Development and validation of a novel 10-year cardiovascular risk prediction nomogram for the United Arab Emirates national population.
| Autor: | Al-Shamsi S; Department of Internal Medicine, United Arab Emirates University College of Medicine and Health Sciences, Al Ain, Abu Dhabi, UAE salshamsi@uaeu.ac.ae. |
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| Jazyk: | angličtina |
| Zdroj: | BMJ open [BMJ Open] 2022 Dec 29; Vol. 12 (12), pp. e064502. Date of Electronic Publication: 2022 Dec 29. |
| DOI: | 10.1136/bmjopen-2022-064502 |
| Abstrakt: | Objectives: Atherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality among United Arab Emirates (UAE) nationals. Recent studies have shown that current tools are poor in predicting the risk of incident ASCVD in Emiratis. To improve ASCVD risk prediction in this high-risk population, this study sought to develop and validate a novel and practical 10-year ASCVD risk nomogram using risk factors known to be significant in UAE nationals. Design: A 10-year retrospective cohort study. Setting: Outpatient clinics at a large public tertiary care hospital in Al-Ain, UAE. Participants: Emiratis aged ≥18 years without prior cardiovascular disease (CVD) who had presented to Tawam Hospital's clinics between 1 April 2008 and 31 December 2008, were included. Patients' data were collected retrospectively until 31 January 2020. Exposure: Cox proportional hazards models were developed to estimate the 10-year ASCVD risk. Primary Outcome Measure: Model discrimination and calibration were assessed using the Harrell C-statistic and the Greenwood-Nam-D'Agostino (GND) χ 2 test, respectively. Receiver operating characteristic curve analysis was used to determine the optimal cut-off point of the nomogram for elevated ASCVD risk. Results: The study included 1245 patients, of whom 117 developed ASCVD within 10 years. The ASCVD risk nomogram comprised age, sex, family history of CVD, hypertension treatment, systolic blood pressure, total cholesterol, glycosylated haemoglobin A1c and estimated glomerular filtration rate. The Harrell C-statistic was 0.826 and the GND χ 2 was 2.83 (p=0.830), which indicated good discrimination and calibration of the nomogram model, respectively. The optimal cut-off point was determined to be 10% (sensitivity=79%; specificity=77%). The nomogram can be freely accessed as an online calculator at (https://ascvdriskuae.shinyapps.io/ASCVDrisk/). Conclusions: The developed nomogram provides an accurate prognostic tool for 10-year ASCVD risk prediction in UAE nationals. These findings may help guide future research on CVD prevention in this high-risk population. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.) |
| Databáze: | MEDLINE |
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