Multimodel inference applied to oxygen recovery kinetics after 6-min walk tests in patients with chronic obstructive pulmonary disease.

Florent Baty,Christian Ritz,Martin Hugo Brutsche,Lukas Kern,Michael Tamm,Signe Marie Jensen

doi:10.1371/journal.pone.0187548

Abstract

6-min walk tests (6MWT) are routinely performed in patients with chronic obstructive pulmonary disease (COPD). Oxygen uptake () kinetics during 6MWT can be modeled and derived parameters provide indicators of patients’ exercise capacity. Post-exercise recovery also provides important parameters of patients’ fitness which has not been extensively investigated in COPD. Several nonlinear regression models with different underlying biological assumptions may be suitable for describing recovery kinetics. Multimodel inference (model averaging) can then be used to capture the uncertainty in considering several models. Our aim was to apply multimodel inference in order to better understand the physiological underpinnings of recovery after 6MWT in patients with COPD. 61 patients with COPD (stages 2 to 4) were included in this study. Oxygen kinetics during 6MWT were modeled using nonlinear regression. Three statistical approaches (mixed-effects, meta-analysis and weighted regression) were compared in order to summarize estimates obtained from multiple kinetics. The recovery phase was modeled using 3 distinct equations (log-logistic, Weibull 1 and Weibull 2). Three models were fitted to the set of 61 kinetics. A significant model-averaged difference of 40.39 sec (SE = 17.1) in the time to half decrease of level () was found between stage 2 and 4 (p = 0.0178). In addition, the Weibull 1 model characterized by a steeper decrease at the beginning of the recovery phase showed some improvement of goodness of fit when fitted to the kinetics of patients with stage 2 COPD in comparison with the 2 other models. Multimodel inference was successfully used to model recovery after 6MWT in patients with COPD. Significant model-averaged differences in were found between moderate and very severe COPD patients. Furthermore, specific patterns of recovery could be identified across COPD stages.

Highlights

In patients with chronic obstructive pulmonary disease (COPD), dyspnea is a frequent respiratory symptom which progressively leads to exercise intolerance
Oxygen kinetics were measured in 61 patients with COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2, 3 and 4)
Multimodel inference is a powerful tool to summarize information from multiple recovery kinetics when modelled by a set of plausible models

Summary

Introduction

In patients with chronic obstructive pulmonary disease (COPD), dyspnea is a frequent respiratory symptom which progressively leads to exercise intolerance. In order to assess the exercise capacity of patients with COPD, 6-min walk tests (6MWT) are commonly performed. This submaximal test is of particular interest as it reflects patients daily life activities. The post-exercise V_ O2 recovery phase provides important indicators of physical fitness as shown by Cohen-Solal et al [2] in patients with chronic heart failure. It has not been extensively investigated in patients with COPD. Modeling approaches have been used to characterize the recovery phase of patients with COPD and significant differences in the steepness of the V_ O2 recovery and the half-time recovery of oxygen uptake (T1=2 V_ O2) have been found across all disease severity stages [4]

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