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      Heart Failure Care in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis

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          Abstract

          In a systematic review and meta-analysis, Kazem Rahimi and colleagues examine the burden of heart failure in low- and middle-income countries.

          Please see later in the article for the Editors' Summary

          Abstract

          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 We thus set out to review both published and unpublished information on the presentation, causes, management, and outcomes of heart failure in LMICs.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 Additional unpublished data were requested from investigators and international heart failure experts.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

          Editors' Summary

          Background

          A healthy heart pumps about 23,000 liters of blood around the body every day. This blood delivers oxygen and nutrients to the rest of the body and carries carbon dioxide and waste products away from the tissues and organs. A healthy heart is therefore essential for life. Unfortunately, many people (particularly elderly people) develop heart failure, a life-threatening condition in which the heart no longer pumps enough blood to meet all the body's needs because it has become too weak or too stiff to work properly. Heart failure can affect the left, right, or both sides of the heart, and it can develop slowly (chronic heart failure) or quickly (acute heart failure). Its symptoms include swelling (edema) of the feet, ankles, and legs, tiredness, and shortness of breath. Heart failure, which is most commonly caused by coronary heart disease (blockage with fatty deposits of the blood vessels that supply the heart) or high blood pressure (hypertension), cannot be cured. However, lifestyle changes (for example, losing weight and avoiding salty food) and various medications can control heart failure and improve the quality of life of patients.

          Why Was This Study Done?

          In high-income countries (HICs), heart failure is a common condition that typically consumes 1%–2% of healthcare resources. Experts believe that heart failure may soon become a major public health issue in low- and middle-income countries (LMICs) because fewer people are dying of infectious diseases in these countries than in the past. LMICs need to plan for this eventuality, but little is known about the current burden of heart failure in LMICs. Here, the researchers undertake a systematic review and meta-analysis of published and unpublished information on the presentation, causes, management, and outcomes of heart failure in LMICs. A systematic review uses predefined criteria to identify all the research on a given topic; a meta-analysis uses statistical approaches to combine the results of several studies.

          What Did the Researchers Do and Find?

          The researchers identified 49 published studies and four unpublished databases that provided information on nearly 240,000 hospitalizations for acute and chronic heart failure in 31 LMICs. Across these LMICs, the average age of patients admitted to hospital for heart failure was 63 years, more than ten years younger than the average admission age in HICs. Differences in mean age at presentation, which ranged from 42 years in Cameroon and Ghana to 75 years in Argentina, largely correlated with the human development index (a measure of national well-being) of individual LMICs. Notably, acute heart failure accounted for 2.2% of all hospital admissions in the LMICs for which data were available. Hypertension was the main cause of heart failure in Africa and the Americas, whereas ischemic heart disease was the main cause in all other regions. More than two-thirds of patients were prescribed diuretics for heart failure, whereas only 57% of patients were treated with angiotensin-converting enzyme inhibitors, only 34% were treated with beta-blockers, and only 32% were treated with mineralocorticoid receptor antagonists, the three treatments currently recommended in guidelines for managing heart failure. Finally, on average, patients admitted to hospital for heart failure in LMICs spent ten days in hospital, and 8.3% of them died in hospital (compared to 6.7% and 4% of similar patients across Europe and the US, respectively).

          What Do These Findings Mean?

          These findings show that the presentation, causes, management, and outcomes of heart failure vary substantially across LMICs. Importantly, however, these findings reveal that heart failure is already a major burden in LMICs and that the use of recommended medications for heart failure is currently suboptimal in these countries. Because the studies included in this systematic review and meta-analysis set out to answer different research questions and used different methods to diagnose heart failure, the estimates of the burden of heart failure in LMICs provided here may not be completely accurate. Moreover, because the data were derived mainly from urban tertiary referral hospitals, these findings may not reflect the broader picture of heart failure in the community in LMICs. However, although additional studies are needed to completely assess the burden of heart failure in LMICs, the present findings nevertheless highlight the need to implement better strategies for the management of heart failure in LMICs.

          Additional Information

          Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001699.

