A clinical and proteomics approach to predict the presence of obstructive peripheral arterial disease: From the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) Study.

ABSTRACT:

Background

Peripheral arterial disease (PAD) is a global health problem that is frequently underdiagnosed and undertreated. Noninvasive tools to predict the presence and severity of PAD have limitations including inaccuracy, cost, or need for intravenous contrast and ionizing radiation.

Hypothesis

A clinical/biomarker score may offer an attractive alternative diagnostic method for PAD.

Methods

In a prospective cohort of 354 patients referred for diagnostic peripheral and/or coronary angiography, predictors of ≥50% stenosis in ≥1 peripheral vessel (carotid/subclavian, renal, or lower extremity arteries) were identified from >50 clinical variables and 109 biomarkers. Machine learning identified variables predictive of obstructive PAD; a score derived from the final mode

SUBMITTER: McCarthy CP 

PROVIDER: S-EPMC6489776 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature