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Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients

BACKGROUND: Cardiovascular risk prediction models encompass numerous CVD risk factors. Available prediction models were developed from non-Asian cohorts hence we decided to evaluate the performance of the ASCVD risk estimator model and the associated 10-year CVD predisposing factors in Punjab. METHO...

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Autores principales: Osoro, Ian, Kumar, Ranjeet, Sharma, Amit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10604522/
https://www.ncbi.nlm.nih.gov/pubmed/37891666
http://dx.doi.org/10.1186/s13098-023-01170-2
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author Osoro, Ian
Kumar, Ranjeet
Sharma, Amit
author_facet Osoro, Ian
Kumar, Ranjeet
Sharma, Amit
author_sort Osoro, Ian
collection PubMed
description BACKGROUND: Cardiovascular risk prediction models encompass numerous CVD risk factors. Available prediction models were developed from non-Asian cohorts hence we decided to evaluate the performance of the ASCVD risk estimator model and the associated 10-year CVD predisposing factors in Punjab. METHODS: We carried out a cross-sectional study among patients having hypertension and diabetes mellitus in a tertiary hospital in Punjab, India. 201 participants without ASCVD who were ≥ 40 years old and had been admitted to the medical ward were assessed. a pre-validated questionnaire was used to collect data on the socio-demographics and behavioral patterns. Lipid profile and blood pressure measurements were collected as per standard protocols. The respondents’ CVD risk was assessed using ASCVD Risk Estimator Plus. Data were analyzed using IBM SPSS version 26; bivariate analysis was done using Chi-square and binary logistic regression was used to identify the predictors of 10-year risk for CVD at a 5% level of significance. Measurements. We examined the stratification of the predicted outcomes and evaluated the associations between individual risk factors and the predicted cardiovascular events. Our study categorized the results of these outcomes into 4 categories: low category (1–5%), borderline category (6–9%) intermediate category (10–20%), and high category (21–95%). RESULTS: Out of the 201 participants that enrolled in our study, the majority 76 (37.8%) were in the intermediate category, 56 (27.9%) were in the high category, 41 (20.4%) were in the borderline category, 28 (13.9%) were in the low category. The median ASCVD percentage was 14.20%. Respondents who were alcoholics, smokers, and drug abusers (OR = 5.8, 95% CI 0.397–83.584) were associated with the highest likelihood of developing CVDs. Furthermore, males had a significantly higher mean predicted CVD outcome % (M = 23.18%) compared to females (M = 14.91%). CONCLUSION: According to our prediction study, it was discovered that 145 (72.1%) participants were not likely to have had an ASCVD in the next 10 years. However, middle-aged males should be more cautious with their lifestyle habits, particularly in dealing with risk factors that can expose them to CVDs.
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spelling pubmed-106045222023-10-28 Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients Osoro, Ian Kumar, Ranjeet Sharma, Amit Diabetol Metab Syndr Research BACKGROUND: Cardiovascular risk prediction models encompass numerous CVD risk factors. Available prediction models were developed from non-Asian cohorts hence we decided to evaluate the performance of the ASCVD risk estimator model and the associated 10-year CVD predisposing factors in Punjab. METHODS: We carried out a cross-sectional study among patients having hypertension and diabetes mellitus in a tertiary hospital in Punjab, India. 201 participants without ASCVD who were ≥ 40 years old and had been admitted to the medical ward were assessed. a pre-validated questionnaire was used to collect data on the socio-demographics and behavioral patterns. Lipid profile and blood pressure measurements were collected as per standard protocols. The respondents’ CVD risk was assessed using ASCVD Risk Estimator Plus. Data were analyzed using IBM SPSS version 26; bivariate analysis was done using Chi-square and binary logistic regression was used to identify the predictors of 10-year risk for CVD at a 5% level of significance. Measurements. We examined the stratification of the predicted outcomes and evaluated the associations between individual risk factors and the predicted cardiovascular events. Our study categorized the results of these outcomes into 4 categories: low category (1–5%), borderline category (6–9%) intermediate category (10–20%), and high category (21–95%). RESULTS: Out of the 201 participants that enrolled in our study, the majority 76 (37.8%) were in the intermediate category, 56 (27.9%) were in the high category, 41 (20.4%) were in the borderline category, 28 (13.9%) were in the low category. The median ASCVD percentage was 14.20%. Respondents who were alcoholics, smokers, and drug abusers (OR = 5.8, 95% CI 0.397–83.584) were associated with the highest likelihood of developing CVDs. Furthermore, males had a significantly higher mean predicted CVD outcome % (M = 23.18%) compared to females (M = 14.91%). CONCLUSION: According to our prediction study, it was discovered that 145 (72.1%) participants were not likely to have had an ASCVD in the next 10 years. However, middle-aged males should be more cautious with their lifestyle habits, particularly in dealing with risk factors that can expose them to CVDs. BioMed Central 2023-10-27 /pmc/articles/PMC10604522/ /pubmed/37891666 http://dx.doi.org/10.1186/s13098-023-01170-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Osoro, Ian
Kumar, Ranjeet
Sharma, Amit
Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title_full Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title_fullStr Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title_full_unstemmed Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title_short Ten-year risk assessment for cardiovascular diseases using ASCVD risk estimator plus: outcomes from hypertension and diabetes patients
title_sort ten-year risk assessment for cardiovascular diseases using ascvd risk estimator plus: outcomes from hypertension and diabetes patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10604522/
https://www.ncbi.nlm.nih.gov/pubmed/37891666
http://dx.doi.org/10.1186/s13098-023-01170-2
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