre may not be representative of the broader population. Retrospective assessment with uncertain accuracy of the aetiology of heart failure. Unclear what proportion received additional investigations such as echocardiography. Unclear how missing data were accounted for.
Nigeria [22] Prospective May–June 2004 Consecutive patients ≥18 y with suspected heart failure presenting to outpatient department, wards, or the casualty unit of Jos University Teaching Hospital. Framingham criteria. 102 Strengths: Consecutive patients included, limiting potential for selection bias. Clear documentation of rationale behind sample size. Standardised diagnosis criteria used. Acknowledged limitations.Limitations: Single tertiary referral centre may not be representative of the broader population. Inpatient and outpatient sample not separated. Aetiology of heart failure ascertained by case notes and clinical findings on examination rather than gold-standard investigation. Echocardiography not available to all patients.
Nigeria [26] Prospective 2006–2008 Consecutive patients ≥15 y with heart failure presenting to the University of Abuja Teaching Hospital. European Society of Cardiology guidelines.Echocardiography available for all patients. 340 Strengths: Large catchment area for this referral centre, improving generalizability. All patients had echocardiographic assessment, improving overall diagnostic accuracy and that of assigned underlying aetiologies of heart failure.Limitations: Single tertiary referral centre may reflect more severe cases or those of uncertain diagnosis, therefore not reflecting practice in the broader health service.
Nigeria [27] Prospective 2006–2010 Clinical registry of consecutive individuals referred for the first time to the cardiology clinic of the University of Abuja Teaching Hospital.Exclusion: those with musculoskeletal chest pain or hepatic or renal failure. European Society of Cardiology guidelines.Echocardiography available from >95% of patients. 475 Strengths: Consecutive patients, reducing the risk of selection bias. Clear, standardised, diagnostic criteria. Documented use of the STROBE guidelines [16] for the reporting of observational studies.Limitations: Single tertiary referral centre may reflect more severe cases or those of uncertain diagnosis, therefore not reflecting practice in the broader health service.
Nigeria [28] Prospective Unknown (published 2009) 177 consecutive individuals with heart failure presenting to the University College Hospital, Ibadan. Framingham criteria.All patients underwent an echocardiogram. 177 Strengths: Clear, standardised, diagnostic criteria. All patients had an echocardiogram, improving the accuracy of heart failure diagnosis and that of underlying aetiology. Catchment area of greater than 3 million individuals, improving the generalizability of the results. Clear explanation of statistical methods used.Limitations: Single tertiary referral centre may reflect more severe cases or those of uncertain diagnosis, therefore not reflecting practice in the broader health service.
Senegal [38] Prospective January–June 2001 Selection criteria not specified. Urban hospital in Dakar. Clinical diagnosis.All patients underwent echocardiography. 170 Strengths: All patients underwent echocardiography, improving the likely accuracy of the diagnosis of heart failure and of assigned aetiology.Limitations: Single urban hospital in the capital may not reflect broader population with heart failure. Unclear selection criteria.
South Africa [25] Prospective 2006 All patients with cardiovascular disease or presenting to the cardiology unit. Those with a de novo presentation with heart failure were included.Exclusion: those with acute ischaemic aetiology. Based on European Society of Cardiology guidelines.All patients had an echocardiogram. 844 Strengths: Sole cardiovascular centre for a population of 1.1 million individuals, increasing the generalizability of findings. All patients underwent echocardiographic assessment, improving likely accuracy of diagnosis and of underlying aetiology of each patient's heart failure. Clear documentation of data availability and criteria applied.Limitations: Exclusion of those with an ischaemic aetiology may underestimate the proportion of those with heart failure due to IHD. Urban hospital setting may not reflect the broader population.
Sub-Saharan Africa [35] Prospective 2007–2010 Patients ≥12 y with acute heart failure confirmed by echocardiography were included.The study was conducted in the following countries: Sudan, Ethiopia, Kenya, Uganda, Mozambique, South Africa, Cameroon, Nigeria, Senegal.Exclusion: those with acute ST-elevation myocardial infarction, known severe renal failure, hepatic failure, or another cause of hypoalbuminemia. Unspecified signs and symptoms of heart failure.All patients had an echocardiogram. 1,006 Strengths: All patients had echocardiographic assessment, improving diagnostic accuracy. Clear documentation of missing data and loss to follow-up as well as how this was accounted for in analyses. First published data on heart failure from a number of African countries.Limitations: Urban single hospital centres included. Individual study sites often had very few patients enrolled (range from 10 to 200). Exclusion criteria may lead to the underestimation of IHD as a cause of heart failure.

Previously unpublished data.


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Table 2  Characteristics of Americas region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
Argentina [23] Retrospective 1992–1999 All patients diagnosed with congestive heart failure, decompensated heart failure, or acute pulmonary oedema as recorded in the electronic vital statistics of a community hospital of Mar del Plata, Argentina. Not specified. 6,368 Strengths: Comprehensive study with limited selection bias.Limitations: Single community hospital that may not be reflective of broader patterns of heart failure prevalence. No standardised method for diagnosing heart failure, relying on discharge reports.
Argentina [21] Prospective 1996–1997 Patients admitted to both the general medical and cardiology wards with decompensated chronic heart failure. Patients must have had heart failure, as diagnosed by the Framingham clinical criteria, for 30 d or more.Exclusion: acute heart failure due to an ischaemic event, those lost to follow-up, and those without an electrocardiogram and chest radiograph. Framingham criteria.Unspecified proportion received echocardiography. 751 Strengths: 31 centres from across Argentina, 42% of which were in Buenos Aires. Standardised diagnostic criteria. Clear statistical methods documented.Limitations: Centres were invited to take part rather than randomised. Uncertain proportion received echocardiographic confirmation. Exclusion criteria may lead to underestimation of IHD as an aetiology of heart failure.
Argentina [43] Prospective 2002–2003 All patients >18 y hospitalised for decompensated chronic heart failure.Exclusion: heart failure secondary to a myocardial infarction or post-operatively. Investigator's discretion. 615 Strengths: 36 centres predominantly based around Buenos Aires or neighbouring regions. Comprehensive assessment of all patients with likely low selection bias.Limitations: Centres were not randomised, rather invited. Consequently, results may not reflect the broader management of heart failure amongst physicians with less of an interest in heart failure. No standard diagnostic criteria. Exclusion criteria may lead to underestimation of IHD as an aetiology of heart failure. Uncertain adjustment for those with missing data.
Argentina [44] Prospective 2007 All patients >18 y of age were included if hospitalised for decompensated chronic heart failure.Exclusion: heart failure as a complication of a myocardial infarction or post-operatively. Investigator's discretion. 736 Strengths: 36 centres from across Argentina.Limitations: Centres invited to take part rather than randomised, and those that did may reflect clinicians with an interest in heart failure, affecting the broader generalizability of results. Exclusion criteria may lead to underestimation of IHD as an aetiology of heart failure. No standard diagnostic criteria. Uncertain adjustment for those with missing data or lost to follow-up. No standard diagnostic criteria for heart failure.
Brazil [45] Retrospective 1992 to 2010 Patients admitted to public hospitals in São Paulo with heart failure. Not specified. 194,098 Strengths: From the Datasus registry, providing hospital episode statistics for the entire public health system of São Paulo.Limitations: Uncertain diagnostic criteria based on individual physician's discretion.
Brazil [42] Prospective 1998–2000 Consecutive patients admitted to hospital with worsening symptoms of heart failure (NYHA functional classes III or IV).Exclusion: patients with heart failure due to valvular heart diseases, thyrotoxicosis, hypothyroidism, severe anaemia, amyloidosis, neoplasia, chronic non-cardiogenic pulmonary diseases, previous heart transplantation, chronic haemodialysis, or participation in drug protocols. Clinical diagnosis based on the Framingham criteria. 494 Strengths: Standardised diagnostic criteria.Limitations: University Teaching Hospital in São Paulo dedicated to cardiology. Exclusion criteria may further hinder generalizability. Only patients with NYHA functional class III or IV, so may not be generalizable to those with milder symptoms. The exclusion of patients with valvular heart disease may impact on the assignment of aetiologies of heart failure. Unclear how loss to follow up and missing data were accounted for.
Brazil [40] Prospective 2001 98 consecutive patients admitted to participating public hospitals and 105 consecutive patients admitted to participating private hospitals within the 3-mo study period in the city of Niteroi with a Boston criteria score of 8 or more. Boston criteria score ≥8. 203 Strengths: Multiple hospitals within Niteroi, improving generalizability. Clear statistical methods reported. Just under half of patients were from the private sector, the remaining from the public sector, allowing direct comparison between these two groups and representation from a broader swathe of society.Limitations: The methods used to select the participating hospitals are unclear, as is the final number of sites included.
Brazil [19] Prospective 2005–2006 Consecutive patients admitted with heart failure and systolic dysfunction. Clinical diagnosis with echocardiographic confirmation. 263 Limitations: Single urban centre that may not be representative of the patterns of care at the national level. Unclear how missing data and loss to follow-up were accounted for. Uncertain diagnostic criteria or proportion receiving echocardiography. Only patients with systolic dysfunction were included, possibly reducing the generalizability of results.
Brazil [39] Prospective 2006–2008 Consecutive patients ≥18 y referred to heart failure clinic with a Boston score of ≥7. Individuals were all classed as living in rural areas as per the Brazilian Institute of Geography and Statistics. Boston criteria score ≥7.All patients underwent echocardiography. 166 Strengths: All patients had echocardiographic assessment. Standard diagnostic criteria.Limitations: Single centre study that may not be representative of the patterns of care at the national level.
Brazil [46] Prospective Unknown (published 2008) Patients consecutively admitted to the emergency department of the Instituto do Coração do Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo over a period of 150 d with the diagnosis of decompensated heart failure. 100 out of the 212 patients initially assessed were retrospectively selected, for whom further details were collected. Not specified. 100 Strengths: Although there were no standard diagnostic criteria for heart failure itself, there were standard criteria for assigning aetiologies of heart failure.Limitations: Single urban tertiary referral centre that may not be representative of the patterns of care at the national level. No standard diagnostic criteria used. Method of selection of the 100 patients for whom more detailed analysis was performed unclear.
Brazil [59] Prospective 16 unspecified months (published 2012). Tertiary centre in Salvador, Bahia, Brazil. Consecutive patients with a diagnosis of heart failure who had had echocardiography. Echocardiography. 383 Strengths: All patients had echocardiographic assessment. Standard criteria for the assignment of aetiologies.Limitations: Single urban tertiary referral centre that may not be representative of the patterns of care at the national level. Only those patients who had already had echocardiography were included. Endemic zone for Chagas disease, which may hinder the generalizability of the study.
Brazil [67] Retrospective 2008 All patients with congestive heart failure treated at the outpatient clinic of Hospital das Clínicas of the Federal University of Goiás.Exclusion: those who died in 2008 (their medical records were incomplete) or who were not from the state of Goiás. Not specified. 144 Strengths: Unbiased case selection.Limitations: Retrospective use of case notes without specified diagnostic criteria. Single urban centre that may not be representative of the patterns of care at the national level. Patients who died within the time frame of the study were excluded, limiting the study to patients with less severe forms of heart failure.
Brazil [65] Prospective 1997 100 patients were randomly selected from the outpatient department of the Hospital das Clinicas, a tertiary referral centre in São Paulo. Patients were included if they were found on echocardiography to have a LVEF of <60%. Echocardiography. 100 Strengths: All patients had echocardiography performed, aiding with the accuracy of diagnosis.Limitations: Single urban tertiary referral centre that may not be representative of the broader population.
Brazil [66] Retrospective 1995 Analysis of those patients admitted with heart failure to the Heart Institute of São Paulo using the PRODESP registry. Not specified. 903 Strengths: Dataset of all patients admitted over the course of 1995 with heart failure to this hospital.Limitations: Specialist heart failure urban hospital, whose patients may not be generalizable. No formal standard for the diagnosis of heart failure is documented.
Chile [41] Prospective 2002–2004 372 patients with NYHA class III or IV heart failure from 14 centres in Chile were included.Exclusion: principal reason for hospitalisation was not heart failure or new-onset heart failure or cardiogenic shock secondary to a myocardial infarction. Clinical diagnosis using European Society of Cardiology diagnostic criteria. In cases of doubt response to treatment was used.52% underwent echocardiography. 372 Strengths: National Registry of Heart Failure of Chile, 14 centres. Clear diagnostic criteria.Limitations: Choice of participating centres not described. Exclusion of patients with heart failure after a myocardial infarction may lead to artificially low rates of IHD as the attributed cause of heart failure.
Chile [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.78% had an echocardiogram. 199 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. 78% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Colombia [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.72% had an echocardiogram. 211 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. >70% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Mexico [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.75% had an echocardiogram. 458 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. 75% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.

