Serum Irisin as a Predictor for Peripheral Arterial Disease: Insights from a Clinical Study

Objective: The purpose of this study was to investigate the correlation between serum irisin concentration and peripheral arterial disease (PAD), and to establish clinical prediction nomograms for PAD occurrence by comparing and analyzing clinical data from patients with PAD and healthy controls. Methods: A total of 112 patients with PAD and 90 healthy individuals were recruited for the study. Clinical data from both groups were collected and serum irisin concentration was measured using enzyme-linked immunosorbent assay (ELISA). Correlation analysis was conducted. Risk factors for PAD were identified through univariate and multivariate logistic regression. The clinical prediction nomograms were established and validated. Results: A total of 202 patients were enrolled in this study, with an average age of 63.98 +/- 10.40 years. Of these, 123 were male (60.9%) and 79 were female (39.1%). Hypertension was present in 104 patients (51.5%), diabetes in 59 patients (29.2%), dyslipidemia in 94 patients (46.5%), and 105 patients (52.0%) were smokers. Among them, 112 patients were assigned to the PAD group, which included 78 males (69.6%) and 34 females (30.4%), with an average age of 67.54 +/- 10.31 years. In this group, 62 patients (55.4%) had hypertension, 53 (47.3%) had diabetes, 62 (55.4%) had dyslipidemia, and 78 (69.6%) were smokers. The Rutherford classification of these patients showed that 64 (57.1%) were at stage I, 25 (22.3%) at stage II, 16 (14.3%) at stage III, and 7 (6.3%) at stage IV. Serum irisin concentration in patients with PAD showed a significant positive correlation with serum high-density lipoprotein (HDL) (r = 0.255) and a significant negative correlation with Rutherford classification (r = -0.374) and smoking status (r = -0.263). Univariate and multivariate logistic regression analyses identified irisin, age, diabetes, dyslipidemia, smoking, creatinine (CR), and neutrophil/lymphocyte ratio (NLR) as independent risk factors for the development of PAD (P < 0.05). Based on these findings, a clinical prediction nomogram was established. Internal validation of the nomogram demonstrated strong discriminatory ability, with an area under the curve (AUC) of 0.942, indicating the model's excellent performance. Calibration curves and decision curve analyses further confirmed the model's robust calibration and clinical applicability. Conclusions: This study concluded that serum irisin concentrations were significantly lower in the PAD group compared to the healthy control group, and that serum irisin concentrations in the PAD group were significantly correlated with serum HDL, Rutherford classification, and smoking status. Additionally, Irisin level, age, diabetes, dyslipidemia, smoking, CR, and NLR were identified as independent risk factors for PAD development. The clinical prediction nomogram based on these factors may aid in accurately predicting the risk of PAD development.