Rheumatic Heart Disease Screening Research Articles

An 8-year single-centre experience of patients with subclinical rheumatic carditis.

Transthoracic echocardiography is the gold standard method for screening and confirmation of acute rheumatic fever and subclinical rheumatic heart disease. Secondary antibiotic prophylaxis that is regularly employed in subclinical rheumatic heart disease may help to reverse mild rheumatic carditis lesions, delay the progression of the disease, reduce morbidity and mortality, and improve patients' quality of life. We retrospectively evaluated the outcomes of 180 patients with subclinical rheumatic heart disease who were followed up for a mean of 4.92 ± 2.0 (3.5-6.5) years. Between 1 March 2015 and 31 December 2023, 180 patients diagnosed with subclinical rheumatic heart disease with a mean follow-up of 4.92 ± 2.0 (3.5-6.5) years were included in the study. Of the patients, 50.6% were male, 49.4% were female, mean age at diagnosis was 11.74 ± 3.18 (9.68-13.65) years, and mean follow-up period was 4.92 ± 2.0 (3.5-6.5) years. Further, 87.2 % of the patients had mitral valve regurgitation, 38.3% had aortic valve regurgitation, and 27.2% had both valve (aortic and mitral valve) regurgitation. Moreover, Sydenham chorea was also diagnosed in 7.8% the patients. Of the patients, 90% had mild rheumatic heart disease, 7.8% had moderate rheumatic heart disease, and 2.2% had severe rheumatic heart disease. After the diagnosis of rheumatic heart disease, 76.7% patients received regular and 23.3% irregular secondary benzathine penicillin G prophylaxis. We believe that echocardiography demonstrates its efficacy and safety profile in reducing the risk of rheumatic heart disease in patients diagnosed with subclinical rheumatic carditis and complying with regular secondary antibiotic prophylaxis.

Acute rheumatic fever and rheumatic heart disease: updates in diagnosis and treatment.

To summarize the latest developments in rheumatic fever and rheumatic heart disease (RHD) prevention, (early) diagnosis, and treatment. The revised Jones criteria have demonstrated increased sensitivity and specificity for rheumatic fever diagnosis in high-risk populations. The management of rheumatic fever remains symptom-based, with no treatment options proven to alter the disease course or prevent chronic RHD. The revised World Heart Federation (WHF) guidelines for the echocardiographic diagnosis of RHD encourage task-shifting of RHD screening, extending reach in endemic regions. These guidelines also present an A-D classification of RHD and provide recommendations for the management of early disease. Integrated models for RHD screening within existing health structures are emerging and automated intelligence is showing potential to support RHD screening and diagnosis. Innovative strategies to foster adherence and equitable access to secondary prophylaxis, such as re-examination of the efficacy of oral penicillin, trials of longer acting penicillin formulations and implants are underway. There is renewed interest and investment in a well tolerated and effective GAS vaccine. We are living in a time of possibility with global acceleration to address the prevailing burden of RHD. Together, we can ensure that RHD does not once again fall off the global health agenda, until equitable elimination has been achieved.

Handheld echocardiography for the screening and diagnosis of rheumatic heart disease: a systematic review to inform WHO guidelines