Previously unpublished data.

NYHA, New York Heart Association.


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Table 3  Characteristics of Eastern Mediterranean region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
Egypt [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.73% had an echocardiogram. 434 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. >90% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Iran#, Retrospective 1998–2012 All 277 patients with heart failure from a dataset of 83,895 hospitalised patients in Iran.Unpublished dataset. Not specified. 277 Strengths: Multi-centre study.Limitations: Non-random selection of hospitals. Diagnostic criteria used unspecified.
Iran [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.95% had an echocardiogram. 105 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. >90% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Lebanon [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.83% had an echocardiogram. 181 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. >80% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Pakistan [47] Retrospective 2002–2003 First presentation to Agha Khan University Hospital in Karachi with the diagnosis of new-onset congestive heart failure that met the Boston criteria.Exclusion: LVEF≥40%, prior diagnosis of systolic heart failure dating back 3 mo, underlying disease with expected survival of less than 6 months, known primary valvular heart disease (rheumatic or nonrheumatic), patient died in-hospital, or no follow-up available after discharge. Clinical diagnosis based on Boston criteria.All patients received echocardiography. 196 Strengths: All patients had echocardiographic assessment.Limitations: Single tertiary referral centre in Karachi may not be generalizable to the broader population. The exclusion of valvular heart disease may impact on the aetiologies ascribed to cases of heart failure. Similarly, the exclusion of those who died in hospital may affect the generalizability of the findings.
Tunisia [70], Prospective 2008–2009 All outpatients ≥21 y of age with new or previously diagnosed heart failure.Exclusion: patients with acute decompensated heart failure. Framingham criteria.71% had an echocardiogram. 257 These data come from the I PREFER registry.Strengths: >10 centres. Sites were randomly selected, and all cardiologists within the country considered eligible. Missing data and loss to follow-up transparent. Prospective trial within a specified recruitment period. 71% had confirmation of heart failure through echocardiography.Limitations: Representative only of those attending outpatient cardiology services, excluding the acute sector or those patients in primary care with heart failure not under joint care of a cardiologist.
Yemen [48] Prospective 2007–2008 First 100 consecutive patients admitted to Ibn Seena Central Hospital, Mukalla, with heart failure. All patients were required to have blood tests, electrocardiogram, echocardiogram, and chest radiogram.Exclusion: all patients who for any reason dropped from follow-up before investigation was completed (died, transferred, discharged) Framingham criteria.All patients underwent echocardiography. 100 Strengths: Clear diagnostic criteria for underlying aetiologies. All patients had echocardiographic assessment. Referral centre for a large catchment area.Limitations: Single urban tertiary referral centre may not be representative of the broader population of patients with heart failure.

Previously unpublished data.

#S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data.


[TableWrap ID: pmed-1001699-t004] doi: 10.1371/journal.pmed.1001699.t004.
Table 4  Characteristics of Europe region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
Romania [51] Retrospective 2006 459 consecutively admitted patients between January and December 2006 to the cardiology department with a discharge diagnosis of chronic heart failure. Not specified. 459 Limitations: Single urban general hospital may not be representative of the broader population of patients with heart failure. Diagnostic criteria not clear. Data recorded from hospital files. Unclear how missing data were accounted for.
Romania [50] Prospective 2008–2009 All consecutive patients hospitalised with a primary diagnosis of acute heart failure syndromes.Exclusion: patients with high-output heart failure. European Society of Cardiology guidelines.80% of patients had an echocardiogram. 3,224 Strengths: National registry involving 13 sites, increasing the generalizability of its results. A large majority of patients had echocardiographic assessment. Both tertiary academic centres and general hospitals were included, increasing generalizability.Limitations: Unclear how missing data were accounted for, although this issue is acknowledged in their limitations section.
Serbia [61] Cross-sectional Unknown Patients with chronic heart failure were recruited from an outpatient cardiology clinic at the Clinic for Cardiovascular Diseases, Clinical Center Niš.Exclusion: those who had had a worsening of symptoms or changes in treatment in the preceding 2 wk. European Society of Cardiology and echocardiography. 127 Strengths: All patients underwent echocardiography. Standardised diagnostic criteria.Limitations: Single urban centre may not be representative of the broader population. Unclear method of case ascertainment.
Turkey [49] Retrospective 1997–1998 Medical records of consecutive patients admitted for congestive heart failure at 16 academic hospitals were selected for review: “The most recent, in average, 50 patients from each centre with sufficient data for CHF [congestive heart failure] in their files were included”. American Heart Association guidelines.81% had an echocardiogram. 661 Strengths: 16 centres from across the country. A large majority of individuals had echocardiographic assessment.Limitations: Results from academic hospitals may not be generalizable to the broader health system. Method of case ascertainment may lead to selection bias. Unclear how missing data were accounted for.
Turkey [64] Prospective 1999–2000 A survey was conducted of a random sample of 117 primary care physicians from across Turkey who logged all patients they saw with heart failure. Not specified. 876 Strengths: Real-world practice taken from a random sample of 117 primary care physicians from across Turkey.Limitations: Diagnosis of heart failure left to the clinicians.
Turkey [63] Prospective 2005 A sample of 4,650 randomly selected individuals had their height, weight, blood pressure measured as well as an ECG and blood taken for NT-proBNP level. Any of the sample with a cardiac history, abnormal ECG, or NT-proBNP ≥120 pg/ml was further investigated with echocardiography. Echocardiography. 320 Strengths: Population-based random sample of individuals may provide generalizable information on prevalence of heart failure.

