Nomogram for predicting post-percutaneous coronary intervention restenosis in patients with coronary artery disease and diabetes: a retrospective study

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.