Early detection and diagnosis of acute rheumatic fever and rheumatic heart disease are key to preventing progression, and echocardiography has an important diagnostic role. Standard echocardiography might not be feasible in high-prevalence regions due to its high cost, complexity, and time requirement. Handheld echocardiography might be an easy-to-use, low-cost alternative, but its performance in screening for and diagnosing acute rheumatic fever and rheumatic heart disease needs further investigation. In this systematic review and meta-analysis, we searched Embase, MEDLINE, LILACS, and Conference Proceedings Citation Index-Science up to Feb 9, 2024, for studies on the screening and diagnosis of acute rheumatic fever and rheumatic heart disease using handheld echocardiography (index test) or standard echocardiography or auscultation (reference tests) in high-prevalence areas. We included all studies with useable data in which the diagnostic performance of the index test was assessed against a reference test. Data on test accuracy in diagnosing rheumatic heart disease, acute rheumatic fever, or carditis with acute rheumatic fever (primary outcomes) were extracted from published articles or calculated, with authors contacted as necessary. Quality of evidence was appraised using GRADE and QUADAS-2 criteria. We summarised diagnostic accuracy statistics (including sensitivity and specificity) and estimated 95% CIs using a bivariate random-effects model (or univariate random-effects models for analyses including three or fewer studies). Area under the curve (AUC) was calculated from summary receiver operating characteristic curves. Heterogeneity was assessed by visual inspection of plots. This study was registered with PROSPERO (CRD42022344081). Out of 4868 records we identified 11 studies, and two additional reports, comprising 15 578 unique participants. Pooled data showed that handheld echocardiography had high sensitivity (0·87 [95% CI 0·76-0·93]), specificity (0·98 [0·71-1·00]), and overall high accuracy (AUC 0·94 [0·84-1·00]) for diagnosing rheumatic heart disease when compared with standard echocardiography (two studies; moderate certainty of evidence), with better performance for diagnosing definite compared with borderline rheumatic heart disease. High sensitivity (0·79 [0·73-0·84]), specificity (0·85 [0·80-0·89]), and overall accuracy (AUC 0·90 [0·85-0·94]) for screening rheumatic heart disease was observed when pooling data of handheld echocardiography versus standard echocardiography (seven studies; high certainty of evidence). Most studies had a low risk of bias overall. Some heterogeneity was observed for sensitivity and specificity across studies, possibly driven by differences in the prevalence and severity of rheumatic heart disease, and level of training or expertise of non-expert operators. Handheld echocardiography has a high accuracy and diagnostic performance when compared with standard echocardiography for diagnosing and screening of rheumatic heart disease in high-prevalence areas. World Health Organization. For the Chinese, French, Italian, Persian, Portuguese, Spanish and Urdu translations of the abstract see Supplementary Materials section.

Agreement between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren from High-Prevalence Settings (Agreement between Screening and Standard Echo for RHD).

Introduction: Handheld echocardiography (echo) is the tool of choice for rheumatic heart disease (RHD) screening. We aimed to assess the agreement between screening and standard echo for latent RHD diagnosis in schoolchildren from an endemic setting. Methods: Over 14 months, 3 nonphysicians used handheld machines and the 2012 WHF Criteria to determine RHD prevalence in consented schoolchildren from Brazilian low-income public schools. Studies were interpreted by telemedicine by 3 experts (Brazil, US). RHD-positive children (borderline/definite) and those with congenital heart disease (CHD) were referred for standard echo, acquired and interpreted by a cardiologist. Agreement between screening and standard echo, by WHF subgroups, was assessed. Results: 1390 students were screened in 6 schools, with 110 (7.9%, 95% CI 6.5-9.5) being screen positive (14 ± 2 years, 72% women). Among 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline, and 1 to normal. Among 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) reclassified as definite RHD, and 2 had mild CHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criterion was B (isolated mitral regurgitation, 64%), followed by A (2 mitral valve morphological features, 31%). In 1 patient with definite RHD reclassified to normal, the WHF criterion was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3-4.2). Conclusions: Although practical, RHD screening with handheld devices tends to overestimate prevalence.

Using Artificial Intelligence for Rheumatic Heart Disease Detection by Echocardiography: Focus on Mitral Regurgitation.

Identification of children with latent rheumatic heart disease (RHD) by echocardiography, before onset of symptoms, provides an opportunity to initiate secondary prophylaxis and prevent disease progression. There have been limited artificial intelligence studies published assessing the potential of machine learning to detect and analyze mitral regurgitation or to detect the presence of RHD on standard portable echocardiograms. We used 511 echocardiograms in children, focusing on color Doppler images of the mitral valve. Echocardiograms were independently reviewed by an expert adjudication panel. Among 511 cases, 229 were normal, and 282 had RHD. Our automated method included harmonization of echocardiograms to localize the left atrium during systole using convolutional neural networks and RHD detection using mitral regurgitation jet analysis and deep learning models with an attention mechanism. We identified the correct view with an average accuracy of 0.99 and the correct systolic frame with an average accuracy of 0.94 (apical) and 0.93 (parasternal long axis). It localized the left atrium with an average Dice coefficient of 0.88 (apical) and 0.9 (parasternal long axis). Maximum mitral regurgitation jet measurements were similar to expert manual measurements (P value=0.83) and a 9-feature mitral regurgitation analysis showed an area under the receiver operating characteristics curve of 0.93, precision of 0.83, recall of 0.92, and F1 score of 0.87. Our deep learning model showed an area under the receiver operating characteristics curve of 0.84, precision of 0.78, recall of 0.98, and F1 score of 0.87. Artificial intelligence has the potential to detect RHD as accurately as expert cardiologists and to improve with more data. These innovative approaches hold promise to scale echocardiography screening for RHD.

