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1.
Glob Heart ; 19(1): 36, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38638125

RESUMO

Background: Health-related quality of life (HRQOL) is a critical issue for patients undergoing surgery for congenital heart disease (CHD) but has never been assessed in a low-income country. We conducted a cross-sectional mixed methods study with age-matched healthy siblings serving as controls at the Uganda Heart Institute. Methods: One-hundred fifteen CHD pediatric and young adult patients and sibling control participants were recruited. Health-related quality of life was assessed using the Pediatric Quality of Life Inventory Version 4.0 in participants ages 5-17 and 36-Item Short Form Survey for young adults aged 18-25. A subset of 27 participants completed face-to-face interviews to supplement quantitative findings. Results: Eighty-six pediatric (age 5-17) sibling and parent pairs completed Peds QOL surveys, and 29 young adult (age 18-25) sibling pairs completed SF-36 surveys. One third of patients had surgery in Uganda. Ventricular septal defects and tetralogy of Fallot were the most common diagnoses. Health-related quality of life scores in patients were lower across all domains compared to control participants in children. Reductions in physical and emotional domains of HRQOL were also statistically significant for young adults. Variables associated with lower HRQOL score on multivariate analysis in pediatric patients were younger age in the physical and emotional domains, greater number of surgeries in the physical domain and surgery outside Uganda in the school domain. The only predictor of lower HRQOL score in young adults was surgery outside Uganda in the social domain. Qualitative interviews identified a number of themes that correlated with survey results including abandonment by family, isolation from peers and community, financial hardship and social stigmatization. Conclusion: Health-related quality of life was lower in Ugandan patients after CHD surgery than siblings. Younger patients and those who had surgery outside of Uganda had lower HRQOL. These data have important implications for patients undergoing CHD surgery in LMIC and have potential to inform interventions.


Assuntos
Cardiopatias Congênitas , Qualidade de Vida , Humanos , Criança , Adulto Jovem , Adolescente , Adulto , Pré-Escolar , Qualidade de Vida/psicologia , Uganda/epidemiologia , Estudos Transversais , Cardiopatias Congênitas/cirurgia , Nível de Saúde , Inquéritos e Questionários
2.
J Am Soc Echocardiogr ; 36(7): 724-732, 2023 07.
Artigo em Inglês | MEDLINE | ID: mdl-36906047

RESUMO

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.


Assuntos
Insuficiência da Valva Mitral , Cardiopatia Reumática , Humanos , Cardiopatia Reumática/diagnóstico por imagem , Inteligência Artificial , Uganda , Programas de Rastreamento/métodos
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