Outcomes of rheumatic fever in Uganda: a prospective cohort study.

BACKGROUND: Rheumatic heart disease is the largest contributor to cardiac-related mortality in children worldwide. Outcomes in endemic settings after its antecedent illness, acute rheumatic fever, are not well understood. We aimed to describe 3-5 year mortality, acute rheumatic fever recurrence, changes in carditis, and correlates of mortality after acute rheumatic fever. METHODS: We conducted a prospective cohort study of Ugandan patients aged 4-23 years who were diagnosed with definite acute rheumatic fever using the modified 2015 Jones criteria from July 1, 2017, to March 31, 2020, enrolled at three rheumatic heart disease registry sites in Uganda (in Mbarara, Mulago, or Lira), and followed up for at least 1 year after diagnosis. Patients with congenital heart disease were excluded. Patients underwent annual review, most recently in August, 2022. We calculated rates of mortality and acute rheumatic fever recurrence, tabulated changes in carditis, performed Kaplan-Meier survival analyses, and used Cox regression models to identify correlates of mortality. FINDINGS: Data were collected between Sept 1 and Sept 30, 2022. Of 182 patients diagnosed with definite acute rheumatic fever, 156 patients were included in the analysis. Of these 156 patients (77 [49%] male and 79 (51%) female; data on ethnicity not collected), 25 (16%) died, 21 (13%) had a cardiac-related death, and 17 (11%) had recurrent acute rheumatic fever over a median of 4·3 (IQR 3·0-4·8) years. 16 (24%) of the 25 deaths occurred within 1 year. Among 131 (84%) of 156 survivors, one had carditis progression by echo. Moderate-to-severe carditis (hazard ratio 12·7 [95% CI 3·9-40·9]) and prolonged PR interval (hazard ratio 4·4 [95% CI 1·7-11·2]) at acute rheumatic fever diagnosis were associated with increased cardiac-related mortality. INTERPRETATION: These are the first contemporary data from sub-Saharan Africa on medium-term acute rheumatic fever outcomes. Mortality rates exceeded those reported elsewhere. Most decedents already had chronic carditis at initial acute rheumatic fever diagnosis, suggesting previous undiagnosed episodes that had already compounded into rheumatic heart disease. Our data highlight the large burden of undetected acute rheumatic fever in these settings and the need for improved awareness of and diagnostics for acute rheumatic fever to allow earlier detection. FUNDING: Strauss Award at Cincinnati Children's Hospital, American Heart Association, and Wellcome Trust.

User-Centered Design to Develop Automated Short Message Service Messaging for Patient Support of Rheumatic Heart Disease Secondary Antibiotic Prophylaxis.

BACKGROUND: The Active Community Case Management Platform is a cloud-based technology developed to facilitate rheumatic heart disease case management by health care providers. This study aimed to design and pilot an automated short message service (SMS) intervention to support secondary prophylaxis adherence. METHODS AND RESULTS: We developed a concise library of messages to support secondary antibiotic prophylaxis. The SMS intervention used TextIT, an interface that enables users to send out interactive SMS messages at scale. The message bank was piloted in a cohort of 50 patients with rheumatic heart disease randomized into 2 groups. Group 1 received standard support (nurse-led/Active Community Case Management Platform). Group 2 received standard support plus SMS intervention for 2 months in the Lira and Gulu districts of Northern Uganda. We collected qualitative data on participants' experiences and assessed treatment adherence. Using a sequential user-centered process consisting of 4 phases (phases 1-4), we developed a message bank (n=43) deployed during our pilot study. There were no between-group differences in treatment adherence or acceptance. Interviews of participants indicated that the intervention was viewed positively. A total of 75% of SMS recipients responded to the messages, and 25% called the study staff to acknowledge receipt of text messages. CONCLUSIONS: This study has successfully developed a bank of SMS messages to support secondary antibiotic prophylaxis adherence. We have demonstrated the feasibility and acceptability of SMS technology in rheumatic heart disease care management. Future work will include integrating automated SMS into the Active Community Case Management Platform and a larger study of integrated SMS to reduce health care worker burden for patient support and improve adherence to secondary antibiotic prophylaxis.

Deployment of Point-of-Care Echocardiography to Improve Cardiac Diagnostic Access Among American Indians.