Echocardiographic Screening of Rheumatic Heart Disease: Current Concepts and Challenges.

The incidence of acute rheumatic fever (ARF), which most commonly affects children aged 5-15 years after group A Streptococcus (GAS) infection, ranges from 8 to 51 per 100 000 people worldwide. Rheumatic heart disease (RHD), which occurs when patients with ARF are inappropriately treated or not given regular prophylaxis, is the most common cause of non-congenital heart disease in children and young adults in low-income countries. Timely treatment of GAS infection can prevent ARF, and penicillin prophylaxis can prevent recurrence of ARF. Secondary prophylaxis with benzathine penicillin G has been shown to decrease the incidence of RHD and is a key aspect of RHD control. The most important factor determining the prognosis of RHD is the severity of cardiac involvement. Although approximately 70% of patients with carditis in the acute phase of the disease recover without sequelae, carditis is important because it is the only complication of ARF that causes sequelae. One-third of patients with ARF are asymptomatic. Patients with mild symptoms of recurrent ARF and silent RHD will develop severe morbidities within 5-10 years if they do not receive secondary preventive treatments. A new screening program should be established to prevent cardiac morbidities of ARF in moderate- and highrisk populations. In the present study, we examined the applicability of echocardiographic screening programs for RHD. Cite this article as: Topçu S, Uçar T. Echocardiographic screening of rheumatic heart disease: Current concepts and challenges. Turk Arch Pediatr. 2024;59(1):3-12.

The role of echocardiographic screening in reducing the burden of rheumatic heart disease in Latin America.

The objectives of this article are to reflect on the rationale behind the use of echocardiographic screening for rheumatic heart disease and to provide key recommendations about steps needed to implement and improve echocardiographic screening programs in Latin America. Rheumatic heart disease remains a public health problem affecting mainly low-income and lower-middle-income countries and populations. Latin America is an area with economic inequalities, and the epidemiology of rheumatic heart disease remains largely unknown. Echocardiographic screening is useful for updating the epidemiology and providing early diagnosis of the disease. We discuss different approaches used in successful echocardiographic screening programs worldwide and in Latin America. We then identify the key elements needed to establish successful echocardiographic screening programs in Latin America, including increased awareness and involvement from multiple sectors (e.g. the community, health care professionals, scientific organizations and public health entities), identification of areas in need, development of a plan and structure that include different screening approaches, and how to ensure appropriate follow up for those who screen positive.

The Impact of a Handheld Ultrasound Device in a Rheumatic Heart Disease Screening Program in Ethiopia

Background: Rheumatic heart disease affects 33 million people in low and middle income countries and is the leading cause of cardiovascular death among children and young adults. Penicillin prophylaxis prevents progression in asymptomatic disease. Efforts to expand echocardiographic screening are focusing on simplified protocols, non-physician ultrasonographers, and portable ultrasound devices, including handheld ultrasound. Recent advances support the use of single-view screening protocols. With the increasing availability and low cost of handheld devices, studies are needed to evaluate their performance in these settings.
 Methods: We conducted a retrospective study comparing the rate of screen positive ultrasounds before and after the use of a handheld ultrasound in an RHD screening program in Ethiopia. We also performed a cross-sectional device comparison in 19 at-risk school-children participating in the rheumatic heart disease screening program.
 Results: Between March of 2019 and Jan of 2022, 6631 children were screened for rheumatic heart disease of whom 4029 were screened after the introduction of a handheld device. Before the use of the handheld ultrasound device 291 (11.2%) children had a screen positive ultrasounds compared with 167 (4.1%) afterwards (p < 0.001). We also compared non-expert to expert interpretation by device and found a significant difference in interpretation for the Lumify (p=0.025). There was a trend towards shorter jet length by color Doppler in the handheld ultrasound device for both expert and non-expert review. 
 Conclusions: Our study highlights that the screen-positive rate in a RHD screening program is influenced by the device being used in the screening process.

