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Reproducibility of Different Methodologies to Calculate Oxygen Consumption and Oxygen Cost During Walking in Chronic Stroke Survivors
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Reproducibility of Different Methodologies to Calculate Oxygen Consumption and Oxygen Cost During Walking in Chronic Stroke Survivors Tim Blatter, MSc, Jacqueline Outermans, PhD, PT, Michiel Punt, PhD, and Harriet Wittink, PhD, PT
Objective: The most common methods to calculate energy costs are based on measured oxygen uptake during walking a standardized distance or time. Unfortunately, it is unclear which method is most reliable to determine energy cost of walking in stroke survivors. The objective of this study was to evaluate the 3 most commonly used methods for calculating oxygen consumption and -cost by assessing test-retest reliability and measurement error in community dwelling chronic stroke survivors during a 6 Minute Walk Test. Methods: In this secondary analysis of a longitudinal study, reproducibility of the outcome of walking distance, walking speed, oxygen consumption and oxygen cost from 3 methods (Kendall’s tau, assumed steady-state and total walking time oxygen consumption) were determined using Intraclass Correlation Coefficient, Standard Error of Measurement and Smallest Detectable Change. Results: 20 from the 31 participants successfully performed the 6 minute walk test-retest within a timeframe of 1 month. Within the 2 tests the reproducibility of walking distance and walking speed was high. The 3 methods to determine reproducibility for oxygen cost and oxygen consumption were considered good (Kendall’s tau), good (assumed steady-state) and excellent (total walking time). Conclusions: The method using oxygen consumption and -cost over the total walking time resulted in the highest reproducibility considering the Intraclass Correlation Coefficient, its 95% Confidence Interval, and smaller absolute differences. Key Words: Test-retest reliability—oxygen cost—oxygen consumption—6MWT © 2020 Elsevier Inc. All rights reserved.
Introduction For nearly half the people who survive a stroke, hemiparesis is the most common disability 3 months after the event.1 Post stroke muscle impairments (eg, spasticity, abnormal muscle activation patterns, and reduced oxygen uptake capacity) have been associated with higher energy demands during walking.2 A higher oxygen cost of walking post stroke has been linked to reduced From the Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, the Netherlands. Received June 5, 2019; revision received November 5, 2019; accepted December 31, 2019. Address correspondence to Tim Blatter MSc, Research Group Lifestyle and Health, Institute of Movement Studies, The University of Applied Science Utrecht, Postbus 12011, 3501 AA, Utrecht, the Netherlands. E-mails: [email protected], [email protected]. 1052-3057/$ - see front matter © 2020 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.104637
walking performance and reduced participation in the community.3 Energy demand during hemiparetic gait has been explored in a broad range of studies using different methods.4-16 The most common methods to calculate energy costs are based on measured oxygen uptake during walking a standardized distance or time. Both oxygen consumption (OCS) and oxygen cost (OC) describe the amount of oxygen that is consumed during the test. First, the definition of oxygen consumption is the transportation and utilization of oxygen in a person during exercise and is expressed in VO2 mL O2/kg/ min.5,17-19 Second, oxygen cost is calculated as oxygen consumption during walking divided by walking speed, resulting in a relative VO2 cost per body weight per meter (mL O2/kg/m).17,18 Both oxygen consumption and -cost can be expressed as a gross or net term. Gross OC is the total amount of oxygen expended for a specific activity, while net oxygen consumption is computed as gross oxygen consumption minus the individual’s
Journal of Stroke and Cerebrovascular Diseases, Vol. &&, No. && (&&), 2020: 104637
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resting oxygen consumption. This term is used to compare the energy cost of specific activities, such as walking, cycling and climbing stairs. A recent review on energy cost of walking in people post stroke2 reported a wide variety of methods between studies in the calculations of oxygen consumption and oxygen cost. In most of the studies, oxygen consumption was measured during steady-state conditions within walking time,6-9,12,20 others used the oxygen consumption and cost over the total walking time.21,22 A standard protocol to determine steady-state in walking among chronic stroke survivors has not been established yet. One of the methods used in previous studies to determine the steady-state as an average VO2 in a time frame of 3 minutes at the end of a 6 minute walk test (6MWT),17 according to an earlier definition of steady-state in healthy subjects.23 Others defined the achievement of a stable VO2-state during a 6MWT as the steady-state8,9,20 but none of these studies used cut-off values or thresholds within the measured parameters. Two earlier studies24,25 used the Kendall’s Tau approach to calculate the occurrence of a steady-state with the use of breath-by-breath data. The authors of the review2 concluded there is an obvious need for a clear definition of steady-state and consistent methods of identifying the steady-state condition during walking post stroke to establish a reproducible method in calculating the oxygen cost during walking. Given the need to study energy cost of walking in stroke survivors, the lack of methodological consistency and knowledge which method is most reliable to determine energy cost of walking, this study aimed to evaluate 3 of the most commonly used methods by assessing testretest reliability and measurement error of energy cost in community dwelling chronic stroke survivors during a 6MWT. Findings from this study can be used in aerobic capacity progress performance evaluation of chronic stroke survivors.
