A nomogram prediction model incorporating HbA1c, IGF-I, LDL-C, TNF-α, hsCRP, stent type, post-procedural percentage diameter stenosis, and calcium antagonist use demonstrated good discrimination for post-PCI restenosis in CAD patients with T2DM, with an apparent AUC of 0.833 and bootstrap-corrected AUC of 0.808.
Lower HbA1c levels were significantly associated with post-PCI restenosis in CAD patients with T2DM.
Higher IGF-I levels were significantly associated with increased risk of post-PCI restenosis.
Higher LDL-C levels were significantly associated with increased risk of post-PCI restenosis.
Higher TNF-α levels were significantly associated with increased risk of post-PCI restenosis.
Higher hsCRP levels were significantly associated with increased risk of post-PCI restenosis.
Use of non-drug-eluting stents (non-DES) was associated with increased risk of post-PCI restenosis.
Higher post-procedural percentage diameter stenosis (%DS) was associated with increased risk of post-PCI restenosis.
Use of calcium antagonists was negatively associated with post-PCI restenosis.
The nomogram prediction model demonstrated good discrimination for post-PCI restenosis.
The study was a retrospective case-control analysis of 272 CAD patients with T2DM who underwent PCI between January 2020 and June 2023.
The authors noted that external validation of the nomogram is pending and that the model may serve as an exploratory tool for risk stratification.
This research suggests that several blood markers and procedural factors can help predict whether patients with both heart disease (coronary artery disease) and type 2 diabetes will develop restenosis — a re-narrowing of the artery — within one year after undergoing a procedure called percutaneous coronary intervention (PCI, or stenting). The study followed 272 such patients and found that higher levels of IGF-I (a growth factor), LDL cholesterol (so-called 'bad' cholesterol), TNF-α and hsCRP (markers of inflammation), and greater residual artery narrowing after the procedure were all linked to a higher chance of restenosis. Interestingly, lower HbA1c (a measure of average blood sugar control) was also associated with restenosis, which is an unexpected finding the authors noted. Additionally, patients who received older-style stents (non-drug-eluting stents) had higher restenosis risk, while those taking a class of blood pressure medications called calcium antagonists had lower risk. Using these eight factors, the researchers built a visual prediction tool called a nomogram that could estimate an individual patient's probability of restenosis. When tested internally using a statistical technique called bootstrap resampling, the model performed well, correctly distinguishing between patients who did and did not develop restenosis about 81% of the time (corrected AUC = 0.808). This research suggests that combining specific blood biomarkers with information about the stenting procedure and medications could help clinicians identify diabetic heart disease patients who are at higher risk of restenosis after PCI. However, the study was conducted at a single center, looked back at past records, and has not yet been tested in an independent patient population, so the authors caution that external validation is needed before the tool could be more broadly applied in clinical practice.
Wang P, Peng H, Fan Q, Shan Y, Yin N. (2026). Nomogram for predicting post-percutaneous coronary intervention restenosis in patients with coronary artery disease and diabetes: a retrospective study.. PeerJ. https://doi.org/10.7717/peerj.21697