Predictive factors and models for major adverse cardiovascular and limb events in patients with peripheral arterial disease.

Background: Peripheral arterial disease (PAD) is associated with an increased risk of major adverse cardiovascular and limb events. However, the factors influencing major adverse cardiovascular events (MACE) and major adverse limb events (MALE) in patients with PAD remain unclear. Additionally, while some predictive models for MACE and MALE in patients with PAD have been developed, their performance is uncertain. This systematic review aims to identify the factors influencing MACE and MALE in patients with PAD and to systematically evaluate existing predictive models. Materials and methods: We conducted a literature search in PubMed, Embase, and the Cochrane Library to identify studies exploring risk factors for MACE and MALE, as well as predictive models for these outcomes. Data extraction focused on study design, patient demographics, reported influencing factors (e.g., clinical, biochemical), and characteristics of predictive models (e.g., variables, validation methods, performance metrics). We specifically evaluated the methodological quality and risk of bias of the identified predictive models using established tools such as PROBAST (Prediction model Risk Of Bias ASsessment Tool). This study aimed to synthesize evidence on determinants of MACE and MALE and critically appraise existing prediction models to inform future research and clinical decision-making. Results: One hundred and sixteen studies reported factors influencing MACE in patients with PAD. Six studies developed or validated predictive models. Three models were rated as having low risk of bias across all domains, while the other three had unclear or high risk of bias in at least one domain. A total of 118 influencing factors associated with MACE were identified. Common factors included: demographic characteristics (age, smoking); (2) comorbidities (diabetes mellitus (DM), coronary artery disease (CAD), prior stroke, heart failure); (3) clinical measures (body mass index (BMI), systolic blood pressure (SBP)); (4) diagnostic indicators (ankle-brachial index (ABI), estimated glomerular filtration rate (eGFR), C-reactive protein (CRP), serum creatinine); (5) medication use (statins); and (6) classification systems (Rutherford classification, Fontaine classification). Fifty-five studies reported factors influencing MALE in patients with PAD. Six studies developed or validated predictive models. Three models were rated as having low risk of bias across all domains, while the other three had unclear or high risk of bias in at least one domain. A total of 88 influencing factors were identified. Common factors across most studies included demographic characteristics (age, smoking, socioeconomic status), comorbid conditions (DM, chronic kidney disease, hypertension, cerebrovascular disease), clinical factors (degree of frailty, BMI), diagnostic indicators (hemoglobin, serum creatinine, serum albumin), medication use (statin), and other factors (Wound, Ischemia, and foot Infection (WIfI) classification, geriatric nutritional risk index (GNRI)). Conclusions: Building on these findings, we conclude that, although substantial research exists on factors influencing MACE and MALE in patients with PAD, significant variability persists in study design (patient population), external factors (healthcare environment), and research focus. Our review provides a concise yet comprehensive analysis of predictive models for MACE and MALE in patients with PAD, identifies key predictive factors, systematically evaluates these models, and offers recommendations for their improvement.