Nomogram for predicting post-percutaneous coronary intervention restenosis in patients with coronary artery disease and diabetes: a retrospective study
- 1Center for Coronary Artery Disease (CCAD), Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Disease, Beijing, China
Abstract
Background: Coronary artery disease (CAD) combined with diabetes mellitus (DM) significantly increases the risk of vascular restenosis following percutaneous coronary intervention (PCI). Despite advancements in stent technology, restenosis remains a concern, especially in diabetic patients. This study aims to predict restenosis risk using serum metabolites and risk factors.
Methods: A retrospective analysis was conducted on 272 CAD and type 2 diabetes mellitus (T2DM) patients who underwent PCI between January 2020 and June 2023. Based on one-year angiographic follow-up, patients were divided into restenosis ( n = 121) and non-restenosis groups ( n = 151). Serum metabolites and biomarkers, including glycated hemoglobin (HbA1c), insulin-like growth factor I (IGF-I), low-density lipoprotein cholesterol (LDL-C), tumor necrosis factor-α (TNF-α), and high-sensitivity C-reactive protein (hsCRP), were evaluated, together with procedure-related characteristics (including stent type and post-procedural percentage diameter stenosis) and medication use (including calcium antagonists). Logistic regression and correlation analysis identified significant predictors, and a nomogram prediction model was developed and internally validated using bootstrap resampling.
Results: Lower HbA1c levels were associated with restenosis (rho = −0.142, P = 0.008; OR = 0.767, 95% CI [0.625–0.941]). Higher levels of IGF-I (rho = 0.328, P < 0.001; OR = 1.053, 95% CI [1.032–1.075]), LDL-C ( r = 0.135, P = 0.025; OR = 1.682, 95% CI [1.107–2.555]), TNF-α ( r = 0.172, P = 0.004; OR = 1.434, 95% CI [1.119–1.838]), and hsCRP ( r = 0.179, P = 0.003; OR = 1.786, 95% CI [1.185–2.693]) were also significantly associated. Non-drug-eluting stents (DES) and higher percentage diameter stenosis (%DS) increased restenosis risk. Calcium antagonists use was negatively correlated with restenosis ( r = − 0.185, P = 0.002; OR = 0.449, 95% CI [0.228–0.884]). The nomogram model demonstrated good discrimination for restenosis (apparent AUC = 0.833; bootstrap-corrected AUC = 0.808).
Conclusion: This study identified key predictive factors for post-PCI restenosis in CAD patients with DM through case-control analysis. The nomogram model showed good discrimination on internal bootstrap validation. Pending external validation, it may provide a useful exploratory tool to support risk stratification and inform management aimed at reducing the restenosis burden in high-risk cardiovascular populations.
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BibTeX
@article{wang2026nomogram,
title = {{Nomogram for predicting post-percutaneous coronary intervention restenosis in patients with coronary artery disease and diabetes: a retrospective study}},
author = {Ping Wang and Hongyu Peng and Qian Fan and Yuan Shan and Ning Yin},
journal = {PeerJ},
year = {2026},
month = oct,
doi = {10.7717/peerj.21697},
url = {https://peerj.com/articles/21697},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Nomogram for predicting post-percutaneous coronary intervention restenosis in patients with coronary artery disease and diabetes: a retrospective study
AU - Ping Wang
AU - Hongyu Peng
AU - Qian Fan
AU - Yuan Shan
AU - Ning Yin
PY - 2026
DA - 2026/10/13
JO - PeerJ
DO - 10.7717/peerj.21697
UR - https://peerj.com/articles/21697
AB - Background: Coronary artery disease (CAD) combined with diabetes mellitus (DM) significantly increases the risk of vascular restenosis following percutaneous coronary intervention (PCI). Despite advancements in stent technology, restenosis remains a concern, especially in diabetic patients. This study aims to predict restenosis risk using serum metabolites and risk factors. Methods: A retrospective analysis was conducted on 272 CAD and type 2 diabetes mellitus (T2DM) patients who underwent PCI between January 2020 and June 2023. Based on one-year angiographic follow-up, patients were divided into restenosis ( n = 121) and non-restenosis groups ( n = 151). Serum metabolites and biomarkers, including glycated hemoglobin (HbA1c), insulin-like growth factor I (IGF-I), low-density lipoprotein cholesterol (LDL-C), tumor necrosis factor-α (TNF-α), and high-sensitivity C-reactive protein (hsCRP), were evaluated, together with procedure-related characteristics (including stent type and post-procedural percentage diameter stenosis) and medication use (including calcium antagonists). Logistic regression and correlation analysis identified significant predictors, and a nomogram prediction model was developed and internally validated using bootstrap resampling. Results: Lower HbA1c levels were associated with restenosis (rho = −0.142, P = 0.008; OR = 0.767, 95% CI [0.625–0.941]). Higher levels of IGF-I (rho = 0.328, P < 0.001; OR = 1.053, 95% CI [1.032–1.075]), LDL-C ( r = 0.135, P = 0.025; OR = 1.682, 95% CI [1.107–2.555]), TNF-α ( r = 0.172, P = 0.004; OR = 1.434, 95% CI [1.119–1.838]), and hsCRP ( r = 0.179, P = 0.003; OR = 1.786, 95% CI [1.185–2.693]) were also significantly associated. Non-drug-eluting stents (DES) and higher percentage diameter stenosis (%DS) increased restenosis risk. Calcium antagonists use was negatively correlated with restenosis ( r = − 0.185, P = 0.002; OR = 0.449, 95% CI [0.228–0.884]). The nomogram model demonstrated good discrimination for restenosis (apparent AUC = 0.833; bootstrap-corrected AUC = 0.808). Conclusion: This study identified key predictive factors for post-PCI restenosis in CAD patients with DM through case-control analysis. The nomogram model showed good discrimination on internal bootstrap validation. Pending external validation, it may provide a useful exploratory tool to support risk stratification and inform management aimed at reducing the restenosis burden in high-risk cardiovascular populations.
SN - 2167-8359
ER -