Materials and Methods Study Design This study is a secondary analysis of a cross-sectional study26 on the relation between aerobic capacity and walking capacity in chronic stroke survivors. The present study concerns a test-retest study on metabolic responses in chronic stroke survivors while performing the 6MWT. In the cross-sectional study,26 the participants were tested twice within a timeframe of 1 month. Three physical therapists, experienced in stroke rehabilitation and exercise testing, conducted the assessments. Inter-assessor agreement was optimized during 3 2-hour sessions. The data were collected during 2 sessions.
In this study, no measurements were done, the results that are described in this study are gathered from the cross-sectional study.26 The author of this secondary analysis screened the data from the cross-sectional study to create a complete data-set to answer his research question.
Human Committee Approval The Medical Ethics Review Committee of the University Medical Centre Utrecht (ID041), chaired by Dr. P.D. Siersema, approved the research protocol (ID11/204) in December 2011. The cross-sectional study26 was conducted in accordance with the declaration of Helsinki. All participants provided written consent.
Participants The participants were recruited from Dutch rehabilitation centers, daycare centers, and private physical therapy practices. Their attending physical therapists established potential eligibility and willingness to participate in the study and asked for permission to pass contact data on to the researcher. The researcher contacted the potential participant for an initial appointment to assess for inclusion and exclusion criteria and obtain informed consent. The inclusion criteria were: (1) diagnosed stroke according to the WHO definition,27 (2) minimal 3 months post stroke, (3) age over 18 years and (4) the ability to walk independently under supervision, i.e., Functional Ambulation Categories (FAC)-score of 3 and above.28 The presence of a severe cognitive disorder, i.e., Mini Mental State Examination greater than 24 points,29 severe cardiovascular disease and severe communicative disorder (Utrecht Communication State < 4 points)30 were the exclusion criteria for the study.26
Variables Demographics and participants’ characteristics included age, gender, height and weight, time since onset stroke, hemiplegic side, walking ability and stroke severity. The FAC28 describes the ability of a person to walk independently in categories from 0; not able to walk to 5; able to walk independently on level and nonlevel surfaces. The FAC-score is mostly determined by their attending physical therapist and assessed during the 6MWT. The Motricity Index (MI) assesses functional strength and a person’s ability for voluntary knee extension, hip flexion and ankle dorsiflexion. The MI is reliable and valid for stroke survivors.31,32 In this study, the researcher positioned the joint and asked the participant to maintain position while the researcher tried slowly to move the joint in opposite direction. The scores for each movement vary from 0 to 33 points for each dimension, indicating no counter activity (0) to maximal counter strength (33). At maximal scores, 1 point is added to a total score of 100 points.
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The main outcome variables of the study were: walking distance, walking speed, oxygen consumption, and oxygen cost.
Walking Distance and Walking Speed Walking distance and walking speed were assessed with the 6MWT. The 6MWT is a valid and reliable test for the stroke population.6,16,31-35 We performed the 6MWT according to the standardized instructions of the American Thoracic Society Guidelines 36 on a 20-meter straight course. The total distance covered was determined by counting the laps and adding the surplus.
Oxygen Consumption and Oxygen Costs The participants were requested not to eat, drink caffeine or smoke at least 2 hours prior to the 6MWT because this influences exercise capacity and therefore threatens reproducibility. While executing the 6MWT, respiratory gas exchange was measured with a portable metabolic system (Cortex Metamax B3-R2, Cortex Biophysik GmbH, Leipzig, Germany). This system contains a mask which allows expired gas to pass through a flowmeter, oxygen analyzer, and carbon dioxide analyzer. A wireless connection (Bluetooth) with a computer supported the possibility to wirelessly calculate the breath-by-breath minute ventilation (VE), oxygen consumption (VO2), carbon dioxide production (VCO2) and respiratory exchange ratio from conventional equations. Preceding and throughout the 6MWT, an electrocardiogram was obtained with a mobile 12-channel system (Custocor Custo Med, Ottobrunn, Germany). The electrocardiogram signal was screened for ventricular arrhythmia and/or exercise-induced ischemia, i.e., ST-segment depression greater than .10 mV (1mm) for 80 ms.37 Prior to the 6MWT, blood pressure was measured with an OMRON M10-IT device (OMRON Europe, Hoofddorp, Netherlands). The 6MWT was only started if blood pressure (BP) values were below 180 mm Hg systolic and 100 mm Hg diastolic. Before testing started, the participant wore the facemask while seated to become familiarized with the equipment. In the last minute of this procedure, the oxygen consumption was measured to ensure a baseline measurement. Directly following the 6MWT, blood pressure was measured again and the rate of perceived exertion was collected using the 6-20 BORG-scale.38 Oxygen consumption was measured breath by breath and afterwards averaged in 1-second intervals for the Kendall’s Tau steady-state18 and 10-second intervals for all other methods.
