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      Cardiopulmonary exercise testing early after stroke using feedback-controlled robotics-assisted treadmill exercise: test-retest reliability and repeatability

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          Abstract

          Background

          Exercise capacity is seriously reduced after stroke. While cardiopulmonary assessment and intervention strategies have been validated for the mildly and moderately impaired populations post-stroke, there is a lack of effective concepts for stroke survivors suffering from severe motor limitations. This study investigated the test-retest reliability and repeatability of cardiopulmonary exercise testing (CPET) using feedback-controlled robotics-assisted treadmill exercise (FC-RATE) in severely motor impaired individuals early after stroke.

          Methods

          20 subjects (age 44–84 years, <6 month post-stroke) with severe motor limitations (Functional Ambulatory Classification 0–2) were selected for consecutive constant load testing (CLT) and incremental exercise testing (IET) within a powered exoskeleton, synchronised with a treadmill and a body weight support system. A manual human-in-the-loop feedback system was used to guide individual work rate levels. Outcome variables focussed on standard cardiopulmonary performance parameters. Relative and absolute test-retest reliability were assessed by intraclass correlation coefficients (ICC), standard error of the measurement (SEM), and minimal detectable change (MDC). Mean difference, limits of agreement, and coefficient of variation (CoV) were estimated to assess repeatability.

          Results

          Peak performance parameters during IET yielded good to excellent relative reliability: absolute peak oxygen uptake (ICC =0.82), relative peak oxygen uptake (ICC =0.72), peak work rate (ICC =0.91), peak heart rate (ICC =0.80), absolute gas exchange threshold (ICC =0.91), relative gas exchange threshold (ICC =0.88), oxygen cost of work (ICC =0.87), oxygen pulse at peak oxygen uptake (ICC =0.92), ventilation rate versus carbon dioxide output slope (ICC =0.78). For these variables, SEM was 4-13%, MDC 12-36%, and CoV 0.10-0.36. CLT revealed high mean differences and insufficient test-retest reliability for all variables studied.

          Conclusions

          This study presents first evidence on reliability and repeatability for CPET in severely motor impaired individuals early after stroke using a feedback-controlled robotics-assisted treadmill. The results demonstrate good to excellent test-retest reliability and appropriate repeatability for the most important peak cardiopulmonary performance parameters. These findings have important implications for the design and implementation of cardiovascular exercise interventions in severely impaired populations. Future research needs to develop advanced control strategies to enable the true limit of functional exercise capacity to be reached and to further assess test-retest reliability and repeatability in larger samples.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1743-0003-11-145) contains supplementary material, which is available to authorized users.

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          Most cited references64

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          Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM.

          Reliability, the consistency of a test or measurement, is frequently quantified in the movement sciences literature. A common metric is the intraclass correlation coefficient (ICC). In addition, the SEM, which can be calculated from the ICC, is also frequently reported in reliability studies. However, there are several versions of the ICC, and confusion exists in the movement sciences regarding which ICC to use. Further, the utility of the SEM is not fully appreciated. In this review, the basics of classic reliability theory are addressed in the context of choosing and interpreting an ICC. The primary distinction between ICC equations is argued to be one concerning the inclusion (equations 2,1 and 2,k) or exclusion (equations 3,1 and 3,k) of systematic error in the denominator of the ICC equation. Inferential tests of mean differences, which are performed in the process of deriving the necessary variance components for the calculation of ICC values, are useful to determine if systematic error is present. If so, the measurement schedule should be modified (removing trials where learning and/or fatigue effects are present) to remove systematic error, and ICC equations that only consider random error may be safely used. The use of ICC values is discussed in the context of estimating the effects of measurement error on sample size, statistical power, and correlation attenuation. Finally, calculation and application of the SEM are discussed. It is shown how the SEM and its variants can be used to construct confidence intervals for individual scores and to determine the minimal difference needed to be exhibited for one to be confident that a true change in performance of an individual has occurred.
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            The Barthel ADL Index: a reliability study.

            The Barthel Index is a valid measure of disability. In this study we investigated the reliability of four different methods of obtaining the score in 25 patients: self-report, asking a trained nurse who had worked with the patient for at least one shift, and separate testing by two skilled observers within 72 hours of admission. Analysis of total (summed) scores revealed a close correlation between all four methods: a difference of 4/20 points was likely to reflect a genuine difference. In individual items, most disagreement was minor and involved the definition of middle grades. Asking an informed nurse or relative was as reliable as testing, and is quicker.
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              Practical statistics for medical researched

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                Author and article information

                Contributors
                oliver.stoller@bfh.ch
                eling.debruin@hest.ethz.ch
                matthias.schindelholz@bfh.ch
                c.schuster@reha-rhf.ch
                ra.debie@maastrichtuniversity.nl
                kenneth.hunt@bfh.ch
                Journal
                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                11 October 2014
                11 October 2014
                2014
                : 11
                : 1
                : 145
                Affiliations
                [ ]Department of Engineering and Information Technology, Institute for Rehabilitation and Performance Technology, Bern University of Applied Sciences, Burgdorf, Switzerland
                [ ]Department of Epidemiology, Maastricht University and Caphri Research School, Maastricht, The Netherlands
                [ ]Research Department, Reha Rheinfelden, Rheinfelden, Switzerland
                [ ]Department of Health Sciences and Technology, Institute of Human Movement Sciences and Sport, ETH Zurich, Zurich, Switzerland
                [ ]Centre for Evidence Based Physiotherapy, Maastricht University, Maastricht, The Netherlands
                Article
                677
                10.1186/1743-0003-11-145
                4271449
                25306061
                a11c378d-3e08-4fa7-b666-6511c1befb31
                © Stoller et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 4 June 2014
                : 3 October 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Neurosciences
                stroke rehabilitation,subacute,severe motor impairment,robotics-assisted gait training,aerobic capacity,treadmill exercise

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