Predictors of Walking Distance After Supervised Exercise Therapy in Patients with Intermittent Claudication

• Published in: European journal of vascular and endovascular surgery 2009-10, Vol.38 (4), p.449-455
• Main Authors: Kruidenier, L.M, Nicolaï, S.P.A, Ten Bosch, J.A, de Bie, R.A, Prins, M.H, Teijink, J.A.W
• Format: Article
• Language: English
• Subjects: Age Factors; Aged; Arterial occlusive disease; Body Mass Index; Exercise Therapy; Female; Humans; Intermittent Claudication - etiology; Intermittent Claudication - physiopathology; Intermittent Claudication - therapy; Lung Diseases - complications; Male; Middle Aged; Peripheral Vascular Diseases - complications; Peripheral Vascular Diseases - physiopathology; Peripheral Vascular Diseases - therapy; Predictive Value of Tests; Prognosis; Recovery of Function; Regression Analysis; Reproducibility of Results; Retrospective Studies; Risk Assessment; Risk Factors; Smoking - adverse effects; Surgery; Treatment Outcome; Walking
• ISSN: 1078-5884; 1532-2165
• DOI: 10.1016/j.ejvs.2009.04.020

Abstract Objective To identify predictor variables for results after supervised exercise therapy (SET), and to develop a clinical prediction model that aims to predict a target walking distance for individual patients. Design Retrospective analyses on prospectively collected data. Materials Patients with intermittent claudication who participated in a SET programme. Methods SET was conducted according to the guidelines of the Royal Dutch Society for Physiotherapy. The main outcome measurement was the absolute claudication distance (ACD) after 6 months of SET. Linear regression analyses were conducted to identify independent predictor variables for ACD. Results In this cohort, 437 patients were analysed. Independent predictor variables for post-treatment ACD were baseline ACD ( P < 0.001), smoking behaviour ( P = 0.012) and body-mass index ( P = 0.041). A better baseline ACD was associated with a longer post-treatment ACD whereas current smoking and a higher body-mass index were associated with a shorter post-treatment ACD. The final regression equation included baseline ACD, age, body-mass index, smoking and pulmonary disease, and was translated into several clinical prediction models. However, only 24.8–33.6% of the patients had an ACD within the calculated target range. Conclusions Predictive variables for post-treatment ACD after SET are baseline ACD, age, body-mass index, pulmonary disease and smoking behaviour. However, translating the regression equation into a clinical prediction model did not lead to a valid model for use in clinical practice.