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Data Analysis Calculation Oxygen Consumption and Oxygen Cost We performed 3 sets of calculations for gross and net oxygen consumption from oxygen consumption during the 6MWT; Method 1. We used Kendall’s tau to determine steady-state during the entire 6MWT, method 2. We calculated the mean oxygen consumption during minute 3 to 5 as we assumed this time frame to represent a steadystate and method 3. We calculated the mean oxygen consumption over the total walking time.
Method 1. Oxygen Consumption during Steady-state Kendall’s Tau A custom written MATLAB (MATLAB and Statistics Toolbox Release 2015b, The MathWorks, Inc., Natick, MA) script determined Kendall’s tau as described by Schwartz et al.18 Briefly, Kendall’s tau was calculated for the breathby-breath sampled VO2 versus time data (in 1-second interval) that occurs within a sliding window of the raw data. Steadiness of the VO2 (for the data point that corresponds to the mid-point of the sliding window) was identified when the probability of t = 0 was less than 0.10 in a 2-tailed test (Z-score). A steady-state was determined if the duration of the Z-scores was at least 1 minute.
Method 2. Oxygen Consumption and Oxygen Costs during the Total Walking Time To determine the oxygen consumption during the assumed steady-state between minute 3 and 5 within the 6MWT5,9,20,39, the VO2 of the participant during this timeframe was averaged over 13 (2*6+1) data points using the 10 second time-interval. The breath by breath data was filtered in 10 second intervals during the total 6 minutes walking time of the test. This generated a total of 36 VO2data points. Oxygen consumption was then determined as the mean of these data points, while the oxygen cost was calculated as oxygen consumption divided by walking speed (the walking distance divided by time).
Method 3. Gross and Net Oxygen Consumption or Oxygen Cost in All Calculations As described in earlier studies5,17,18,40 the net oxygen consumption was calculated as the measured gross oxygen consumption during steady-state or total walking time minus the resting oxygen consumption. Due to the difference in duration of resting phase that each participant needed to be familiarized with the mask of the portable metabolic system in this study, the last minute of the resting phase was used to calculate resting oxygen consumption for all calculations. Net oxygen cost was calculated by
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Figure 1. Flowchart participants. The clinical characteristics of the remaining subjects are shown in Table 1 and all variables were normally distributed.
dividing the net oxygen consumption by the average walking speed of the participant during the 6MWT.
Statistical Analysis Descriptives Descriptive statistics were used to report the demographic and clinical characteristics of the sample. The symmetry of the distribution of all continuous variables was assessed using the Shapiro-Wilk test. Thereafter percentages, means and standard deviations were calculated, and nominal data were categorized.