ECG, electrocardiogram.


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Table 5  Characteristics of South East Asia region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
India [69], Retrospective 2008–2012 Billing codes from hospital used to identify patients with heart failure in Andhra Pradesh. Not specified. 5,758 Strengths: This study of billing data is from a large sample of over 1.5 million hospitalisations.Limitations: Billing data rely on clinical coding, and consequently there are no standardised diagnostic criteria available.
Indonesia [20] Prospective 2006 Consecutively hospitalised patients ≥18 y in five hospitals. Patients with heart failure primarily being treated as a co-morbid rather than primary condition.Exclusion: those without an accessible medical record, those without acute decompensated heart failure. Not specified. 1,687 Indonesian arm of ADHERE-International.Strengths: Five hospitals, improving the potential generalizability of results. Missing data transparently accounted for. Echocardiographic assessment in 37.9% of patients.Limitations: Discharge data with lack of standardisation in the diagnosis of heart failure, which may lead to selection bias.
Thailand [52] Retrospective 2006–2007 Consecutively hospitalised patients age more than 18 y at 18 cardiovascular centres. Patients with heart failure primarily being treated as a co-morbid rather than primary condition.Exclusion: those without an accessible medical record, patients with cardiogenic shock, and perioperative heart failure. Not specified. 1,612 Thai arm of ADHERE-International.Strengths: 18 cardiovascular centres from across the country, consequently greater generalizability of the results. 60.4% had echocardiographic assessment.Limitations: Discharge data with lack of standardisation in the diagnosis of heart failure, which may lead to selection bias.

Previously unpublished data.