BACKGROUND: American Indians face significant barriers to diagnosis and management of cardiovascular disease. We sought to develop a real-world implementation model for improving access to echocardiography within the Indian Health Service, the American Indian Structural Heart Disease Partnership. METHODS AND RESULTS: The American Indian Structural Heart Disease Partnership was implemented and evaluated via a 4-step process of characterizing the system where it would be instituted, building point-of-care echocardiography capacity, deploying active case finding for structural heart disease, and evaluating the approach from the perspective of the clinician and patient. Data were collected and analyzed using a parallel convergent mixed methods approach. Twelve health care providers successfully completed training in point-of-care echocardiography. While there was perceived usefulness of echocardiography, providers found it difficult to integrate screening point-of-care echocardiography into their workday given competing demands. By the end of 12 months, 6 providers continued to actively utilize point-of-care echocardiography. Patients who participated in the study felt it was an acceptable and effective approach. They also identified access to transportation as a notable challenge to accessing echocardiograms. Over the 12-month period, a total of 639 patients were screened, of which 36 (5.6%) had a new clinically significant abnormal finding. CONCLUSIONS: The American Indian Structural Heart Disease Partnership model exhibited several promising strategies to improve access to screening echocardiography for American Indian populations. However, competing priorities for Indian Health Service providers' time limited the amount of integration of screening echocardiography into outpatient practice. Future endeavors should explore community-based solutions to develop a more sustainable model with greater impact on case detection, disease management, and improved outcomes.

Development and User Testing of a Dynamic Tool for Rheumatic Heart Disease Management.

OBJECTIVE: Most rheumatic heart disease (RHD) registries are static and centralized, collecting epidemiological and clinical data without providing tools to improve care. We developed a dynamic cloud-based RHD case management application with the goal of improving care for patients with RHD in Uganda. METHODS: The Active Community Case Management Tool (ACT) was designed to improve community-based case management for chronic disease, with RHD as the first test case. Global and local partner consultation informed selection of critical data fields and prioritization of application functionality. Multiple stages of review and revision culminated in user testing of the application at the Uganda Heart Institute. RESULTS: Global and local partners provided feedback of the application via survey and interview. The application was well received, and top considerations included avenues to import existing patient data, considering a minimum data entry form, and performing a situation assessment to tailor ACT to the health system setup for each new country. Test users completed a postuse survey. Responses were favorable regarding ease of use, desire to use the application in regular practice, and ability of the application to improve RHD care in Uganda. Concerns included appropriate technical skills and supports and potential disruption of workflow. CONCLUSION: Creating the ACT application was a dynamic process, incorporating iterative feedback from local and global partners. Results of the user testing will help refine and optimize the application. The ACT application showed potential for utility and integration into existing care models in Uganda.

Evaluating the implementation of a dynamic digital application to enable community-based decentralisation of rheumatic heart disease case management in Uganda: protocol for a hybrid type III effectiveness-implementation study.

INTRODUCTION: Rheumatic heart disease (RHD) affects over 39 million people worldwide, the majority in low-income and middle-income countries. Secondary antibiotic prophylaxis (SAP), given every 3-4 weeks can improve outcomes, provided more than 80% of doses are received. Poor adherence is strongly correlated with the distance travelled to receive prophylaxis. Decentralising RHD care has the potential to bridge these gaps and at least maintain or potentially increase RHD prophylaxis uptake. A package of implementation strategies was developed with the aim of reducing barriers to optimum SAP uptake. METHODS AND ANALYSIS: A hybrid implementation-effectiveness study type III was designed to evaluate the effectiveness of a package of implementation strategies including a digital, cloud-based application to support decentralised RHD care, integrated into the public healthcare system in Uganda. Our overarching hypothesis is that secondary prophylaxis adherence can be maintained or improved via a decentralisation strategy, compared with the centralised delivery strategy, by increasing retention in care. To evaluate this, eligible patients with RHD irrespective of their age enrolled at Lira and Gulu hospital registry sites will be consented for decentralised care at their nearest participating health centre. We estimated a sample size of 150-200 registrants. The primary outcome will be adherence to secondary prophylaxis while detailed implementation measures will be collected to understand barriers and facilitators to decentralisation, digital application tool adoption and ultimately its use and scale-up in the public healthcare system. ETHICS AND DISSEMINATION: This study was approved by the Institutional Review Board (IRB) at Cincinnati Children's Hospital Medical Center (IRB 2021-0160) and Makerere University School of Medicine Research Ethics Committee (Mak-SOMREC-2021-61). Participation will be voluntary and informed consent or assent (>8 but <18) will be obtained prior to participation. At completion, study findings will be communicated to the public, key stakeholders and submitted for publication.