Reproducibility IBM SPSS version 23 was used to determine distribution, mean values and standard deviation. The reproducibility of the OC and OCS calculations of the test-retest was calculated in SPSS with an ICC two-way random single measure with absolute agreement (ICCagreement 2.1), the standard error of measurement (SEM) and the smallest detectable change (SDC). The ICCagreement2.1 is considered poor when it is below .40, fair between .41 and .59, good when its value is .60-.74 and excellent when it exceeds .75.41 The SEM and SDC are both expressed in actual measurement units and therefore useful in individual level evaluations. SEM was calculated using the following formula: SEMagre pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi ement ¼ s ð1ICCÞ where s is the pooled standard deviation of test and retest scores. SEM can be calculated as SEMagreement or SEMconsistency42 SEMagreement takes the systematic difference between test and retest into account
while the SEMconsistency ignores systematic differences. We therefore used SEMagreement in all calculations. The SEM can be convertedpinto ffiffiffi the smallest detectable change (SDC) (SDC ¼ 1:96 2 SEM) which reflects the smallest within-person change in score that, with 95% confidence, can be interpreted as a ‘‘real’’ change, above measurement error, in 1 individual (SDCind).43
Results Participants As shown in Figure 1, there were 62 eligible participants for the cross-sectional study. Four participants decided not to participate. 21 participants preferred not to be tested on 2 separate occasions and 6 participants missed the second session. 31 participants successfully performed the 6MWT twice, unfortunately 3 participants were rescheduled outside the 1-month timeframe between test and re-test. Test-forms from 5 participants were missing data after testing and in three 6MWTs an error occurred in the indirect metabolic measurement due to leakage in the mask, resulting in an invalid measurement of oxygen consumption. All our participants were experienced in walking the 6MWT, hereby precluding a practice effect. Demographic characteristics of our participants are shown in Table 1. The mean BMI score of these participants was 27.9 kg/m2, 5 participants were below a BMI of 25 (normal weight), 9 participants between 25 and 30 (overweight) and 6 participants above 30 (obese). Regarding co-morbidity from these participants, 13 did not suffer from a (known) co-
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morbidity, 2 participants had Diabetes type 2, 1 participant had Cardiovascular Disease, 1 participant had epilepsy, 1 participant had Goiter, 1 participant suffered from lowered kidney function and 1 participant had muscle dystrophy in the left ankle. Most of the participants still went to the physical therapist (median: 2 hours or more) during the cross-sectional study.
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6MWT and the oxygen cost was the result of the average VO2 during the total walking time. The reliability of these results were both considered excellent. The higher 95% CIs in the OC net and gross calculation (resp. .569-.892 and .727-.952) confirm the higher reliability of the estimates within the group, comparing to the other results.
Discussion Oxygen Consumption and Oxygen Cost The measured and calculated mean results of the 6MWT are described below in Table 2. The mean walking distance was 383.38 meters in the first test (T1) and 391.30 meters in the second test (T2). Average speed (m/s) was calculated using the distance covered divided by 360 seconds. The mean difference in speed between T1 and T2 was .01 m/s. The rate of perceived exertion on BORGscale had a median score of 13 in both tests. The individual and mean OCS during the 6MWT are shown in Figure 2. There were large individual differences in OCS, which ranged after 3 minutes walking from 10 mL O2/ kg/min to 27 mL O2/kg/min in both tests (see Fig 2). There is 1 outlier clearly visible in both tests, this participant performed the first 6MWT with an average OCS of 22 mL O2/kg/min and the second 6MWT with an average OCS of 24 mL O2/kg/min, while the rest performed the test close to 14 mL O2/kg/min. In T2 the average OCS within the group was similar to T1, while the standard deviation was larger in the second test. From the total of 40 measurements among 20 participants, 13 participants reached a steady-state according to Kendall’s tau in both T1 and T2 with a duration of at least 1 minute. Their average OCS during these steady-states was 15.5 mL O2/kg/min in T1 and 16.9 mL O2/kg/min in T2; see Table 2. No participant reached steady-state at the same moment in both tests according to Kendall’s tau. During the assumed steady-state in minute 3 to minute 5 the average OCS was 15.36 mL O2/kg/min and 15.82 mL O2/kg/min. When OCS during total walking time was calculated the participants consumed 14.17 mL O2/kg/min oxygen in T1 and 14.90 mL O2/kg/min in T2. For gross oxygen cost (OC) the means of both trials were .24 mL O2/kg/m.