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Table 6  Characteristics of Western Pacific region studies and databases included.
Country of Origin Study Design Recruitment Period Selection Criteria Heart Failure Definition Cases of Heart Failure Strengths and Limitations
China [57] Retrospective 1980–2000 Patients admitted with heart failure to participating hospitals. Not specified. 1,756 Strengths: Multi-centre study may increase generalizability of results. Long study time period enabling analysis of trends across time.Limitations: Retrospective use of case notes, with consequent lack of standardised diagnostic criteria, may increase selection and reporting bias.
China [58] Retrospective 1980–2008 Patients admitted to the medical wards during the study period. Not specified. 2,458 Strengths: Long time period of study allowed the analysis of medication prescription changes over time.Limitations: Urban single-centre study may not be generalizable to broader health service. Retrospective use of case notes without standardised diagnostic criteria for heart failure may increase reporting and selection bias.
China [56] Retrospective 1995–2004 Patients admitted with heart failure. Not specified. 259 Limitations: Diagnostic criteria not standardised, leading to potential for reporting and selection bias.
China [53] Retrospective 1995–2009 Patients admitted with heart failure to three university hospitals. American Heart Association 2005 guidelines. 1,119 Strengths: Multi-centre cohort study.Limitations: Academic centres may not reflect the broader health service.
China [55] Retrospective 2007 Patients admitted with heart failure. Framingham criteria. 478 Limitations: Rural single-centre study that may not be generalizable to the broader health service. Retrospective analysis of case notes open to reporting bias.
China [54] Retrospective 2008–2009 Patients admitted with heart failure. European Society of Cardiology 2005 guidelines 206 Limitations: Urban single-centre study that may not be generalizable to the broader health service.
China [60] Prospective Unknown (published 2012) Individuals admitted to the People's Liberation Army General Hospital, Beijing, over the age of 60 y with a diagnosis of chronic heart failure.Exclusion: those with severe aortic stenosis, anticipated cardiac transplantation, or a left ventricular assist device. European Society of Cardiology 2008 guidelines. 327 Limitations: Single-centre army general hospital in the capital with a high proportion of male patients (78% of this cohort) may not be broadly generalizable.
China [62] Prospective Unknown (published 2009) Cluster randomised sample of adults in primary care facilities with congestive heart failure in six counties of Liaoning Province. Framingham criteria. 529 Strengths: Cluster randomisation of primary care facilities, reducing potential for bias. Representation from six counties of Liaoning Province may improve regional generalizability of the results.Limitations: Uncertain diagnostic criteria and patient pool.
Malaysia [68], Retrospective 2007–2008 Consecutive individuals with a principal discharge diagnosis of heart failure, using the relevant International Classification of Disease-9 codes. Patients with heart failure primarily being treated as a co-morbid rather than primary condition.Exclusion: patients <18 y, those without an accessible medical record, those without acute decompensated heart failure. Not specified. 907 Malaysian arm of ADHERE-International.Strengths: Multi-centre trial, improving the potential generalizability of results. All questions on the electronic case report were required to be completed, eliminating reporting bias due to missing data.Limitations: Discharge data with lack of standardisation in the diagnosis of heart failure, which may lead to selection bias.
Philippines [68], Retrospective 2006–2007 All consecutive individuals admitted with an International Classification of Disease-9 code for heart failure. Patients with heart failure primarily being treated as a co-morbid rather than primary condition.Exclusion: Patients <18 y, those without an accessible medical record, and those without acute decompensated heart failure. Not specified. 261 Philippines arm of ADHERE-International.Strengths: Multi-centre trial, improving the potential generalizability of results. All questions on the electronic case report were required to be completed, eliminating reporting bias due to missing data.Limitations: Discharge data with lack of standardisation in the diagnosis of heart failure, which may lead to selection bias.

Previously unpublished data.


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Table 7  Included countries grouped by World Health Organization region.
Africa Americas Eastern Mediterranean Europe South East Asia Western Pacific
Algeria Argentina Egypt Romania India China
Cameroon Brazil Iran Turkey Indonesia Malaysia
DRC Chile Lebanon Serbia Thailand Philippines
Ethiopia Colombia Pakistan
Ghana Mexico Tunisia
Kenya Yemen
Mozambique
Nigeria
Senegal
South Africa
Uganda

DRC, Democratic Republic of the Congo.


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Table 8  Characteristics of patients, by region.
Characteristic Region
Africa Americas Eastern Mediterranean Europe South East Asia Western Pacific All
Age
Mean age (range), in years* 52 (42–64) 70 (53–77) 63 (57–69) 67 (61–73) 54 (50–64) 67 (53–74) 63 (42–77)
Number of studies 14 14 4 5 3 7 45
Male
Percent male (95% CI) 51% (43%–59%) 58% (54%–63%) 65% (61%–70%) 61% (48%–73%) 60% (51%–70%) 58% (50%–65%) 58% (54%–62%)
I2 (95% CI) 99% (98%–99%), p<0.001 98% (98%–99%), p<0.001 61% (6%–84%), p<0.0239 99% (98%–99%), p<0.001 99% (98%–99%), p<0.001 98% (97%–99%), p<0.001 100% (100%–100%), p<0.001
Number of studies 13 16 3 6 3 9 48
LVEF
Mean (range) LVEF, in percent* 42% (29%–49%) 41% (27%–43%) 50% (34%–55%) 38% (38%–40%) 33% (—) 42% (38%–57%) 40% (27%–57%)
Number of studies 6 7 1 3 1 2 17
Length of stay
Mean (range) number of days* 11 (9–13) 10 (5–25) 5 (—) 3 (—) 23 (13–35) 10 (5–35)
Number of studies 3 6 1 1 3 14

*Weighted by study size.


