Modelling study of the ability to diagnose acute rheumatic fever at different levels of the Ugandan healthcare system.

OBJECTIVE: To determine the ability to accurately diagnose acute rheumatic fever (ARF) given the resources available at three levels of the Ugandan healthcare system. METHODS: Using data obtained from a large epidemiological database on ARF conducted in three districts of Uganda, we selected variables that might positively or negatively predict rheumatic fever based on diagnostic capacity at three levels/tiers of the Ugandan healthcare system. Variables were put into three statistical models that were built sequentially. Multiple logistic regression was used to estimate ORs and 95% CI of predictors of ARF. Performance of the models was determined using Akaike information criterion, adjusted R2, concordance C statistic, Brier score and adequacy index. RESULTS: A model with clinical predictor variables available at a lower-level health centre (tier 1) predicted ARF with an optimism corrected area under the curve (AUC) (c-statistic) of 0.69. Adding tests available at the district level (tier 2, ECG, complete blood count and malaria testing) increased the AUC to 0.76. A model that additionally included diagnostic tests available at the national referral hospital (tier 3, echocardiography, anti-streptolysin O titres, erythrocyte sedimentation rate/C-reactive protein) had the best performance with an AUC of 0.91. CONCLUSIONS: Reducing the burden of rheumatic heart disease in low and middle-income countries requires overcoming challenges of ARF diagnosis. Ensuring that possible cases can be evaluated using electrocardiography and relatively simple blood tests will improve diagnostic accuracy somewhat, but access to echocardiography and tests to confirm recent streptococcal infection will have the greatest impact

Active case finding for rheumatic fever in an endemic country

Background: Despite the high burden of rheumatic heart disease in sub‐Saharan Africa, diagnosis with acute rheumatic fever (ARF) is exceedingly rare. Here, we report the results of the first prospective epidemiologic survey to diagnose and characterize ARF at the community level in Africa. Methods and Results: A cross‐sectional study was conducted in Lira, Uganda, to inform the design of a broader epidemiologic survey. Key messages were distributed in the community, and children aged 3 to 17 years were included if they had either (1) fever and joint pain, (2) suspicion of carditis, or (3) suspicion of chorea, with ARF diagnoses made by the 2015 Jones Criteria. Over 6 months, 201 children met criteria for participation, with a median age of 11 years (interquartile range, 6.5) and 103 (51%) female. At final diagnosis, 51 children (25%) had definite ARF, 11 (6%) had possible ARF, 2 (1%) had rheumatic heart disease without evidence of ARF, 78 (39%) had a known alternative diagnosis (10 influenza, 62 malaria, 2 sickle cell crises, 2 typhoid fever, 2 congenital heart disease), and 59 (30%) had an unknown alternative diagnosis. Conclusions: ARF persists within rheumatic heart disease–endemic communities in Africa, despite the low rates reported in the literature. Early data collection has enabled refinement of our study design to best capture the incidence of ARF and to answer important questions on community sensitization, healthcare worker and teacher education, and simplified diagnostics for low‐resource areas. This study also generated data to support further exploration of the relationship between malaria and ARF diagnosis in rheumatic heart disease/malaria‐endemic countries

Active Case Finding for Rheumatic Fever in an Endemic Country

Background: Despite the high burden of rheumatic heart disease in sub‐Saharan Africa, diagnosis with acute rheumatic fever (ARF) is exceedingly rare. Here, we report the results of the first prospective epidemiologic survey to diagnose and characterize ARF at the community level in Africa. Methods and Results: A cross‐sectional study was conducted in Lira, Uganda, to inform the design of a broader epidemiologic survey. Key messages were distributed in the community, and children aged 3 to 17 years were included if they had either (1) fever and joint pain, (2) suspicion of carditis, or (3) suspicion of chorea, with ARF diagnoses made by the 2015 Jones Criteria. Over 6 months, 201 children met criteria for participation, with a median age of 11 years (interquartile range, 6.5) and 103 (51%) female. At final diagnosis, 51 children (25%) had definite ARF, 11 (6%) had possible ARF, 2 (1%) had rheumatic heart disease without evidence of ARF, 78 (39%) had a known alternative diagnosis (10 influenza, 62 malaria, 2 sickle cell crises, 2 typhoid fever, 2 congenital heart disease), and 59 (30%) had an unknown alternative diagnosis. Conclusions: ARF persists within rheumatic heart disease–endemic communities in Africa, despite the low rates reported in the literature. Early data collection has enabled refinement of our study design to best capture the incidence of ARF and to answer important questions on community sensitization, healthcare worker and teacher education, and simplified diagnostics for low‐resource areas. This study also generated data to support further exploration of the relationship between malaria and ARF diagnosis in rheumatic heart disease/malaria‐endemic countries

Incidence of acute rheumatic fever in northern and western Uganda: a prospective, population-based study

Background Acute rheumatic fever is infrequently diagnosed in sub-Saharan African countries despite the high prevalence of rheumatic heart disease. We aimed to determine the incidence of acute rheumatic fever in northern and western Uganda. Methods For our prospective epidemiological study, we established acute rheumatic fever clinics at two regional hospitals in the north (Lira district) and west (Mbarara district) of Uganda and instituted a comprehensive acute rheumatic fever health messaging campaign. Communities and health-care workers were encouraged to refer children aged 3–17 years, with suspected acute rheumatic fever, for a definitive diagnosis using the Jones Criteria. Children were referred if they presented with any of the following: (1) history of fever within the past 48 h in combination with any joint complaint, (2) suspicion of acute rheumatic carditis, or (3) suspicion of chorea. We excluded children with a confirmed alternative diagnosis. We estimated incidence rates among children aged 5–14 years and characterised clinical features of definite and possible acute rheumatic fever cases. Findings Data were collected between Jan 17, 2018, and Dec 30, 2018, in Lira district and between June 5, 2019, and Feb 28, 2020, in Mbarara district. Of 1075 children referred for evaluation, 410 (38%) met the inclusion criteria; of these, 90 (22%) had definite acute rheumatic fever, 82 (20·0%) had possible acute rheumatic fever, and 24 (6%) had rheumatic heart disease without evidence of acute rheumatic fever. Additionally, 108 (26%) children had confirmed alternative diagnoses and 106 (26%) had an unknown alternative diagnosis. We estimated the incidence of definite acute rheumatic fever among children aged 5–14 years as 25 cases (95% CI 13·7–30·3) per 100 000 person-years in Lira district (north) and 13 cases (7·1–21·0) per 100 000 person-years in Mbarara district (west). Interpretation To the best of our knowledge, this is the first population-based study to estimate the incidence of acute rheumatic fever in sub-Saharan Africa. Given the known rheumatic heart disease burden, it is likely that only a proportion of children with acute rheumatic fever were diagnosed. These data dispel the long-held hypothesis that the condition does not exist in sub-Saharan Africa and compel investment in improving prevention, recognition, and diagnosis of acute rheumatic fever. Funding American Heart Association Children's Strategically Focused Research Network Grant, THRiVE-2, General Electric, and Cincinnati Children's Heart Institute Research Core