Reproducibility The results of the reproducibility calculations are described in Table 2. The ICCs for the steady-state (SS) calculations according to Kendall’s Tau were .612 and considered good.41 The ICCs for the assumed steady-state net and gross were higher (resp. .728 and .805) as well for OCS measured during total walking time (resp. .728 and .813) were considered respectively good and excellent. The highest ICCs (resp. .805 and .882) were found when the oxygen cost of walking was calculated with the assumption that no steady-state was reached during the
The use of steady-state as a method to determine oxygen consumption chronic stroke survivors in walking is common practice in most previous studies.10,12,20 The stable cardiorespiratory outcome measures and continuous walking speed can give reliable information about the oxygen consumption and oxygen cost, provided that task is easy enough for the participant to maintain a steadystate condition. Accelerating, decelerating and turning causing balance difficulties, change of muscle activity and intensity could complicate these objectives, especially in chronic stroke survivors. With dozens of different methods to determine oxygen consumption in walking for stroke survivors, the results are difficult to combine and hard to interpret. As described in the introduction, a standard protocol to determine steady-state in walking among chronic stroke survivors has not established yet. This is the first study that determined which method is “best” for calculating oxygen consumption in patients with chronic post stroke hemiparesis. We defined the most reproducible method as the “best method”. Overall, steady-states were difficult to establish, calling into question previous studies in which assumptions were made such as that after 3 minutes walking a steady-state should be visible10 or to expect a plateau value approximately 85% of age-predicted heart rate maximum value within the first 2 minutes.6 Equally, we found that the algorithm described by Schwartz24 to determine a steady-state digitally did not provide a solution for measuring steadystate. None of the 20 participants reached a similar steady-state in both trials and for a number of participants no steady-state could be calculated. Therefore, the reproducibility results according to Kendall’s Tau shown in Table 2 represent a smaller group within our participants, with a lower ICC and greater SEM and SDC compared to the other 2 methods. Our findings suggest that on group level the participants had a similar pattern in oxygen consumption during the 6MWT. However, the closer a method tried to determine the oxygen consumption on an individual level by identifying the steadiness in VO2 measurement, the smaller the group of participants that achieved steadiness got and the lower its reproducibility became. Therefore, the method that used the overall data and not steady-state data, showed the highest reproducibility. The second method, showing lower reproducibility, assumes a steady-state after 3 minutes walking and uses a shorter interval to average oxygen consumption. The third
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Table 1. Mean and SD and between group differences in demographic and stroke specific characteristics (N = 20) Demographic characteristics
Mean (SD)
Range
Age (years) Height (m) Weight (kg) BMI Male (%) Time since onset (mean months) Walking support (number)
59.4 (10.1) 1.71 (.09) 81.7 (20.00) 27.9 (6.0) 55% 55.65 (49.00) Shoe: 7 Cane: 5 AFO: 2 77.1 (23.5) 3: 9.1% 4: 18.2% 5: 63.6%
41-79 1.55-1.86 50-108 19.5-43.3
Motricity index (0-100) FAC-score (%)
6-170
9-100
Abbreviations: FAC, functional ambulation categories; SD, standard deviation.
(Kendall’s tau) uses 1-sec interval and VO2 data showed the lowest reproducibility here. The lack of steadiness in VO2 we found in our sample, when the second and third method were applied, could imply that the participants were not able to walk the 6MWT with a steady-state in VO2. This may have related to the straight 20 meter course we used in our protocol and the accelerating and decelerating necessary to perform the test.
Most of our participants live a more sedentary life compared to their healthy peers, maybe due to the fact that their walking demands higher energy.2 The result of this lifestyle is shown in Table 1, the mean BMI score of our participants was over 25. Although this is an unfortunate fact, it is not unique. In similar previous studies,6,20,32 the majority of participants has a sufficiently high BMI to be classified as “overweight” or “obese”. One of the main objectives of most physical therapists is to motivate stroke survivors to participate in a more active lifestyle. The ICCs for walking distance and speed in this study were similar to previous studies.6,12,44,45 The highest ICC within the 3 methods was found in gross OC calculated over the total walking time. The 95% CI was in this method also the narrowest, suggesting the most reliable estimation of the methods that were studied. This method had a comparable result as in a previous study5,17,18,21 the highest ICC, a small SEM and SDC. Also, Brehm17 already established that gross OC is more reliable than net OC, first because net OC varied more for people with gait impairments than for healthy subjects and second the measurements of net OC became more variable as the resting period increased, especially for patients. Only a few studies described the SEMs and SDCs of the 6MWT measurements in chronic stroke patients. The SEM in walking distance is similar to earlier studies.44,46 One study in 2003,21 with only 9 stroke survivors, calculated the oxygen cost of walking (mL O2/kg/m) and reported
Table 2. Clinical outcomes and reproducibility of the 3 methods to determine steady-states Measurement Distance (m) Speed (m/s) Rest OCS (mL O2/kg/min) Steady-state Kendall’s tau (N = 13) SS OCS (mL O2/kg/min) Steady-state 3-5min (N = 20) Gross 2 min OCS (mL O2/kg/min) Net 2 min OCS (mL O2/kg/min) Total Walking Time (N = 20) Gross OCS (mL O2/kg/min) Net OCS (mL O2/kg/min) Gross OC (mL O2/kg/m) Net OC (mL O2/kg/m)
95% CI
SEM
SDC
.969
.923-.987
22.92
54.78
.968
.922-.987
.06
.15
.593
.229-.814
.62
.08
3.50 3.30
.612
136-.862
2.12
5.06
15.58 15.38 11.86 11.41
3.44 4.24 3.23 3.77
.805
571-.918
1.70
4.07
.728
434-.882
1.83
4.38
14.28 14.62 10.49 10.65 .25 .25 .18 .18
2.94 3.70 2.73 3.27 .09 .07 .06 .05
.813
590-.921
1.45
3.45
.727
425-.883
.03
.06
.882
727-.952
1.57
3.76
.805
569-.892
.03
.05
Mean
Std. dev.
