• Xi Chen, Julie A Stoner, Polly S Montgomery, Ana I Casanegra, Federico Silva-Palacios, Sixia Chen, Amanda E Janitz, and Andrew W Gardner.
• Department of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center, Oklahoma City, Okla. Electronic address: xi-chen@ouhsc.edu.
• J. Vasc. Surg. 2017 Oct 1; 66 (4): 1202-1209.

BackgroundPeripheral artery disease (PAD) is a highly prevalent disease that impairs walking ability. Walking tests, such as the 6-minute walk test (6MWT) and 4-meter walk test, are commonly used to assess exercise endurance and ambulatory function over a short distance, respectively. The 6MWT performance is predictive of PAD severity and disease outcomes, but it is not feasible in many clinical settings because it requires a long walkway to serve as the test route and lengthens clinic visits. As an alternative, the 4-meter walk test is convenient, inexpensive, and repeatable, but whether it accurately predicts endurance performance in the long-distance 6MWT is not known. The goal of this study was to develop a statistical model to predict 6MWT gait speed from 4-meter walk test results and clinical characteristics among patients with PAD.MethodsMeasures of 6MWT gait speed were derived from 183 patients with symptomatic PAD who were evaluated at the University of Oklahoma Health Sciences Center (2004-2012). The testing procedures and research personnel remained constant throughout the duration of the study. Independent variables included demographic and clinical information and 4-meter walk test gait speed. Fivefold cross validation and manual backward selection were used for model selection. Adjusted R2 and corrected Akaike information criterion were applied to quantify the predictive performance of the regression models.ResultsA total of 183 people (54% male; mean age, 65 [standard deviation (SD), 10] years) with moderate PAD severity (ankle-brachial index [ABI]; mean, 0.72 [SD, 0.24]) performed the walking tests. Participants covered an average distance of 335 (SD, 97) m distance in the 6MWT. The 4-meter walk gait speed, ABI, and dyspnea were independent predictors of 6MWT speed in the multivariate model (adjusted R2 = 0.55). The model resulted in 95% prediction interval widths of 30 m for mean and 260 m for individual predicted 6MWT distance measures.ConclusionsSlower 4-meter walking speed, lower ABI, and presence of dyspnea all predict slower 6MWT gait speed, which corresponds to shorter 6MWT distance. Prediction of group means is reasonably precise; however, prediction of individual patient 6MWT performance is imprecise relative to between-group differences that are clinically important.Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

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