A risk nomogram model for predicting readmission after percutaneous coronary intervention within one year in type 2 diabetes mellitus patients with acute coronary syndrome

AIM To investigate and evaluate the risk factors associated with readmission within one year after percutaneous coronary intervention (PCI) in patients diagnosed with acute coronary syndrome and type 2 diabetes mellitus and to develop a clinical prediction model.

METHODS A retrospective medical data analysis was conducted in patients diagnosed with acute coronary syndrome and type 2 diabetes mellitus and discharged after successful PCI between January 2019 and January 2022. The patients were categorized into a readmission group or a non-readmission group based on their hospital readmission status due to major cardiovascular adverse events within a year after PCI. The risk factors associated with the readmission were analyzed using logistic regression.

RESULTS The findings of multivariate logistic regression analysis indicated that age (OR = 1.064, 95% CI: 1.059～1.096), hospitaldays (OR = 1.109, 95% CI: 1.053～1.169), historyof diabetes exceeding 20 years (OR = 2.005, 95%CI:1.346～2.959), Cystatin C (OR = 1.699,95% CI:1.299～2.239), ejection fraction (OR = 0.975, 95%CI: 0.958～0.992), multi-vessel disease ( OR=1.744, 95%CI: 1.270～2.422) and ST/T wave changes(OR = 1.920, 95% CI: 1.419～2.612) were all significant predictors of readmission risk. Based on these results, a nomogram model for predicting the risks of readmission in this patient population was developed.

CONCLUSION The risk factors for readmission of patients with acute coronary syndrome complicated with type 2 diabetes within one year after PCI include age, hospitalization days, diabetes history exceeding 20 years, Cystatin C, ejection fraction, multivessel disease and ST/T wave changes. Our nomogram prediction model exhibits good discrimination and effectiveness, rendering it a valuable clinical tool for early predicting the risks of readmission.