ICC2,1
T1 T2 T1 T2 T1 T2
376.91 382.15 1.05 1.06 3.72 3.97
132.87 127.43 .37 .35 .87 1.05
T1 T2
15.61 16.44
T1 T2 T1 T2 T1 T2 T1 T2 T1 T2 T1 T2
Abbreviations: OC, oxygen cost; OCS, oxygen consumption; SS, steady-state.
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Figure 2. VO2 over time measurement 6MWT first and second trial.
similar SEMs and SDCs (resp. .03 and .06) as found in this study (resp. .03 and .05).
Limitations There are some limitations to this present study that should be considered when interpreting the results. First, the small sample size resulted in a large variation, hereby causing a broad 95% CI and a less precise ICC. It is common to use the ICC calculation to determine the test-retest reliability. An earlier study31 suggested that solely using the ICC for the evaluation of reliability (distance in meters of the 6MWT in their case) can lead to fallacious conclusions, and comprehensive evaluations should assess the effect of measurement error on individual results in a test. Also, differences in filtering the VO2 data within the methods could affect the ICCs. The data in the “assumed” steady-state periods and over total walking time was filtered in 10-sec interval, while the data from Kendall’s tau was filtered in 1-sec interval according to previous studies.18,47 Furthermore, speed was not directly measured in this study but calculated using walking time and distance, forcing the researchers to use an average speed. Variability of walking speed, and its effect on OCS and oxygen cost was not determinable in this study. For instance, the VO2 values of the 3-5 minutes were on average 1.0 mL O2/kg/min higher than the values obtained in the total walking time method. Participants may have walked faster in the last part of the 6MWT, similar to the study of Altenburger,48 or became more fatigued and consequently increased their OCS. What actually caused this difference in OCS remains unclear.
Summary and Conclusion The aim of this study was to evaluate the 3 most commonly used methods for calculating OCS and OC by assessing test-retest reliability and measurement error in community dwelling chronic stroke survivors during a 6MWT. The gross OC calculation over the total walking time seems to be the “best” method for reliable oxygen consumption testing considering the higher ICC (.882) and smaller absolute differences.
Conflict of Interest The authors declare that there is no conflict of interest.
References 1. Kelly-Hayes M, Beiser A, Kase CS, et al. The influence of gender and age on disability following ischemic stroke: the framingham study. J Stroke Cerebrovasc Dis 2003;12: 119-126. 2. Kramer S, Johnson L, Bernhardt J, et al. Energy expenditure and cost during walking after stroke: a systematic review. Arch Phys Med Rehabil 2016;97:61-632. https:// doi.org/10.1016/j.apmr.2015.11.007 http://www.sciencedirect.com/science/article/pii/S0003999315014744. 3. Awad LN, Palmer JA, Pohlig RT, et al. Walking speed and step length asymmetry modify the energy cost of walking after stroke. Neurorehabil Neural Repair 2015;29:416-423. https://doi.org/10.1177/1545968314552528. 4. Bernardi M, Macaluso A, Sproviero E, et al. Cost of walking and locomotor impairment. J Electromyogr Kinesiol 1999;9:149-157. 5. Brehm MA, Knol DL, Harlaar J. Methodological considerations for improving the reproducibility of walking efficiency outcomes in clinical gait studies. Gait Posture 2008;27:196-201.
