ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Clinical and Translational Cardiovascular Medicine
Volume 12 - 2025 | doi: 10.3389/fcvm.2025.1602492
A study on predicting the risk of coronary artery disease in OSAHS patients based on a four-variable screening tool potential predictive model and its correlation with the severity of coronary atherosclerosis
Provisionally accepted
- First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
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Objective:This study aims to evaluate the potential association between the four-variable screening tool (the 4V) potential predictive model in predicting coronary artery disease (CAD) risk in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) and its correlation with the severity of coronary atherosclerosis, as measured by the Gensini scoring system. Methods: 1197 OSAHS patients with suspected CAD who were hospitalized in the First Affiliated Hospital of Xinjiang Medical University between March 2020 and February 2024 were selected. There were 423 cases in the OSAHS plus CAD group and 774 cases in the OSAHS group. LASSO regression analysis was carried out for screening potential influencing factors. Propensity score matching (PSM) was used to balance covariables between groups, and 293 cases were included per group in a 1:1 ratio. Univariable and multivariable logistic regression analyses were employed to evaluate parameters independently associated with CAD and construct a nomogram model.Receiver operating characteristic (ROC) curve analysis, Hosmer-Lemeshow test, calibration curve and decision curve (DCA) analyses were employed to assess its predictive value in CAD. A random forest machine learning algorithm was used to evaluate the importance of each risk factor. Pearson's or Spearman's correlation coefficients were employed to assess the strengths of associations among all variables and between predictors and Gensini scores. Results: LASSO-logistic regression analysis revealed age , hypertension , AHI, and the 4V were independently associated with OSAHS plus CAD.The analysis of the ROC curve , Hosmer-Lemeshow test, calibration curve, and DCA results indicate that potential predictive model based on the 4V possesses significant clinical applicability in predicting OSAHS in conjunction with CAD. A comprehensive analysis utilizing the random forest machine learning algorithm demonstrated that the AHI exhibits the highest predictive value. The correlation analysis results showed that the scores of the four-variable screening tool were positively correlated with the Gensini scores. Conclusion:Age, hypertension, AHI, and the four-variable screening tool are independent risk factors for CAD in patients with OSAHS. The potential predictive model based on the 4V is closely related to the prediction of CAD and its correlation with the severity of coronary atherosclerosis.
Keywords: Four-variable screening tool, Obstructive sleep apnea hypopnea syndrome, Coronary Artery Disease, prediction, association study
Received: 21 Apr 2025; Accepted: 13 Jun 2025.
Copyright: © 2025 Yao, Li, Chen, Qiu, Aimaiti and Maimaitimin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yulan Chen, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
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