JOURNAL ARTICLE
META-ANALYSIS
REVIEW
SYSTEMATIC REVIEW
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The Health Systems Barriers and Facilitators for RHD Prevalence: An Epidemiological Meta-Analysis From Uganda and Tanzania.

Global Heart 2017 March
BACKGROUND: Rheumatic heart disease (RHD) is an important and preventable cause of cardiovascular disease.

OBJECTIVES: As part of a recent RHD initiative in Uganda and Tanzania, we systematically reviewed group A streptococcal disease (GAS), acute rheumatic fever (ARF), and RHD in these countries.

METHODS: Using a systematic review and meta-analysis/meta-synthesis, we searched PubMed, Embase, and grey literature for quantitative and qualitative studies conducted in Uganda and Tanzania that included individuals affected by GAS, ARF, and RHD. We pre-specified 3 sets of outcomes: 1) disease epidemiology; 2) barriers and facilitators to health care; and 3) stakeholder identification and engagement. Study descriptors, outcomes, and interest, and quality assessments were recorded. For the first objective, we conducted random-effects meta-analyses. For the second objective, we produced a narrative synthesis of themes. No studies contained data on the third objective.

RESULTS: Of 293 records identified, 12 met our inclusion criteria (9 for objective 1 and 3 for objective 2). Most quantitative studies were at moderate or high risk of bias, and only 1 of 2 qualitative studies was high quality. We estimated the prevalence of RHD to be 17.9 (95% confidence interval [CI]: 4.0 to 41.2) per 1,000 individuals. The most frequent nonfatal sequelae were heart failure, pulmonary hypertension, and atrial fibrillation. Case-fatality rates in medical and surgical wards were 17% (95% CI: 13% to 21%) and 27% (95% CI: 18% to 36%), respectively. Barriers and facilitators to GAS and RHD care were identified in the domains of individual knowledge, family support, provider communication and knowledge, and system design.

CONCLUSIONS: RHD remains endemic in Tanzania and Uganda, and symptomatic RHD is associated with high rates of morbidity and mortality. We have identified critical data gaps in the areas of GAS and ARF epidemiology as well as health care utilization patterns and their determinants.

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