ARTICLE IN PRESS 8 6. Eng JJ, Dawson AS, Chu KS. Submaximal exercise in persons with stroke: test-retest reliability and concurrent validity with maximal oxygen consumption. Arch Phys Med Rehabil 2004;85:113-118. 7. Ijmker T, Houdijk H, Lamoth CJ, et al. Energy cost of balance control during walking decreases with external stabilizer stiffness independent of walking speed. J Biomech 2013;46:2109-2114. 8. Jung T, Ozaki Y, Lai B, et al. Comparison of energy expenditure between aquatic and overground treadmill walking in people post-stroke. Physiother Res Int 2014;19:55-64. 9. Macko RF, Smith GV, Dobrovolny CL, et al. Treadmill training improves fitness reserve in chronic stroke patients. Arch Phys Med Rehabil 2001;82:879-884. 10. Macko RF, Ivey FM, Forrester LW, et al. Treadmill exercise rehabilitation improves ambulatory function and cardiovascular fitness in patients with chronic stroke: A randomized, controlled trial. Stroke 2005;36:2206-2211. 11. Olney SJ, Monga TN, Costigan PA. Mechanical energy of walking of stroke patients. Arch Phys Med Rehabil 1986;67:92-98. 12. Platts MM, Rafferty D, Paul L. Metabolic cost of over ground gait in younger stroke patients and healthy controls. Med Sci Sports Exerc 2006;38:1041-1046. 13. Stoquart G, Detrembleur C, Lejeune TM. The reasons why stroke patients expend so much energy to walk slowly. Gait Posture 2012;36:409-413. 14. van Nunen MP, Gerrits KH, de Haan A, et al. Exercise intensity of robot-assisted walking versus overground walking in nonambulatory stroke patients. J Rehabil Res Dev 2012;49:1537-1546. 15. Waters RL, Mulroy S. The energy expenditure of normal and pathologic gait. Gait Posture 1999;9:207-231. 16. Zamparo P, Francescato MP, De Luca G, et al. The energy cost of level walking in patients with hemiplegia. Scand J Med Sci Sports 1995;5:348-352. 17. Brehm MA, Becher J, Harlaar J. Reproducibility evaluation of gross and net walking efficiency in children with cerebral palsy. Dev Med Child Neurol 2007;49:45-48. 18. Schwartz MH. Protocol changes can improve the reliability of net oxygen cost data. Gait & Posture 2007;26:494-500. https://doi.org/10.1016/j.gaitpost.2007.07.014 http://www. sciencedirect.com/science/article/pii/S0966636207001865. 19. Garby L, Astrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand 1987;129:443-444. 20. Dobrovolny CL, Ivey FM, Rogers MA, et al. Reliability of treadmill exercise testing in older patients with chronic hemiparetic stroke. Arch Phys Med Rehabil 2003;84:1308-1312. 21. da Cunha-Filho IT, Henson H, Wankadia S, et al. Reliability of measures of gait performance and oxygen consumption with stroke survivors. J Rehabil Res Dev 2003;40:19. https://doi.org/10.1682/JRRD.2003.01.0019 http://www.ncbi.nlm.nih.gov/pubmed/15150717. 22. Maeda N. Energy expenditure and walking ability in stroke patients: their improvement by ankle-foot orthoses. Isokinet Exerc Sci 2009;17:57-62. 23. Whipp BJ, Wasserman K. Oxygen uptake kinetics for various intensities of constant-load work. J Appl Physiol 1972;33:351-356. 24. Schwartz MH, Koop SE, Bourke JL, et al. A nondimensional normalization scheme for oxygen utilization data. Gait Posture 2006;24:14-22. 25. Plasschaert F, Jones K, Forward M. Energy cost of walking: solving the paradox of steady-state in the presence of variable walking speed. Gait Posture 2009;29:311-316.
T. BLATTER ET AL. 26. Outermans JC, van de Port I, Kwakkel G, et al. The role of postural control in the association between aerobic capacity and walking capacity in chronic stroke: a cross-sectional analysis. Eur J Phys Rehabil Med 2018. https://doi.org/ 10.23736/S1973-9087.18.04987-0. 27. Hatano S. Experience from a multicentre stroke register: a preliminary report. Bull World Health Organ 1976;54: 541-553. 28. Holden MK, Gill KM, Magliozzi MR, et al. Clinical gait assessment in the neurologically impaired. Reliability and meaningfulness. Phys Ther 1984;64:35-40. 29. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-198. 30. Back P, van der Velden H, Schepers V, et al. De pontane communicatieschaal van het utrechts communicatie onderzoek: Een valide screener van communicatieve vaardigheden. Revalidata 2006;28:5-8. 31. Flansbjer UB, Holmback AM, Downham D, et al. Reliability of gait performance tests in men and women with hemiparesis after stroke. J Rehabil Med 2005;37:75-82. 32. Stookey AD, McCusker MG, Sorkin JD, et al. TestRetest reliability of portable metabolic monitoring after disabling stroke. Neurorehabil Neural Repair 2013;27:872-877. https://doi.org/10.1177/1545968313497103 http://journals.sagepub.com/doi/full/10.1177/1545968313497103. 33. Demers C, McKelvie RS, Negassa A, et al. Reliability, validity, and responsiveness of the six-minute walk test in patients with heart failure. Am Heart J 2001;142:698-703. https://doi.org/10.1067/mhj.2001.118468 http://www. sciencedirect.com/science/article/pii/S0002870301764113. 