1. Developing non-laboratory cardiovascular risk assessment charts and validating laboratory and non-laboratory-based models
- Author
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy, Hassannejad, Razieh, Mansourian Gharakozlou, Marjan, Marateb, Hamid Reza, Mohebian, Mohammad Reza, Gaziano, Thomas Andrew, Jackson, Rodney T., Di Angelantonio, Emanuele, Sarrafzadegan, Nizal, Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. BIOART - BIOsignal Analysis for Rehabilitation and Therapy, Hassannejad, Razieh, Mansourian Gharakozlou, Marjan, Marateb, Hamid Reza, Mohebian, Mohammad Reza, Gaziano, Thomas Andrew, Jackson, Rodney T., Di Angelantonio, Emanuele, and Sarrafzadegan, Nizal
- Abstract
Background: Developing simplified risk assessment model based on non-laboratory risk factors that could determine cardiovascular risk as accurately as laboratory-based one can be valuable, particularly in developing countries where there are limited resources. Objective: To develop a simplified non-laboratory cardiovascular disease risk assessment chart based on previously reported laboratory-based chart and evaluate internal and external validation, and recalibration of both risk models to assess the performance of risk scoring tools in other population. Methods: A 10-year non-laboratory-based risk prediction chart was developed for fatal and non-fatal CVD using Cox Proportional Hazard regression. Data from the Isfahan Cohort Study (ICS), a population-based study among 6504 adults aged = 35 years, followed-up for at least ten years was used for the non-laboratory-based model derivation. Participants were followed up until the occurrence of CVD events. Tehran Lipid and Glucose Study (TLGS) data was used to evaluate the external validity of both non-laboratory and laboratory risk assessment models in other populations rather than one used in the model derivation. Results: The discrimination and calibration analysis of the non-laboratory model showed the following values of Harrell’s C: 0.73 (95% CI 0.71–0.74), and Nam-D’Agostino ¿2:11.01 (p = 0.27), respectively. The non-laboratory model was in agreement and classified high risk and low risk patients as accurately as the laboratory one. Both non-laboratory and laboratory risk prediction models showed good discrimination in the external validation, with Harrell’s C of 0.77 (95% CI 0.75–0.78) and 0.78 (95% CI 0.76–0.79), respectively. Conclusions: Our simplified risk assessment model based on non-laboratory risk factors could determine cardiovascular risk as accurately as laboratory-based one. This approach can provide simple risk assessment tool where laboratory testing is unavailable, inconvenient, and costly., The baseline survey was supported by the undersecretary of research of the ministry of health and Isfahan cardiovascular research center, cardiovascular research institute affiliated to Isfahan University of Medical Sciences [grant number 31309304]. This work was also supported by the People Programme (Marie Curie Actions) of the European Union Seventh Framework Programme (FP7/2007–2013) [grant number 600388] and from the Agency for Business Competitiveness of the Government of Catalonia, ACC1Ó., Peer Reviewed, Postprint (published version)
- Published
- 2021