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.