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. 2022 Mar 3:15:2451-2461.
doi: 10.2147/IJGM.S357250. eCollection 2022.

A Nomogram for Predicting In-Stent Restenosis Risk in Patients Undergoing Percutaneous Coronary Intervention: A Population-Based Analysis

Yinhua Luo #  1 , Ni Tan #  2 , Jingbo Zhao  3 , Yuanhong Li  3
Affiliations

A Nomogram for Predicting In-Stent Restenosis Risk in Patients Undergoing Percutaneous Coronary Intervention: A Population-Based Analysis

Yinhua Luo et al. Int J Gen Med. .

Abstract

Objective: In-stent restenosis (ISR) is a fatal complication of percutaneous coronary intervention (PCI). An early predictive model with the medical history of patients, angiographic characteristics, inflammatory indicators and blood biochemical index is urgently needed to predict ISR events. We aim to establish a risk prediction model for ISR in CAD patients undergoing PCI.

Methods: A total of 477 CAD patients who underwent PCI with DES (drug-eluting stents) between January 2017 and December 2020 were retrospectively enrolled. And the preoperative factors were compared between the non-ISR and ISR groups. The least absolute shrinkage and selection operator (LASSO) and multi-factor logistic regression were used for statistical analysis. The prediction model was evaluated using receiver operator characteristic (ROC) analysis, the Hosmer-Lemeshow 2 statistic, and the calibration curve.

Results: In this study, 94 patients developed ISR after PCI. Univariate analysis showed that post-PCI ISR was associated with the underlying disease (COPD), higher Gensini score (GS score), higher LDL-C, higher neutrophil/lymphocyte ratio, and higher remnant cholesterol (RC). The multi-factor logistic regression analysis suggested that remnant cholesterol (odds ratio [OR] = 2.09, 95% confidence interval [CI] [1.40-3.11], P < 0.001), GS score (OR = 1.01, 95% CI [1.00, 1.02], P = 0.002), medical history of COPD (OR = 4.56, 95% CI [1.98, 10.40], P < 0.001), and monocyte (OR = 1.30, 95% CI [1.04, 1.70], P < 0.001) were independent risk factors for ISR. A nomogram was generated and displayed favorable fitting (Hosmer-Lemeshow test P = 0.609), discrimination (area under ROC curve was 0.847), and clinical usefulness by decision curve analysis.

Conclusion: Patients with certain preoperative characteristics, such as a history of COPD, higher GS scores, higher levels of RC, and monocytes, who undergo PCI may have a higher risk of developing ISR. The predictive nomogram, based on the above predictors, can be used to help identify patients who are at a higher risk of ISR early on, with a view to provide post-PCI health management for patients.

Keywords: CHD; ISR; PCI; coronary heart disease; in-stent restenosis; nomogram map; percutaneous coronary intervention.

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Conflict of interest statement

Yinhua Luo and Ni Tan are co-first authors for this study. The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
The study design and the selection procession of CAD patients.
Figure 2
Figure 2
Risk factors selecting using LASSO model.
Figure 3
Figure 3
Nomogram to predict the probability of ISR in patients with stent implantation.
Figure 4
Figure 4
ROC curves for validating the discrimination power of nomogram.
Figure 5
Figure 5
Calibration plots of the nomogram for the probability of PCI patients with ISR.
Figure 6
Figure 6
Decision curve analysis for the ISR prediction nomogram.
See this image and copyright information in PMC

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