[TableWrap ID: pmed-1001699-t009] doi: 10.1371/journal.pmed.1001699.t009.
Table 9  Characteristics of patients, by country.
Region and Country Recruitment Period Heart Failure Cases Mean Age (Years) Male (Percent) Mean Length of Stay (Days) Mean LVEF (Percent)
Africa
Algeria [70], 2008–2009 400 64 60% 49%
Cameroon [24] 1998–2001 167 57 59% 23%
Cameroon [29] 2002–2008 462 43 57% 13
Democratic Republic of the Congo [32] 2003–2004 100 57 48%
Ghana [30] 1992–1995 572 42 55%
Nigeria [26] 2006–2008 340 51 51% 42%
Nigeria [27] 2006–2010 475 49 50%
Nigeria [22] 2004 102 45 31%
Nigeria [28] Unspecified 177 52 51% 45%
Nigeria [31] 2001–2005 423 54 57%
Nigeria [36] 1995–2005 202 56 54%
Senegal [38] 2001 170 50 11
South Africa [25] 2006 844 55 43% 45%
Sub-Saharan Africa [35] 2007–2010 1,006 52 49% 9 40%
Americas
Argentina [21] 1996–1997 751 66 41%
Argentina [43] 2002–2003 615 70 55%
Argentina [44] 2007 736 59%
Argentina [23] 1992–1999 6,368 77 65% 5
Brazil [39] 2006–2008 166 61 51% 49%
Brazil [40] 2001 203 67 50% 8*
Brazil [42] 1998–2000 494 58 70% 34%
Brazil [45] 1992–2010 194,098 51% 10
Brazil [46] Unspecified 100 59 56% 9 46%
Brazil [19] 2005–2006 263 60 63% 25 27%
Brazil [59] Unspecified 383 54 53%
Brazil [66] 1997 100 57 76% 43%
Brazil [67] 2008 144 61 54%
Brazil [65] 1995 903 53 60%
Chile [41] 2002–2004 372 69 59% 11 35%
Chile [70], 2008–2009 199 65 55% 42%
Colombia [70], 2008–2009 211 70 86% 46%
Mexico [70], 2008–2009 458 68 43% 54%
Eastern Mediterranean
Egypt [70], 2008–2009 434 58 66% 55%
Iran#, 1998–2012 277 67 5
Iran [70], 2008–2009 105 57 77% 34%
Lebanon [70], 2008–2009 181 69 61% 43%
Pakistan [47] 2002–2003 196 61 65%
Tunisia [70], 2008–2009 257 67 51% 53%
Yemen [48] 2007–2008 100 58 65%
Europe
Romania [50] 2008–2009 3,224 69 56% 38%
Romania [51] 2006 459 61 86%
Serbia [61] Unspecified 127 71 73% 40%
Turkey [49] 1997–1998 661 61 64% 38%
Turkey [63] 2005 320 40%
Turkey [64] 1998–2000 876 64 48%
South East Asia
India [69], 2008–2012 5,758 50 66% 3
Indonesia [20] 2006 1,687 60 65% 33%
Thailand [52] 2006–2007 1,612 64 50%
Western Pacific
China [53] 1995–2009 1,119 65 71% 38%
China [54] 2008–2009 206 74 56%
China [55] 2007 478 69 47%
China [56] 1995–2004 259 70 63% 29
China [57] 1980–2000 1,756 68 56% 35
China [58] 1980–2008 2,458 71 52% 13
China [60] Unspecified 327 78% 57%
China [62] 2008 529 30%
Malaysia [68], 2007–2008 907 61 69%
Philippines [68], 2006–2007 725 53 55%

Previously unpublished dataset.

*Contributed by author.

#S. Rahimzadeh, F. Farzadfar F, and M. Ghaziani, unpublished data.


