Objective To investigate the factors influencing cardiac rehabilitation compliance after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) and to construct a nomogram prediction model based on this.
Methods Two hundred and fifty ACS patients admitted to our hospital from June 2020 to August 2022 who underwent cardiac rehabilitation in the acute phase of rehabilitation after PCI were selected, and the ACS patients were divided into good compliance group (n=154) and poor compliance group (n=96) according to cardiac rehabilitation compliance. The general data of the patients in the two groups were collected and surveyed using the demographic data questionnaire, depression scale, and anxiety scale. The influencing factors of post-PCI cardiac rehabilitation compliance in ACS patients were analyzed using multivariate logistic regression, and the relationship between these influencing factors and compliance was analyzed by the Spearman′s correlation test, and a nomogram was constructed based on the factors influencing the post-PCI cardiac rehabilitation compliance in ACS patients. The predictive ability, accuracy, and clinical utility of the model were evaluated and validated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis.
Results Compared with the good compliance group, the patients in the poor compliance group had significantly higher (P<0.05) age, percentage of education (junior high school and below), monthly income level, distance traveled to see the doctor, percentage of hypertension, percentage of hyperlipidemia, percentage of (poor) perception of disease, percentage of (poor) social support, as well as percentage of depression, anxiety, and cardiac function class (grade Ⅲ) (P<0.05), and significantly lower levels of serum high-density lipoprotein cholesterol (HDL-C) and left ventricular ejection fraction (LVEF) levels (P<0.05); however, the levels of gender, smoking history, alcohol consumption history, body mass index (BMI), ACS type, marital status, diabetes mellitus, renal disease, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C),albumin (ALB), glycated hemoglobin (HbA1c), uric acid (UA), left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), type of medication, and postoperative complications (cerebral hemorrhage, thrombosis, and infections) were not statistically significant (P>0.05). The results of multivariate logistic regression analysis showed that age, distance traveled to see the doctor, and depression were independent risk factors affecting cardiac rehabilitation compliance of patients (P<0.05), while education level, monthly income level, HDL-C, and LVEF level were independent protective factors for cardiac rehabilitation compliance of patients (P<0.05).The results of Spearman′s correlation analysis showed that education level and monthly income levels, HDL-C, and LVEF were significantly and positively correlated with patients′ cardiac rehabilitation compliance scores (r=0.655, 0.720, 0.694, 0.826, all P<0.05), while age and distance traveled to see a doctor were significantly and negatively correlated with patients′ cardiac rehabilitation compliance scores (r=-0.643, -0.812, both P<0.05), and there was no significant correlation between depression and patients′ cardiac rehabilitation compliance scores (r=-0.322, P>0.05). In the nomogram prediction model, the ROC curve model had an area under the ROC curve (AUC)=0.970, and the calibration and decision curves showed that the model had good accuracy.
Conclusion Age, education level, monthly income level, distance traveled to see the doctor, depression, HDL-C, and LVEF are all influencing factors of cardiac rehabilitation compliance after PCI in patients with ACS, and a nomogram prediction model based on this can effectively assess the risk of cardiac rehabilitation compliance in patients.