Leveraging School Health Programs in Africa: Integrated Screening for Rheumatic Heart Disease and Dental Caries.

Rheumatic heart disease (RHD) and dental caries (DC) disproportionately affect children and young adults in sub-Saharan countries, with major impact on schoolchildren's health and education. DC in children with RHD constitutes an important risk for fatal complications. Our study aimed at assessing the feasibility of simultaneous RHD and DC screening in school environment. March 20-24, 2022, we performed an observational descriptive study of schoolchildren in a public school in Maputo City, Mozambique. RHD screening involved two stages: first, a physical examination (including cardiac auscultation and direct observation of the oral cavity), and second, an abbreviated echocardiography performed by a cardiologist. Rapid testing for group A Streptococcus (GAS) was done to every eighth child in the classroom and for those with signs suggesting recent infection, in accordance with the study protocol developed for screening. A multidisciplinary team collected the data. Data were analyzed using descriptive statistics. A total of 954 students (median age 9; range 6-15) were screened. One hundred and twenty-five participants were eligible for a rapid antigen test, of which 6 (4.8%) tested positive. On clinical evaluation 52 children (5.3%) presented a heart murmur. Echocardiography on 362 children showed borderline RHD in 35 children and definite RHD in 2 (0.6%); 1 child had a ventricular septal defect. Dental cavities were present in 444 (48.4%), despite 904 out of 917 students reporting brushing of their teeth once to three times daily (98.6%). School-based integrated oral and cardiovascular screenings and use of rapid tests for GAS carriage provide crucial information to create customized preventive strategies for rheumatic fever (RF) and RHD in low- and middle-income countries (LMICs), in addition to detecting children at very high risk of bacterial endocarditis. The sustainability of such interventions and acceptability by health providers needs to be assessed.

Abstract 14701: Agreement Between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren From High-Prevalence Settings

Background: Handheld echocardiography (echo) is the tool of choice for Rheumatic Heart Disease (RHD) screening, based on the 2012 World Heart Federation (WHF) Criteria. We aimed to assess the agreement between screening and standard echo for diagnosis of latent RHD in schoolchildren from an endemic setting. Methods: Over 14 months, 3 non-physicians used handheld machines (GE, VSCAN) and the 2012 WHF Criteria to determine RHD prevalence in low-income public schools in Minas Gerais, Southeast Brazil. Consented children were eligible for participation. Studies were interpreted remotely using a telemedicine cloud-server by 2 experts in Brazil and the US. RHD-positive children (borderline and definite) and those with congenital heart disease (CHD) were referred for standard echo with portable devices (GE, Vivid IQ), with acquisition and interpretation by an expert cardiologist. Agreement between screening and standard echo, by category and according to the WHD criteria, was assessed, and the kappa statistic was applied. Results: A total of 1,390 students were screened in 6 schools and, among these, 110 (7.9%, 95% CI 6.5 - 9.5) were screen-positive and referred for standard echo, with mean age of 14±2 years, 80 (72%) women. Among the 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline and 1 to normal. Among the 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) to definite RHD and 2 had mild CHD. Among 11 children with CHD in screening, 4 were confirmed, 5 were reclassified to normal and 2 to RHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criteria was B (isolated mitral regurgitation): 64%, followed by A (2 morphological features of the mitral valve): 31%. In the only patient with definite RHD reclassified to normal, WHF criteria was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3 - 4.2). Conclusions: Although practical, RHD screening with handheld devices tend to overestimate prevalence. Even in endemic settings, continuous education for detection, and application of risk stratification for management are crucial.

Abstract 14599: A Pilot Rheumatic Heart Disease Screening Program Using Portable, Handheld Echocardiography in Rivas, Nicaragua