[TableWrap ID: pmed-1001699-t010] doi: 10.1371/journal.pmed.1001699.t010.
Table 10  Reported causes of heart failure, by region.
Cause Region
Africa Americas Eastern Mediterranean Europe South East Asia Western Pacific All
Hypertension
Percent (95% CI) 46% (36%–55%) 31% (19%–43%) 52% (35%–69%) 30% (12%–48%) 12% (10%–14%) 21% (11%–30%) 37% (30%–43%)
I2 (95% CI) 98% (98%–99%), p<0.001 99% (99%–99%), p<0.001 97% (95%–98%), p<0.001 99% (98%–99%), p<0.001 98% (97%–99%), p<0.000 99% (99%–99%), p<0.001
Number of studies 13 12 2 3 1 4 33
IHD
Percent (95% CI) 8% (5%–11%) 33% (27%–38%) 59% (46%–71%) 61% (58%–64%) 45% (43%–48%) 54% (37%–71%) 35% (28%–42%)
I2 (95% CI) 98% (97%–98%), p<0.001 96% (94%–97%), p<0.001 94% (89%–97%), p<0.001 59% (0%–86%), p<0.063 99% (99%–100%), p<0.001 100% (100%–100%), p<0.001
Number of studies 11 14 2 4 1 5 35
Valvulopathy
Percent (95% CI) 18% (13%–23%) 15% (11%–20%) 22% (14%–30%) 25% (4%–46%) 19% (17%–21%) 21% (8%–34%) 18% (15%–22%)
I2 (95% CI) 96% (95%–97%), p<0.001 95% (92%–96%), p<0.001 89% (78%–95%), p<0.001 99% (—), p<0.001 99% (98%–99%), p<0.001 98% (97%–98%), p<0.001
Number of studies 13 9 2 2 1 4 29
Cardiomyopathy
Percent (95% CI) 24% (19%–29%) 30% (21%–39%) 27% (12%–42%) 7% (3%–12%) 14% (12%–16%) 14% (4%–24%) 24% (20%–29%)
I2 (95% CI) 94% (91%–96%), p<0.001 98% (97%–99%), p<0.001 97% (95%–98%), p<0.001 99% (99%–100%), p<0.001 99% (98%–99%), p<0.001
Number of studies 12 7 2 1 1 4 26

[TableWrap ID: pmed-1001699-t011] doi: 10.1371/journal.pmed.1001699.t011.
Table 11  Reported management of heart failure, by region.
Management Region
Africa Americas Eastern Mediterranean Europe South East Asia Western Pacific All
ACEIs
Percent (95% CI) 70% (62%–79%) 60% (51%–69%) 48% (27%–69%) 64% (53%–76%) 31% (21%–40%) 47% (19%–74%) 57% (49%–64%)
I2 (95% CI) 96% (94%–98%), p<0.001 98% (98%–99%), p<0.001 99% (99%–99%), p<0.001 99% (99%–99%), p<0.001 97% (—), p<0.001 100% (100%–100%), p<0.001 100% (100%–100%), p<0.001
Number of studies 6 9 3 5 1 7 29
Beta-blockers
Percent (95% CI) 25% (13%–37%) 38% (26%–51%) 49% (27%–71%) 29% (9%–49%) 26% (24%–27%) 27% (9%–44%) 34% (28%–41%)
I2 (95% CI) 99% (98%–99%), p<0.001 99% (99%–99%), p<0.001 99% (99%–99%), p<0.001 100% (100%–100%), p<0.001 0% (—), p<0.564 100% (100%–100%), p<0.001 100% (99%–100%), p<0.001
Number of studies 7 8 3 4 1 5 26
Diuretics
Percent (95% CI) 73% (48%–99%) 71% (62%–80%) 71% (49%–94%) 71% (58%–85%) 65% (50%–80%) 57% (30%–85%) 69% (60%–78%)
I2 (95% CI) 100% (100%–100%), p<0.001 99% (99%–99%), p<0.001 99% (99%–100%), p<0.001 100% (99%–100%), p<0.001 99% (—), p<0.001 100% (100%–100%), p<0.001 100% (100%–100%), p<0.001
Number of studies 6 9 2 5 1 6 27
Mineralocorticoid receptor antagonists
Percent (95% CI) 46% (30%–63%) 32% (24%–40%) 26% (13%–39%) 41% (25%–58%) 15% (10%–19%) 17% (7%–26%) 32% (25%–39%)
I2 (95% CI) 98% (97%–99%), p<0.001 96% (94%–97%), p<0.001 97% (95%–98%), p<0.001 100% (100%–100%), p<0.001 92% (—), p<0.001 99% (99%–99%), p<0.001 100% (100%–100%), p<0.001
Number of studies 5 5 2 5 1 4 20


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