Diagnosis models to predict peripheral arterial disease: a systematic review and meta analysis

作者：Xiaoyan Quan, Huarong Xiong, Xiaoyu Liu, Pan Song, Dan Wang, Qin Chen, Xiaoli Hu, Meihong Shi · 发表于：Scientific Reports · 年份：2025 · DOI：10.1038/s41598-025-10459-3 · 被引用次数：5 · 研究领域：Peripheral Artery Disease Management、Diagnosis and Treatment of Venous Diseases、Cerebrovascular and Carotid Artery Diseases

Peripheral arterial disease (PAD) affects approximately 236.62 million individuals globally, exposing them to significantly increased risks of major limb events such as death and amputation. Concurrently, the number of diagnostic prediction models for PAD patients is steadily rising; however, these studies exhibit varying results, and their quality and applicability in clinical practice and future research remain unclear. To systematically assess the methodological quality of studies on PAD diagnostic prediction models. PubMed, Embase, Web of Science and Cochrane Database of Systematic Reviews were searched to identify studies which aiming to develop or validate a diagnostic prediction model of PAD. The retrieval time limit is from the establishment of the database to June 1, 2025. Two researchers independently screened and extracted data from eligible studies and evaluated the risk of bias using the Prediction Model Risk of Bias Assessment Tool (PROBAST). A total of 24 studies on PAD diagnostic prediction models were included, most of which exhibited high risk of bias, predominantly in the domains of study population and statistical analysis. The meta-analyzed Area Under the Receiver Operating Characteristic Curve (AUC) was 0.79 [0.74, 0.84], indicating favorable model performance. The reported number of predictor variables ranged from 2 to 20, with common predictors including age, gender, hypertension, diabetes, smoking, and BMI. This study demonstrates that PAD diagnostic ...