          • This study is further discussed in a PLOS Medicine Perspective by Druin Burch

          • The US National Heart, Lung, and Blood Institute provides information for patients about heart failure

          • The UK National Health Service Choices website provides information about all aspects of heart failure

          • The American Heart Association, a not-for-profit organization, also provides detailed information about heart failure for patients and their carers

          • The British Heart Foundation, a not-for-profit organization, provides additional information about heart failure, including a personal story about heart failure; further personal stories about heart failure are provided by the not-for-profit organization Healthtalkonline

          • Heart Failure Matters provides practical information about heart failure for patients, families, and caregivers in several languages; its website includes an animated journey through heart failure and several personal stories about the condition

          • MedlinePlus provides links to further resources about heart failure (in English and Spanish)

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          Most cited references89

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement

          Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a starting point for developing clinical practice guidelines. Granting agencies may require a systematic review to ensure there is justification for further research,3 and some health care journals are moving in this direction.4 As with all research, the value of a systematic review depends on what was done, what was found, and the clarity of reporting. As with other publications, the reporting quality of systematic reviews varies, limiting readers' ability to assess the strengths and weaknesses of those reviews. Several early studies evaluated the quality of review reports. In 1987, Mulrow examined 50 review articles published in 4 leading medical journals in 1985 and 1986 and found that none met all 8 explicit scientific criteria, such as a quality assessment of included studies.5 In 1987, Sacks and colleagues6 evaluated the adequacy of reporting of 83 meta-analyses on 23 characteristics in 6 domains. Reporting was generally poor; between 1 and 14 characteristics were adequately reported (mean = 7.7; standard deviation = 2.7). A 1996 update of this study found little improvement.7 In 1996, to address the suboptimal reporting of meta-analyses, an international group developed a guidance called the QUOROM Statement (QUality Of Reporting Of Meta-analyses), which focused on the reporting of meta-analyses of randomized controlled trials.8 In this article, we summarize a revision of these guidelines, renamed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses), which have been updated to address several conceptual and practical advances in the science of systematic reviews (Box 1). Terminology The terminology used to describe a systematic review and meta-analysis has evolved over time. One reason for changing the name from QUOROM to PRISMA was the desire to encompass both systematic reviews and meta-analyses. We have adopted the definitions used by the Cochrane Collaboration.9 A systematic review is a review of a clearly formulated question that uses systematic and explicit methods to identify, select, and critically appraise relevant research, and to collect and analyze data from the studies that are included in the review. Statistical methods (meta-analysis) may or may not be used to analyze and summarize the results of the included studies. Meta-analysis refers to the use of statistical techniques in a systematic review to integrate the results of included studies. Developing the PRISMA Statement A 3-day meeting was held in Ottawa, Canada, in June 2005 with 29 participants, including review authors, methodologists, clinicians, medical editors, and a consumer. The objective of the Ottawa meeting was to revise and expand the QUOROM checklist and flow diagram, as needed. The executive committee completed the following tasks, prior to the meeting: a systematic review of studies examining the quality of reporting of systematic reviews, and a comprehensive literature search to identify methodological and other articles that might inform the meeting, especially in relation to modifying checklist items. An international survey of review authors, consumers, and groups commissioning or using systematic reviews and meta-analyses was completed, including the International Network of Agencies for Health Technology Assessment (INAHTA) and the Guidelines International Network (GIN). The survey aimed to ascertain views of QUOROM, including the merits of the existing checklist items. The results of these activities were presented during the meeting and are summarized on the PRISMA Website. Only items deemed essential were retained or added to the checklist. Some additional items are nevertheless desirable, and review authors should include these, if relevant.10 For example, it is useful to indicate whether the systematic review is an update11 of a previous review, and to describe any changes in procedures from those described in the original protocol. Shortly after the meeting a draft of the PRISMA checklist was circulated to the group, including those invited to the meeting but unable to attend. A disposition file was created containing comments and revisions from each respondent, and the checklist was subsequently revised 11 times. The group approved the checklist, flow diagram, and this summary paper. Although no direct evidence was found to support retaining or adding some items, evidence from other domains was believed to be relevant. For example, Item 5 asks authors to provide registration information about the systematic review, including a registration number, if available. Although systematic review registration is not yet widely available,12,13 the participating journals of the International Committee of Medical Journal Editors (ICMJE)14 now require all clinical trials to be registered in an effort to increase transparency and accountability.15 Those aspects are also likely to benefit systematic reviewers, possibly reducing the risk of an excessive number of reviews addressing the same question16,17 and providing greater transparency when updating systematic reviews. The PRISMA Statement The PRISMA Statement consists of a 27-item checklist (Table 1; see also Text S1 for a downloadable template for researchers to re-use) and a 4-phase flow diagram (Figure 1; see