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Development of a Cardiovascular Disease Risk Prediction Model: A Preliminary Retrospective Cohort Study of a Patient Sample in Saudi Arabia.
Alabduljabbar, Khaled; Alkhalifah, Mohammed; Aldheshe, Abdulaziz; Shihah, Abdulelah Bin; Abu-Zaid, Ahmed; DeVol, Edward B; Albedah, Norah; Aldakhil, Haifa; Alzayed, Balqees; Mahmoud, Ahmed; Alkhenizan, Abdullah.
Afiliación
  • Alabduljabbar K; Department of Family Medicine & Polyclinics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Alkhalifah M; Department of Family Medicine & Polyclinics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Aldheshe A; Department of Family Medicine & Polyclinics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Shihah AB; Department of Family Medicine & Polyclinics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Abu-Zaid A; College of Medicine, Alfaisal University, Riyadh 11533, Saudi Arabia.
  • DeVol EB; College of Graduate Health Sciences, University of Tennessee Health Science Center, Memphis, TN 38163, USA.
  • Albedah N; Department of Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Aldakhil H; Department of Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Alzayed B; Department of Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Mahmoud A; Department of Epidemiology and Scientific Computing, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
  • Alkhenizan A; Department of Family Medicine & Polyclinics, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia.
J Clin Med ; 12(15)2023 Aug 04.
Article en En | MEDLINE | ID: mdl-37568517
Saudi Arabia has an alarmingly high incidence of cardiovascular disease (CVD) and its associated risk factors. To effectively assess CVD risk, it is essential to develop tailored models for diverse regions and ethnicities using local population variables. No CVD risk prediction model has been locally developed. This study aims to develop the first 10-year CVD risk prediction model for Saudi adults aged 18 to 75 years. The electronic health records of Saudi male and female patients aged 18 to 75 years, who were seen in primary care settings between 2002 and 2019, were reviewed retrospectively via the Integrated Clinical Information System (ICIS) database (from January 2002 to February 2019). The Cox regression model was used to identify the risk factors and develop the CVD risk prediction model. Overall, 451 patients were included in this study, with a mean follow-up of 12.05 years. Thirty-five (7.7%) patients developed a CVD event. The following risk factors were included: fasting blood sugar (FBS) and high-density lipoprotein cholesterol (HDL-c), heart failure, antihyperlipidemic therapy, antithrombotic therapy, and antihypertension therapy. The Bayesian information criterion (BIC) score was 314.4. This is the first prediction model developed in Saudi Arabia and the second in any Arab country after the Omani study. We assume that our CVD predication model will have the potential to be used widely after the validation study.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Clin Med Año: 2023 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Clin Med Año: 2023 Tipo del documento: Article País de afiliación: Arabia Saudita Pais de publicación: Suiza