Introduction: Portable, handheld echocardiography offers several advantages for rheumatic heart disease (RHD) screening in low-resource settings. Analyses of focused protocols using handheld echocardiography have yielded acceptable sensitivity and specificity for diagnosis of RHD, including in those performed by non-expert sonographers. Previous studies estimate high burden of RHD in Nicaragua. We conducted a pilot community-based RHD screening program using handheld echocardiography in Rivas, Nicaragua using contemporary RHD diagnostic criteria. Methods: Non-expert sonographers were trained using the GE Vscan Extend TM device and a simplified version of the 2012 World Heart Federation criteria for diagnosis of RHD. Referral criteria for complete echocardiogram included the presence of a mitral regurgitant jet of > 2.0 cm, aortic regurgitant jet > 1.0 cm, or any morphologic abnormality of the mitral or aortic valve, as well as left ventricular dysfunction or significant congenital heart disease. Participants were recruited by convenience-based sampling in communities throughout Rivas, Nicaragua. Participants were notified at the point-of-care of need for complete echocardiogram. All studies were overread asynchronously by expert readers for diagnostic accuracy. Results: Between March 2022 and April 2023, 494 screening echocardiographic studies were performed and evaluated for diagnostic accuracy. The median age was 36.3 years (IQR 19.2, 56.2), 22% of participants were <18 years of age, and 60% of participants were female. There were 17.6% of participants referred for complete echocardiogram at the point-of-care compared with 13.0% meeting referral criteria on expert review. Negative and positive predictive values for non-expert vs. expert assessment were 92.4% and 62.1%, respectively. Cohen’s kappa for inter-rater reliability was 0.338, suggesting fair agreement. Conclusions: This pilot program demonstrated the feasibility of a screening program for RHD in rural Nicaragua with non-expert sonographers. Lessons from this program are intended to inform future epidemiological studies to determine the population prevalence and longitudinal outcomes of RHD in this region.

Abstract 16681: Echocardiogram-Based Screening and Prevalence of Rheumatic Heart Disease in Children and Adolescents From Endemic Areas: A Systematic Review and Updated Meta-Analysis

Background: Rheumatic heart disease (RHD) is the leading cause of cardiac death in children, posing a significant burden to health systems, particularly in developing countries. Echocardiogram is a sensitive tool to identify early RHD patients, who may benefit from secondary prevention. Therefore, we performed an updated meta-analysis to determine the prevalence of latent RHD using echocardiogram-based screening performed in endemic regions across the globe. Methods: PubMed, Embase, Cochrane, and Lilacs databases were searched for cross-sectional studies reporting the prevalence of RHD in individuals aged 5-20 years, through echocardiogram-based screening programs in endemic areas. Studies with screening based on auscultation were excluded. Echocardiography-detected RHD was considered as borderline or definite by World Heart Federation (WHF) criteria and possible, probable or definite by World Heart Organization (WHO) criteria. We used random-effects models to assess the prevalence of RHD according to the geographic distribution. Results: A total of 57 studies were included, with a total of 224,100 screened subjects. WHF criteria for RHD echocardiographic diagnosis were used in 46 studies, WHO criteria in 6, and others in 3. The overall prevalence of echocardiography detected RHD was 23 per 1,000 individuals (95% CI 18 to 29 per 1,000), with a pooled prevalence of definitive RHD of 9 per 1,000 individuals (95% CI 7 to 12 per 1,000). Analysis of the prevalence of echocardiography detected RHD in different continents yielded an overall prevalence of 21 per 1,000 (95% CI 14 to 31 per 1,000) in Africa, 28 per 1,000 (95% CI 18 to 42 per 1,000) in Oceania, 21 per 1,000 (95% CI 15 to 30 per 1,000) in Asia, and 22 per 1,000 (95% CI 6 to 76 per 1,000) in Latin America. Conclusion: Screening programs incorporating echocardiography found a significant prevalence of RHD, in the range of 20 to 30 per 1,000 children and adolescents screened in endemic areas across different continents.

Early-warning of Cardiac Condition through Detection of Murmur in Heart Sound - A Case Study.

Cardiovascular disease, particularly Rheumatic Heart Disease (RHD), is one of the leading causes of death in many developing countries. RHD is manageable and treatable with early detection. However, multiple countries across the globe suffer from a scarcity of experienced physicians who can perform screening at large scales. Advancements in machine learning and signal processing have paved way for Phonocardiogram (PCG)-based automatic heart sound classification. The direct implication of such methods is that it is possible to enable a person without specialized training to detect potential cardiac conditions with just a digital stethoscope. Hospitalization or life-threatening situations can be dramatically reduced via such early screenings. Towards this, we conducted a case study amongst a population from a particular geography using machine learning and deep learning methods for the detection of murmur in heart sounds. The methodology consists of first pre-processing and identifying normal vs. abnormal heart sound signals using 3 state-of-the-art methods. The second step further identifies the murmur to be systolic or diastolic by capturing the auscultation location. Abnormal findings are then sent for early attention of clinicians for proper diagnosis. The case study investigates the efficacy of the automated method employed for early screening of potential RHD and initial encouraging results of the study are presented.

