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The Framingham 10-year cardiovascular disease risk is measured by laboratory-based and non-laboratory-based models. This study aimed to determine the agreement between these two models in a large population in Southern Iran. In this study, the baseline data of 8138 individuals participated in the Pars cohort study were used. The participants had no history of cardiovascular disease or stroke. For the laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, systolic blood pressure (SBP) and treatment status, total cholesterol, and High-Density Lipoprotein. For the non-laboratory-based risk model, scores were determined based on age, sex, current smoking, diabetes, SBP and treatment status, and Body Mass Index. The agreement between these two models was determined by Bland Altman plots for agreement between the scores and kappa statistic for agreement across the risk groups. Bland Altman plots showed that the limits of agreement were reasonable for females < 60 years old (95% CI: -2.27-4.61%), but of concern for those ≥ 60 years old (95% CI: -3.45-9.67%), males < 60 years old (95% CI: -2.05-8.91%), and males ≥ 60 years old (95% CI: -3.01-15.23%). The limits of agreement were wider for males ≥ 60 years old in comparison to other age groups. According to the risk groups, the agreement was better in females than in males, which was moderate for females < 60 years old (kappa = 0.57) and those ≥ 60 years old (kappa = 0.51). The agreement was fair for the males < 60 years old (kappa = 0.39) and slight for those ≥ 60 years old (Kappa = 0.14). The results showed that in overall participants, the agreement between the two risk scores was moderate according to risk grouping. Therefore, our results suggest that the non-laboratory-based risk model can be used in resource-limited settings where individuals cannot afford laboratory tests and extensive laboratories are not available.
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http://dx.doi.org/10.1038/s41598-021-90188-5 | DOI Listing |
J Family Med Prim Care
July 2025
Department of Community Medicine, Ministry of Labour and Employment, Government of India, New Delhi, India.
Introduction: Cardiovascular diseases (CVDs) are the leading cause of death globally with three-fourths of the deaths occurring in low- and middle-income countries. According to the World Health Organization (WHO), CVDs represent 32% of the total global deaths that occurred in 2019, which is indeed a very high number.
Aim And Objectives: The aim of this study was to estimate the 10-year risk of cardiovascular events among adults aged ≥ 40 years in a rural population using the WHO CVD risk prediction charts for the South Asia region.
Reprod Sci
August 2025
Department of Mathematics and Computer, Eskişehir Osmangazi University, Eskisehir, Türkiye.
This study aimed to predict the likelihood of natural conception among couples by using a machine learning (ML) approach based on sociodemographic and sexual health data. This marks a novel, non-invasive methodology for fertility prediction. This prospective study included 197 couples divided into two groups: 98 fertile couples (Group 1) who achieved natural conception within one year, and 99 infertile couples (Group 2) who were unable to conceive despite regular unprotected intercourse.
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July 2025
Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
Background: Current guidelines for atherosclerotic cardiovascular disease (ASCVD) primary prevention mostly recommend risk scores that predict risk of non-fatal myocardial infarction, fatal ischemic heart disease (IHD), and fatal or non-fatal ischemic stroke (hard outcomes), ignoring the burden from other non-fatal IHD outcomes. We explored the optimal risk thresholds for statin initiation using non-laboratory-based soft and hard ASCVD outcome models and compared the cost-utility of such models in the Chinese population.
Methods: We constructed Markov cohort models to estimate the incidence of ASCVD events, costs, and quality-adjusted life years (QALYs) over a lifetime from a social perspective.
J Public Health (Oxf)
June 2025
Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, 1985717413, Iran.
Objective: We compared non-laboratory models' efficacy with standard laboratory-based model in identifying high-risk populations for cardiovascular disease (CVD) in resource-limited settings.
Methods: A national sample of 121 672 individuals aged 40-70 from the PERSIAN cohort was analyzed. Non-laboratory models, including the World Health Organization (WHO) and Iranian pooled-cohort CVD mortality models, were compared with the WHO laboratory-based model.
PLoS One
June 2025
Office of Health Equity Research, Yale School of Medicine, New Haven, Connecticut, United States of America.
Background: The World Health Organization (WHO) non-laboratory cardiovascular disease (CVD) risk chart is sub-region-specific and is advocated in resource-constrained settings. However, the extent of agreement with laboratory-based assessment among hypertensive adults attending primary health centers (PHCs) in the West Africa sub-region remains unknown. This study compared 10-year CVD risk among adults with hypertension attending PHCs in Ghana and Nigeria.
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