A nomogram predicting 30-day mortality in patients undergoing percutaneous coronary intervention.

Background and Aims: Early detection of mortality after percutaneous coronary intervention (PCI) is crucial, whereas most risk prediction models are based on outdated cohorts before the year 2000. This study aimed to establish a nomogram predicting 30-day mortality after PCI.
Materials and Methods: In total, 10,444 patients undergoing PCI in National Center for Cardiovascular Diseases in China were enrolled to establish a nomogram to predict 30-day mortality after PCI. The nomogram was generated by incorporating parameters selected by logistic regression with the stepwise backward method.
Results: Five features were selected to build the nomogram, including age, male sex, cardiac dysfunction, STEMI, and TIMI 0-2 after PCI. The performance of the nomogram was evaluated, and the area under the curves (AUC) was 0.881 (95% CI: 0.8-0.961). Our nomogram exhibited better performance than a previous risk model (AUC = 0.7, 95% CI: 0.586-0.813) established by Brener et al. The survival curve successfully stratified the patients above and below the median score of 4.
Conclusion: A novel nomogram for predicting 30-day mortality was established in unselected patients undergoing PCI, which may help risk stratification in clinical practice.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2022 Song, Liu, Wang, Chen, Yang, Wen, Gao, Shao and Tang.)