Abbreviated Echocardiographic Screening for Rheumatic Heart Disease by Non-Experts: A Diagnostic Accuracy Study of Two Approaches

Abbreviated Echocardiographic Screening for Rheumatic Heart Disease by Non-Experts: A Diagnostic Accuracy Study of Two Approaches

Morpho-mechanistic screening criteria for the echocardiographic detection of rheumatic heart disease

IntroductionScreening echocardiography, guided by the current World Heart Federation (WHF) criteria, has important limitations that impede the establishment of large-scale rheumatic heart disease (RHD) control programmes in endemic regions. The...

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

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. 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. 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). 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.

Abbreviated Echocardiographic Screening for Rheumatic Heart Disease by Nonexperts with and without Offsite Expert Review: A Diagnostic Accuracy Study

Early detection of rheumatic heart disease (RHD) through echocardiographic screening can facilitate early access to effective treatment, which reduces the risk for progression. Accurate, feasible approaches to echocardiographic screening that can be incorporated into routine health services are needed. The authors hypothesized that offsite expert review could improve the diagnostic accuracy of nonexpert-obtained echocardiographic images. This prospective cross-sectional study was performed to evaluate the diagnostic accuracy of health worker-conducted single parasternal long-axis view with a sweep of the heart using hand-carried ultrasound for the detection of RHD in high-risk populations in Timor-Leste and Australia. In the primary analysis, the presence of any mitral or aortic regurgitation met the criteria for a positive screening result. Sensitivity and specificity were calculated for a screen-and-refer approach based on nonexpert practitioner assessment (approach 1) and for an approach using offsite expert review of nonexpert practitioner-obtained images to decide onward referral (approach 2). Each participant had a reference test performed by an expert echocardiographer on the same day as the index test. Diagnosis of RHD was determined by a panel of three experts, using 2012 World Heart Federation criteria. The prevalence of borderline or definite RHD among 3,329 participants was 4.0% (95% CI, 3.4%-4.7%). The sensitivity of approach 1 for borderline or definite RHD was 86.5% (95% CI, 79.5%-91.8%), and the specificity was 61.4% (95% CI, 59.7%-63.1%). Approach 2 achieved similar sensitivity (88.4%; 95% CI, 81.5%-93.3%) and improved specificity (77.1%; 95% CI, 75.6%-78.6%). Nonexpert practitioner-obtained single parasternal long-axis view with a sweep of the heart images, reviewed by an offsite expert, can detect borderline and definite RHD on screening with reasonable sensitivity and specificity. Brief training of nonexpert practitioners with ongoing support could be used as an effective strategy for scaling up echocardiographic screening for RHD in high-risk settings.

Handheld echocardiographic screening for rheumatic heart disease by non-experts in rural South Kordofan, Sudan: Supporting task shifting for control of a serious disease

BackgroundRheumatic heart disease (RHD) is a major and preventable cause of cardiac morbidity in Sudan. It can be detected early with a handheld echocardiography (HHE) machine. Our study aimed to screen for RHD in rural South Kordofan and to investigate the ability of non-experts to obtain good quality HHE records. MethodsA cross-sectional study was conducted in South Kordofan, Sudan. A team of non-experts was trained for two weeks on handheld echocardiographic screening for RHD using a simplified protocol. Cases were recorded and reviewed by a pediatric cardiologist. Demographic and clinical features of screened subjects were studied. Descriptive statistics were presented as “number (%)” or “mean ± SD”. RHD frequency was expressed as cases per 1000, and the Chi-Square test/Fisher's Exact test was used to compare RHD findings between different groups. ResultsA total of 467 subjects were screened. Echocardiographic quality was acceptable in 93% of recorded studies, hence 452 cases were included in the analysis. The disease frequency was found to be 50 per 1000. Out of 452 screened subjects (age 10–25 years), 23 were found to have RHD. The disease was mild in 70% and moderate or involving two valves in 30% of patients. Risk factors for the disease included the father's occupation and the village of residence. ConclusionShortly trained non-expert medicals can assist in RHD surveillance in remote areas using HHE for early detection and management. South Kordofan state is highly endemic to RHD and a control program needs to be implemented.