also Figure S1 for a downloadable template for researchers to re-use). The aim of the PRISMA Statement is to help authors improve the reporting of systematic reviews and meta-analyses. We have focused on randomized trials, but PRISMA can also be used as a basis for reporting systematic reviews of other types of research, particularly evaluations of interventions. PRISMA may also be useful for critical appraisal of published systematic reviews. However, the PRISMA checklist is not a quality assessment instrument to gauge the quality of a systematic review. Box 1 Conceptual issues in the evolution from QUOROM to PRISMA Figure 1 Flow of information through the different phases of a systematic review Table 1 Checklist of items to include when reporting a systematic review or meta-analysis From QUOROM to PRISMA The new PRISMA checklist differs in several respects from the QUOROM checklist, and the substantive specific changes are highlighted in Table 2. Generally, the PRISMA checklist “decouples” several items present in the QUOROM checklist and, where applicable, several checklist items are linked to improve consistency across the systematic review report. Table 2 Substantive specific changes between the QUOROM checklist and the PRISMA checklist (a tick indicates the presence of the topic in QUOROM or PRISMA) The flow diagram has also been modified. Before including studies and providing reasons for excluding others, the review team must first search the literature. This search results in records. Once these records have been screened and eligibility criteria applied, a smaller number of articles will remain. The number of included articles might be smaller (or larger) than the number of studies, because articles may report on multiple studies and results from a particular study may be published in several articles. To capture this information, the PRISMA flow diagram now requests information on these phases of the review process. Endorsement The PRISMA Statement should replace the QUOROM Statement for those journals that have endorsed QUOROM. We hope that other journals will support PRISMA; they can do so by registering on the PRISMA Website. To underscore to authors, and others, the importance of transparent reporting of systematic reviews, we encourage supporting journals to reference the PRISMA Statement and include the PRISMA web address in their Instructions to Authors. We also invite editorial organizations to consider endorsing PRISMA and encourage authors to adhere to its principles. The PRISMA Explanation and Elaboration Paper In addition to the PRISMA Statement, a supporting Explanation and Elaboration document has been produced18 following the style used for other reporting guidelines.19-21 The process of completing this document included developing a large database of exemplars to highlight how best to report each checklist item, and identifying a comprehensive evidence base to support the inclusion of each checklist item. The Explanation and Elaboration document was completed after several face-to-face meetings and numerous iterations among several meeting participants, after which it was shared with the whole group for additional revisions and final approval. Finally, the group formed a dissemination subcommittee to help disseminate and implement PRISMA. Discussion The quality of reporting of systematic reviews is still not optimal.22-27 In a recent review of 300 systematic reviews, few authors reported assessing possible publication bias,22 even though there is overwhelming evidence both for its existence28 and its impact on the results of systematic reviews.29 Even when the possibility of publication bias is assessed, there is no guarantee that systematic reviewers have assessed or interpreted it appropriately.30 Although the absence of reporting such an assessment does not necessarily indicate that it was not done, reporting an assessment of possible publication bias is likely to be a marker of the thoroughness of the conduct of the systematic review. Several approaches have been developed to conduct systematic reviews on a broader array of questions. For example, systematic reviews are now conducted to investigate cost-effectiveness,31 diagnostic32 or prognostic questions,33 genetic associations,34 and policy-making.35 The general concepts and topics covered by PRISMA are all relevant to any systematic review, not just those whose objective is to summarize the benefits and harms of a health care intervention. However, some modifications of the checklist items or flow diagram will be necessary in particular circumstances. For example, assessing the risk of bias is a key concept, but the items used to assess this in a diagnostic review are likely to focus on issues such as the spectrum of patients and the verification of disease status, which differ from reviews of interventions. The flow diagram will also need adjustments when reporting individual patient data meta-analysis.36 We have developed an explanatory document18 to increase the usefulness of PRISMA. For each checklist item, this document contains an example of good reporting, a rationale for its inclusion, and supporting evidence, including references, whenever possible. We believe this document will also serve as a useful resource for those teaching systematic review methodology. We encourage journals to include reference to the explanatory document in their Instructions to Authors. Like any evidence-based endeavour, PRISMA is a living document. To this end we invite readers to comment on the revised version, particularly the new checklist and flow diagram, through the PRISMA website. We will use such information to inform PRISMA's continued development. Note: To encourage dissemination of the PRISMA Statement, this article is freely accessible on the Open Medicine website and the PLoS Medicine website and is also published in the Annals of Internal Medicine, BMJ, and Journal of Clinical Epidemiology. The authors jointly hold the copyright of this article. For details on further use, see the PRISMA website. The PRISMA Explanation and Elaboration Paper is available at the PLoS Medicine website. Supporting Information Figure S1 Flow of information through the different phases of a systematic review (downloadable template document for researchers to re-use) Text S1 Checklist of items to include when reporting a systematic review or meta-analysis (downloadable template document for researchers to re-use)
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            Meta-analysis in clinical trials

