Predictors of walking capacity in peripheral arterial disease patients

Abstract

OBJECTIVE: To estimate walking capacity in intermittent claudication patients through a prediction model based on clinical characteristics and the walking impairment questionnaire. METHODS: The sample included 133 intermittent claudication patients of both genders aged between 30 and 80 years. Data regarding clinical characteristics, the walking impairment questionnaire and treadmill walking test performance were obtained. Multiple regression modeling was conducted to predict claudication onset distance and total walking distance using clinical characteristics (age, height, mass, body mass index, ankle brachial index lower, gender, history of smoking and co-morbid conditions) and walking impairment questionnaire responses. Comparisons of claudication onset distance and total walking distance measured during treadmill tests and estimated by a regression equation were performed using paired t-tests. RESULTS: Co-morbid conditions (diabetes and coronary artery disease) and questions related to difficulty in walking short distances (walking indoors - such as around your house and walking 5 blocks) and at low speed (walking 1 block at average speed - usual pace) resulted in the development of new prediction models high significant for claudication onset distance and total walking distance (p < 0.001). In addition, non-significant differences from the results obtained by the treadmill test and estimated by the current model (p > 0.05) were observed. CONCLUSION: The current study demonstrated that walking capacity can be adequately estimated based on comorbid conditions and responses to the walking impairment questionnaire.