The Use of Artificial Intelligence Guidance for Rheumatic Heart Disease Screening by Novices.

INTRODUCTION: A novel technology utilizing artificial intelligence (AI) to provide real-time image-acquisition guidance, enabling novices to obtain diagnostic echocardiographic images, holds promise to expand the reach of echo screening for rheumatic heart disease (RHD). We evaluated the ability of nonexperts to obtain diagnostic-quality images in patients with RHD using AI guidance with color Doppler. METHODS: Novice providers without prior ultrasound experience underwent a 1-day training curriculum to complete a 7-view screening protocol using AI guidance in Kampala, Uganda. All trainees then scanned 8 to 10 volunteer patients using AI guidance, half RHD and half normal. The same patients were scanned by 2 expert sonographers without the use of AI guidance. Images were evaluated by expert blinded cardiologists to assess (1) diagnostic quality to determine presence/absence of RHD and (2) valvular function and (3) to assign an American College of Emergency Physicians score of 1 to 5 for each view. RESULTS: Thirty-six novice participants scanned a total of 50 patients, resulting in a total of 462 echocardiogram studies, 362 obtained by nonexperts using AI guidance and 100 obtained by expert sonographers without AI guidance. Novice images enabled diagnostic interpretation in >90% of studies for presence/absence of RHD, abnormal MV morphology, and mitral regurgitation (vs 99% by experts, P ≤ .001). Images were less diagnostic for aortic valve disease (79% for aortic regurgitation, 50% for aortic stenosis, vs 99% and 91% by experts, P < .001). The American College of Emergency Physicians scores of nonexpert images were highest in the parasternal long-axis images (mean, 3.45; 81% ≥ 3) compared with lower scores for apical 4-chamber (mean, 3.20; 74% ≥ 3) and apical 5-chamber images (mean, 2.43; 38% ≥ 3). CONCLUSIONS: Artificial intelligence guidance with color Doppler is feasible to enable RHD screening by nonexperts, performing significantly better for assessment of the mitral than aortic valve. Further refinement is needed to optimize acquisition of color Doppler apical views.

Cardiovascular diseases in Africa in the twenty-first century: Gaps and priorities going forward.

In 2015, the United Nations set important targets to reduce premature cardiovascular disease (CVD) deaths by 33% by 2030. Africa disproportionately bears the brunt of CVD burden and has one of the highest risks of dying from non-communicable diseases (NCDs) worldwide. There is currently an epidemiological transition on the continent, where NCDs is projected to outpace communicable diseases within the current decade. Unchecked increases in CVD risk factors have contributed to the growing burden of three major CVDs-hypertension, cardiomyopathies, and atherosclerotic diseases- leading to devastating rates of stroke and heart failure. The highest age standardized disability-adjusted life years (DALYs) due to hypertensive heart disease (HHD) were recorded in Africa. The contributory causes of heart failure are changing-whilst HHD and cardiomyopathies still dominate, ischemic heart disease is rapidly becoming a significant contributor, whilst rheumatic heart disease (RHD) has shown a gradual decline. In a continent where health systems are traditionally geared toward addressing communicable diseases, several gaps exist to adequately meet the growing demand imposed by CVDs. Among these, high-quality research to inform interventions, underfunded health systems with high out-of-pocket costs, limited accessibility and affordability of essential medicines, CVD preventive services, and skill shortages. Overall, the African continent progress toward a third reduction in premature mortality come 2030 is lagging behind. More can be done in the arena of effective policy implementation for risk factor reduction and CVD prevention, increasing health financing and focusing on strengthening primary health care services for prevention and treatment of CVDs, whilst ensuring availability and affordability of quality medicines. Further, investing in systematic country data collection and research outputs will improve the accuracy of the burden of disease data and inform policy adoption on interventions. This review summarizes the current CVD burden, important gaps in cardiovascular medicine in Africa, and further highlights priority areas where efforts could be intensified in the next decade with potential to improve the current rate of progress toward achieving a 33% reduction in CVD mortality.

A genome-wide association study of plasma concentrations of warfarin enantiomers and metabolites in sub-Saharan black-African patients.

Diversity in pharmacogenomic studies is poor, especially in relation to the inclusion of black African patients. Lack of funding and difficulties in recruitment, together with the requirement for large sample sizes because of the extensive genetic diversity in Africa, are amongst the factors which have hampered pharmacogenomic studies in Africa. Warfarin is widely used in sub-Saharan Africa, but as in other populations, dosing is highly variable due to genetic and non-genetic factors. In order to identify genetic factors determining warfarin response variability, we have conducted a genome-wide association study (GWAS) of plasma concentrations of warfarin enantiomers/metabolites in sub-Saharan black-Africans. This overcomes the issue of non-adherence and may have greater sensitivity at genome-wide level, to identify pharmacokinetic gene variants than focusing on mean weekly dose, the usual end-point used in previous studies. Participants recruited at 12 outpatient sites in Uganda and South Africa on stable warfarin dose were genotyped using the Illumina Infinium H3Africa Consortium Array v2. Imputation was conducted using the 1,000 Genomes Project phase III reference panel. Warfarin/metabolite plasma concentrations were determined by high-performance liquid chromatography with tandem mass spectrometry. Multivariable linear regression was undertaken, with adjustment made for five non-genetic covariates and ten principal components of genetic ancestry. After quality control procedures, 548 participants and 17,268,054 SNPs were retained. CYP2C9*8, CYP2C9*9, CYP2C9*11, and the CYP2C cluster SNP rs12777823 passed the Bonferroni-adjusted replication significance threshold (p < 3.21E-04) for warfarin/metabolite ratios. In an exploratory GWAS analysis, 373 unique SNPs in 13 genes, including CYP2C9*8, passed the Bonferroni-adjusted genome-wide significance threshold (p < 3.846E-9), with 325 (87%, all located on chromosome 10) SNPs being associated with the S-warfarin/R-warfarin outcome (top SNP rs11188082, CYP2C19 intron variant, p = 1.55E-17). Approximately 69% of these SNPs were in linkage disequilibrium (r 2 > 0.8) with CYP2C9*8 (n = 216) and rs12777823 (n = 8). Using a pharmacokinetic approach, we have shown that variants other than CYP2C9*2 and CYP2C9*3 are more important in sub-Saharan black-Africans, mainly due to the allele frequencies. In exploratory work, we conducted the first warfarin pharmacokinetics-related GWAS in sub-Saharan Africans and identified novel SNPs that will require external replication and functional characterization before they can be considered for inclusion in warfarin dosing algorithms.

Stable warfarin dose prediction in sub-Saharan African patients: A machine-learning approach and external validation of a clinical dose-initiation algorithm.

Warfarin remains the most widely prescribed oral anticoagulant in sub-Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine-learning techniques in predicting stable warfarin dose in sub-Saharan Black-African patients and (b) externally validated a previously developed Warfarin Anticoagulation in Patients in Sub-Saharan Africa (War-PATH) clinical dose-initiation algorithm. The development cohort included 364 patients recruited from eight outpatient clinics and hospital departments in Uganda and South Africa (June 2018-July 2019). Validation was conducted using an external validation cohort (270 patients recruited from August 2019 to March 2020 in 12 outpatient clinics and hospital departments). Based on the mean absolute error (MAE; mean of absolute differences between the actual and predicted doses), random forest regression (12.07 mg/week; 95% confidence interval [CI], 10.39-13.76) was the best performing machine-learning technique in the external validation cohort, whereas the worst performing technique was model trees (17.59 mg/week; 95% CI, 15.75-19.43). By comparison, the simple, commonly used regression technique (ordinary least squares) performed similarly to more complex supervised machine-learning techniques and achieved an MAE of 13.01 mg/week (95% CI, 11.45-14.58). In summary, we have demonstrated that simpler regression techniques perform similarly to more complex supervised machine-learning techniques. We have also externally validated our previously developed clinical dose-initiation algorithm, which is being prospectively tested for clinical utility.