Abstract 15026: 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 (echo) images holds promise to expand the reach of echo screening for rheumatic heart disease (RHD). We evaluated the ability of non-experts to obtain diagnostic quality images in patients with RHD using AI guidance (Caption Health) with color Doppler. Methods: This study was performed in Kampala, Uganda at the Uganda Heart Institute. Nurses and nursing students with no prior echo experience underwent one-day training in the use of AI guidance, which included a 7-view screening protocol with 2D and color Doppler images. Following training, all participants scanned 8-10 patients using AI guidance, half RHD and half normal. The same patients were scanned by two expert sonographers without the use of AI guidance. Each echo was evaluated by a panel of 4 expert echocardiographers blinded to the identity of the scanner (novice/exert) and diagnosis of the patient to provide quality assessment including (1) diagnostic quality to determine presence/absence of RHD, (2) more detailed valvular assessment, and (3) ACEP score 1-5 for each view. Results: Thirty-six novice scanners scanned a total of 50 patients, 25 with RHD and 25 controls. A total of 462 echocardiogram studies were obtained, 351 obtained by non-experts using AI guidance and 111 obtained by expert sonographers without AI guidance. Preliminary analysis of 394 interpretations showed that 95% of non-expert studies were of diagnostic quality to assess for RHD and mitral valve disease (vs 100% by experts, p=0.03), but only 56% of non-expert studies were of diagnostic quality to assess aortic valve disease (vs 97% by experts, p&lt;0.0001). The ACEP scores of non-expert images were highest in the parasternal long axis images (mean 3.62, 84% ≥ 3) compared to lower scores for apical 4 (mean 3.28, 73% ≥3), and apical 5 images (mean 2.52, 46% ≥ 3). Conclusions: AI guidance with color Doppler is feasible to enable rheumatic heart disease screening by non-experts, performing significantly better for assessment of the mitral than aortic valve. Further refinement is needed to optimize acquisition of color Doppler apical views.

Abstract 12284: Utilizing Automated Machine Learning for Rheumatic Heart Disease Detection in Doppler Echocardiography

Introduction: Rheumatic heart disease (RHD) is the number one cause globally of morbidity and mortality from heart disease in children and young adults. The mitral regurgitation (MR) jet length on color Doppler echocardiography is an important index for diagnosis, but its measurement and interpretation vary. Objective: Develop an automatic machine learning approach to identify and measure the MR jet length on color Doppler for RHD detection. Methods: We used 316 echocardiograms from 95 children (mean age 12±2 years; range 5 to 17 years) with DICOM color Doppler images of the mitral valve taken from parasternal long axis (PLAX) and apical 4 chamber (AP4) views. All echocardiograms were independently reviewed by an adjudication panel consisting of four expert pediatric cardiologists to determine maximum MR jet length and diagnosis (RHD or normal). Among 95 cases, 29 were normal and 66 had RHD. Our automated method included. (1) Selection of frames during ventricular systole using a convolutional neural network architecture. (2) Localization of left atrium using convolutional neural networks with LinkNet structure. (3) Measurement of MR jet length by image color analysis. (4) Detection of RHD by applying a generalized regression model based on the maximum MR jet length measured and maximizing the balanced accuracy using cross validation. Results: Machine learning selected the correct systolic frame with an average accuracy of 0.95 (sensitivity 97%/specificity 93%) and 0.94 (sensitivity 94%/specificity 94%) for the AP4 and PLAX view, respectively. It localized the atrium with an average Dice coefficient of 0.89 and 0.9 for the AP4 and PLAX view, respectively. We estimated the MR jet length with an average absolute error of 0.33±0.4 cm (p-value = 0.15 compared to manual measurements). Our deep learning approach performed similar to or better than previously published manual methods for categorization of RHD positive vs negative. The accuracy of RHD detection was 0.84 (sensitivity 86%/specificity 79%). Conclusions: Our automatic method has the potential to reliably detect RHD as accurately as expert cardiologists. This innovative approach holds promise to scale echocardiography screening for RHD and expand prophylaxis to prevent progression of RHD globally.