The PREVENT equations demonstrated good discrimination for 10-year ASCVD risk in Emirati females (C-index: 0.81-0.82) but moderate discrimination in males (C-index: 0.70-0.72).
Cohort (n=897)
No
Do the PREVENT equations accurately predict 10-year ASCVD risk in Emirati adults without prior CVD?
The AHA PREVENT equations effectively predict ASCVD risk in Emirati women but require recalibration for better accuracy, particularly in men.
BACKGROUND: Cardiovascular disease (CVD) prediction models are important tools for identifying individuals at risk and guiding preventative strategies. However, before new prediction models can be used in clinical practice, it is vital to validate them in the specific population they are intended to serve. Despite the high burden of CVD in Arab populations, they remain underrepresented in model development and validation studies. This study aimed to externally validate the performance of the newly released PREVENT models, originally developed in a United States population, among UAE nationals. METHODS: This study included 897 Emirati participants aged 30-79 from Tawam Hospital, UAE, with no prior CVD history. Data were collected from April to December 2008, with follow-up on atherosclerotic CVD (ASCVD) events until January 2020. The study compared the 10-year ASCVD risk using the PREVENT-ASCVD Base and PREVENT-ASCVD HbA1c equations, assessing discrimination and calibration using C-index values and calibration plots. RESULTS: The Emirati cohort had a mean age of 52 years, with 50% female participants. Over a median follow-up of 10.4 years for females and 10.1 years for males, 8.2% of females and 13.4% of males experienced ASCVD events. The PREVENT equations demonstrated good discrimination in females (C-index: 0.81-0.82) but moderate discrimination in males (C-index: 0.70-0.72), with calibration plots indicating overestimation at lower risk levels and underestimation at higher levels, especially in males. At the 7.5% risk cut-off, sensitivity and specificity were suboptimal in males but performed well in females. CONCLUSIONS: While the PREVENT equations predicted ASCVD risk effectively in Emirati women, recalibration is needed for better accuracy. These findings support the use of the PREVENT models for CVD prevention in the UAE, particularly for women. TRIAL REGISTRATION: This study is a retrospective observational study that utilizes existing data. As such, it does not involve the prospective assignment of participants to interventions, nor does it meet the criteria for a clinical trial. Therefore, trial registration is not applicable to this research.
Al-Shamsi et al. (2025) conducted a cohort in Atherosclerotic cardiovascular disease risk (n=897). PREVENT-ASCVD Base and PREVENT-ASCVD HbA1c equations was evaluated on 10-year ASCVD risk discrimination and calibration. The PREVENT equations demonstrated good discrimination for 10-year ASCVD risk in Emirati females (C-index: 0.81-0.82) but moderate discrimination in males (C-index: 0.70-0.72).
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