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              Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

              Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                PLoS
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, USA )
                1549-1277
                1549-1676
                August 2014
                12 August 2014
                : 11
                : 8
                : e1001699
                Affiliations
                [1 ]The George Institute for Global Health, University of Oxford, Oxford, United Kingdom
                [2 ]The George Institute for Global Health, University of Sydney, Sydney, Australia
                [3 ]Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
                [4 ]Non-Communicable Diseases Research Centre, Tehran University of Medical Sciences, Tehran, Iran
                [5 ]Endocrinology and Metabolism Research Centre, Tehran University of Medical Sciences, Tehran, Iran
                [6 ]Effi-Stat, Paris, France
                [7 ]Department of Cardiology, Royal Brisbane and Women's Children Hospital and University of Queensland School of Medicine, Brisbane, Australia
                [8 ]Department of Epidemiology, Shahid Beheshti University of Medical Sciences, Tehran, Iran
                [9 ]The George Institute for Global Health, Hyderabad, India
                [10 ]Clinical Trials Service Unit, University of Oxford, Oxford, United Kingdom
                [11 ]National University of Singapore, Singapore
                [12 ]Hatter Institute for Cardiovascular Research in Africa, University of Cape Town, Cape Town, South Africa
                [13 ]Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
                [14 ]National Cardiovascular Centre University Indonesia, Jakarta, Indonesia
                [15 ]Universidad Nacional del Centro de la Provincia de Buenos Aires, Buenos Aires, Argentina
                [16 ]Centre Hospitalier Universitaire de Poitiers, Poitiers Cedex, France
                [17 ]Centre of Cardiovascular Research & Education in Therapeutics, Monash University, Melbourne, Australia
                [18 ]Bodleian Healthcare Libraries, University of Oxford, Oxford, United Kingdom
                [19 ]The George Institute for Global Health, Peking University, Beijing, China
                [20 ]University of Glasgow, Glasgow, United Kingdom
                Umeå Centre for Global Health Research, Umeå University, Sweden
                Author notes

                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.

                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.

                Article
                PMEDICINE-D-13-04109
                10.1371/journal.pmed.1001699
                4130667
                25117081
                23182e0a-fbad-4048-943c-e2b00bca585b
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 19 December 2013
                : 24 June 2014
                Page count
                Pages: 41
                Funding
                This work was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre Programme and NIHR Career Development Fellowship. KR and SM are supported by the Oxford Martin School and the George Institute for Global Health. The researchers conducted this study totally independently of the funding bodies. No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Cardiology
                Epidemiology
                Public and Occupational Health
                Global Health
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its Supporting Information files. Raw data extractions are available for sharing to other researchers upon request.

                Medicine
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