Detection of medial vascular calcification in chronic kidney disease based on pulse wave analysis in the frequency domain

Abstract

Medial vascular calcification (mVC), particularly prevalent in patients with chronic kidney disease (CKD), is a pathological deposition of minerals in the medial layer of the vessel wall and is associated with an increased risk of cardiovascular disease. Currently, there is no cost–effective and non-invasive procedure of mVC assessment in routine clinical practice. We explored whether in–depth analysis of non-invasively recorded peripheral pulse waves can serve as an effective mVC biomarker.The study included 97 CKD patients with histological assessment of mVC in the epigastric artery and pulse wave measurements in the brachial artery. Pulse waves were analysed in the frequency domain to obtain features, which, together with traditional mVC risk factors (i.e., age, sex, and body mass index), were used to build generalized linear models for mVC prediction. The classifiers with the best scores in terms of balanced accuracy were combined in an ensemble establishing the final model.The final, ensembled model, assessed using a leave-one-out cross-validation process, achieved a balanced accuracy equal to 0.87, an accuracy of 0.93, an AUC ROC of 0.91, and an F-score of 0.96. Apart from the features associated with pulse waves, the selected variables included age, sex, body mass index, heart rate and diastolic blood pressure.Analysis of non-invasively recorded peripheral pulse waveforms combined with traditional risk factors, can help to detect mVC in CKD patients and thus, potentially introduce risk-lowering therapeutic strategies at earlier disease stages in the future.