Development and Validation of a Risk Nomogram Model for Predicting Revascularization After Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome

Abstract

Objective

Percutaneous coronary intervention (PCI) is one of the most effective treatments for acute coronary syndrome (ACS). However, the need for postoperative revascularization remains a major problem in PCI. This study was to develop and validate a nomogram for prediction of revascularization after PCI in patients with ACS.

Methods

A retrospective observational study was conducted using data from 1083 patients who underwent PCI (≥6 months) at a single center from June 2013 to December 2019. They were divided into training (70%; n = 758) and validation (30%; n = 325) sets. Multivariate logistic regression analysis was used to establish a predictive model represented by a nomogram. The nomogram was developed and evaluated based on discrimination, calibration, and clinical efficacy using the concordance statistic (C-statistic), calibration plot and decision curve analysis (DCA), respectively.

Results

The nomogram was comprised of ten variables: follow-up time (odds ratio (OR): 1.01; 95% confidence interval (CI): 1.00–1.03), history of diabetes mellitus (OR: 1.83; 95% CI: 1.25–2.69), serum creatinine level on admission (OR: 0.99; 95% CI: 0.98–1.00), serum uric acid level on admission (OR: 1.005; 95% CI: 1.002–1.007), lipoprotein-a level on admission (OR: 1.0021; 95% CI: 1.0013–1.0029), low density lipoprotein cholesterol level on re-admission (OR: 1.33; 95% CI: 0.10–0.47), the presence of chronic total occlusion (OR: 3.30; 95% CI: 1.93–5.80), the presence of multivessel disease (OR: 4.48; 95% CI: 2.85–7.28), the presence of calcified lesions (OR: 1.63; 95% CI: 1.11–2.39), and the presence of bifurcation lesions (OR: 1.82; 95% CI: 1.20–2.77). The area under the receiver operating characteristic curve values for the training and validation sets were 0.765 (95% CI: 0.732–0.799) and 0.791 (95% CI: 0.742–0.830), respectively. The calibration plots showed good agreement between prediction and observation in both the training and validation sets. DCA also demonstrated that the nomogram was clinically useful.

Conclusion

We developed an easy-to-use nomogram model to predict the risk of revascularization after PCI in patients with ACS. The nomogram may provide useful assessment of risk for subsequent treatment of ACS patients undergoing PCI.

Keywords:

• acute coronary syndrome
• percutaneous coronary intervention
• revascularization
• nomogram
• prediction model

Data Sharing Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethical Considerations

The study was conducted in accordance with the Declaration of Helsinki and was approved by the ethics committee for medical research at the Affiliated Hospital of Xuzhou Medical University. Due to the retrospective nature of the study, the requirement of written informed consent was waived by the review board. Confidential patient information was deleted from the entire data set prior to analysis.

Author Contributions

All authors contributed significantly to the conception and design, data acquisition, and data analysis and interpretation; participated in the drafting of the article or critically revised it for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agreed to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no conflicts of interest for this work.