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Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies

OBJECTIVES: We developed a questionnaire-based risk-scoring system to identify children at risk for rheumatic heart disease (RHD) in rural India. The resulting predictive model was validated in Nepal, in a population with a similar demographic profile to rural India. METHODS: The study involved 8646...

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Autores principales: Ray, Madhab, Guha, Santanu, Dhungana, Ranga Raj, Karak, Avik, Choudhury, Basabendra, Ray, Bipasha, Zubair, Haroon, Ray, Meghna, Sengupta, Srijan, Bhatt, Deepak L., Goldberg, Robert J., Selker, Harry P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10344801/
https://www.ncbi.nlm.nih.gov/pubmed/37455788
http://dx.doi.org/10.1016/j.ijcrp.2023.200195
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author Ray, Madhab
Guha, Santanu
Dhungana, Ranga Raj
Karak, Avik
Choudhury, Basabendra
Ray, Bipasha
Zubair, Haroon
Ray, Meghna
Sengupta, Srijan
Bhatt, Deepak L.
Goldberg, Robert J.
Selker, Harry P.
author_facet Ray, Madhab
Guha, Santanu
Dhungana, Ranga Raj
Karak, Avik
Choudhury, Basabendra
Ray, Bipasha
Zubair, Haroon
Ray, Meghna
Sengupta, Srijan
Bhatt, Deepak L.
Goldberg, Robert J.
Selker, Harry P.
author_sort Ray, Madhab
collection PubMed
description OBJECTIVES: We developed a questionnaire-based risk-scoring system to identify children at risk for rheumatic heart disease (RHD) in rural India. The resulting predictive model was validated in Nepal, in a population with a similar demographic profile to rural India. METHODS: The study involved 8646 students (mean age 13.0 years, 46% boys) from 20 middle and high schools in the West Midnapore district of India. The survey asked questions about the presence of different signs and symptoms of RHD. Students with possible RHD who experienced sore throat and joint pain were offered an echocardiogram to screen for RHD. Their findings were compared with randomly selected students without these symptoms. The data were analyzed to develop a predictive model for identifying RHD. RESULTS: Based on our univariate analyses, seven variables were used for building a predictive model. A four-variable model (joint pain plus sore throat, female sex, shortness of breath, and palpitations) best predicted the risk of RHD with a C-statistic of 0.854. A six-point scoring system developed from the model was validated among similarly aged children in Nepal. CONCLUSIONS: A simple questionnaire-based predictive instrument could identify children at higher risk for this disease in low-income countries where RHD remains prevalent. Echocardiography could then be used in these high-risk children to detect RHD in its early stages. This may support a strategy for more effective secondary prophylaxis of RHD.
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spelling pubmed-103448012023-07-15 Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies Ray, Madhab Guha, Santanu Dhungana, Ranga Raj Karak, Avik Choudhury, Basabendra Ray, Bipasha Zubair, Haroon Ray, Meghna Sengupta, Srijan Bhatt, Deepak L. Goldberg, Robert J. Selker, Harry P. Int J Cardiol Cardiovasc Risk Prev Research Paper OBJECTIVES: We developed a questionnaire-based risk-scoring system to identify children at risk for rheumatic heart disease (RHD) in rural India. The resulting predictive model was validated in Nepal, in a population with a similar demographic profile to rural India. METHODS: The study involved 8646 students (mean age 13.0 years, 46% boys) from 20 middle and high schools in the West Midnapore district of India. The survey asked questions about the presence of different signs and symptoms of RHD. Students with possible RHD who experienced sore throat and joint pain were offered an echocardiogram to screen for RHD. Their findings were compared with randomly selected students without these symptoms. The data were analyzed to develop a predictive model for identifying RHD. RESULTS: Based on our univariate analyses, seven variables were used for building a predictive model. A four-variable model (joint pain plus sore throat, female sex, shortness of breath, and palpitations) best predicted the risk of RHD with a C-statistic of 0.854. A six-point scoring system developed from the model was validated among similarly aged children in Nepal. CONCLUSIONS: A simple questionnaire-based predictive instrument could identify children at higher risk for this disease in low-income countries where RHD remains prevalent. Echocardiography could then be used in these high-risk children to detect RHD in its early stages. This may support a strategy for more effective secondary prophylaxis of RHD. Elsevier 2023-07-03 /pmc/articles/PMC10344801/ /pubmed/37455788 http://dx.doi.org/10.1016/j.ijcrp.2023.200195 Text en © 2023 The Authors. Published by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Paper
Ray, Madhab
Guha, Santanu
Dhungana, Ranga Raj
Karak, Avik
Choudhury, Basabendra
Ray, Bipasha
Zubair, Haroon
Ray, Meghna
Sengupta, Srijan
Bhatt, Deepak L.
Goldberg, Robert J.
Selker, Harry P.
Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title_full Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title_fullStr Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title_full_unstemmed Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title_short Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
title_sort development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10344801/
https://www.ncbi.nlm.nih.gov/pubmed/37455788
http://dx.doi.org/10.1016/j.ijcrp.2023.200195
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