Ankle Brachial Index Use in Peripheral Vascular Interventions for Claudication

Construction of prediction models for novel subtypes in patients with arteriosclerosis obliterans undergoing endovascular therapy: an unsupervised machine learning study

BACKGROUND

Arteriosclerosis obliterans (ASO) is a chronic arterial disease that can lead to critical limb ischemia. Endovascular therapy is increasingly used for limb salvage in ASO patients, but the outcomes vary. The development of prediction models using unsupervised machine learning may lead to the identification of novel subtypes to guide patient prognosis and treatment.

METHODS

This retrospective study analyzed clinical data from 448 patients with ASOs who underwent endovascular therapy. Unsupervised machine learning algorithms were employed to identify subgroups. To validate the precision of the clustering outcomes, an analysis of the postoperative results of the clusters was conducted. A prediction model was constructed using binary logistic regression.

RESULTS

Two distinct subgroups were identified by unsupervised machine learning and characterized by differing patterns of clinical features. Patients in Cluster 2 had significantly worse conditions and prognoses than those in Cluster 1. For the novel ASO subtypes, a nomogram was developed using six predictive factors, namely, platelet count, ankle brachial index, Rutherford category, operation method, hypertension, and diabetes status. The nomogram achieved excellent discrimination for predicting membership in the two identified clusters, with an area under the curve of 0.96 and 0.95 in training cohort and internal test cohort.

CONCLUSION

This study demonstrated that unsupervised machine learning can reveal novel phenotypic subgroups of patients with varying prognostic risk who underwent endovascular therapy. The prediction model developed could support clinical decision-making and risk counseling for this complex patient population. Further external validation is warranted to assess the generalizability of the findings.

Ankle-Brachial Index: Diagnostic Tool of Peripheral Arterial Disease and Predictor of Cardiovascular Risk-An Update of Current Knowledge

The ankle-brachial index (ABI) was introduced as a screening method for the diagnosis of lower extremity peripheral arterial disease (PAD). Later findings recognized ABI as a prognostic marker of adverse cardiovascular events due to its relation to atherosclerosis in other vascular territories. This narrative review aims to appraise the validity, reliability, and utility of ABI in the detection of PAD and the determination of global atherosclerotic cardiovascular risk. While the ABI value can be influenced by different physiological characteristics including age, sex, body position, and techniques used for ABI determination, it has high specificity and reproducibility in the assessment of vascular patients. In conclusion, when used correctly, the ABI remains a reliable and invaluable indicator of lower-limb perfusion and a useful tool for predicting the risk of future cardiovascular events. However, its underutilization in clinical settings is noteworthy.