34. Dunn A, Marsden DL, Nugent E, et al. Protocol variations and six-minute walk test performance in stroke survivors: a systematic review with meta-analysis. Stroke Res Treat 2015;2015:1-28. https://doi.org/ 10.1155/2015/484813 http://search.proquest.com/docview/1709484551. 35. Liu J, Drutz C, Kumar R, et al. Use of the six-minute walk test poststroke: is there a practice effect. Arch Phys Med Rehabil 2008;89:1686-1692. https://doi.org/10.1016/j. apmr.2008.02.026 http://www.sciencedirect.com/science/article/pii/S0003999308004280. 36. ATS statement. Guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;166:111 http://www. ncbi.nlm.nih.gov/pubmed/12091180. 37. Balady GJ, Arena R, Sietsema K, et al. Clinician’s guide to cardiopulmonary exercise testing in adults: a scientific statement from the American heart association. Circulation 2010;122:191-225. 38. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982;14:377-381. 39. Garby L, Astrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand 1987;129:443-444. 40. Dawes H, Collett J, Ramsbottom R, et al. Measuring oxygen cost during level walking in individuals with acquired brain injury in the clinical setting. J Sports Sci Med 2004;3:76-82. 41. Cicchetti DV. Guidelines criteria and rules of thumb for evaluating normed and standardized assessment instrument in psychology. Psychol Assess 1994;6:284-290. https://doi.org/10.1037/1040-3590.6.4.284. 42. de Vet HC, Terwee CB, Knol DL, et al. When to use agreement versus reliability measures. J Clin Epidemiol 2006;59:1033-1039.
ARTICLE IN PRESS CALCULATING OCS AND OC DURING WALKING IN CHRONIC STROKE SURVIVORS 43. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007;60:34-42. 44. Fulk GD, Echternach JL, Nof L, et al. Clinometric properties of the six-minute walk test in individuals undergoing rehabilitation poststroke. Physiother Theory Pract 2008;24:195-204. 45. Perera S, Mody SH, Woodman RC, et al. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc 2006;54:743-749. https://doi.org/10.1111/j.1532-5415.2006.00701.x http:// onlinelibrary.wiley.com/doi/10.1111/j.1532-5415.2006.00701. x/abstract.
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46. Punt M, van Alphen B, van de Port I G, et al. Clinimetric properties of a novel feedback device for assessing gait parameters in stroke survivors. J Neuroeng Rehabil 2014;11:3-30. 47. Plasschaert F, Jones K, Forward M. Energy cost of walking: a comparison of two recognised methods for defining steady-state in a group of unimpaired children and children with cerebral palsy. Gait Posture 2010;31:537-539. 48. Altenburger PA, Dierks TA, Miller KK, et al. Examination of sustained gait speed during extended walking in individuals with chronic stroke. Arch Phys Med Rehabil 2013;94:2471-2477.
Reproducibility of Different Methodologies to Calculate Oxygen Consumption and Oxygen Cost During Walking in Chronic Stroke Survivors Tim Blatter, MSc, Jacqueline Outermans, PhD, PT, Michiel Punt, PhD, and Harriet Wittink, PhD, PT
Objective: The most common methods to calculate energy costs are based on measured oxygen uptake during walking a standardized distance or time. Unfortunately, it is unclear which method is most reliable to determine energy cost of walking in stroke survivors. The objective of this study was to evaluate the 3 most commonly used methods for calculating oxygen consumption and -cost by assessing test-retest reliability and measurement error in community dwelling chronic stroke survivors during a 6 Minute Walk Test. Methods: In this secondary analysis of a longitudinal study, reproducibility of the outcome of walking distance, walking speed, oxygen consumption and oxygen cost from 3 methods (Kendall’s tau, assumed steady-state and total walking time oxygen consumption) were determined using Intraclass Correlation Coefficient, Standard Error of Measurement and Smallest Detectable Change. Results: 20 from the 31 participants successfully performed the 6 minute walk test-retest within a timeframe of 1 month. Within the 2 tests the reproducibility of walking distance and walking speed was high. The 3 methods to determine reproducibility for oxygen cost and oxygen consumption were considered good (Kendall’s tau), good (assumed steady-state) and excellent (total walking time). Conclusions: The method using oxygen consumption and -cost over the total walking time resulted in the highest reproducibility considering the Intraclass Correlation Coefficient, its 95% Confidence Interval, and smaller absolute differences. Key Words: Test-retest reliability—oxygen cost—oxygen consumption—6MWT © 2020 Elsevier Inc. All rights reserved.
Introduction For nearly half the people who survive a stroke, hemiparesis is the most common disability 3 months after the event.1 Post stroke muscle impairments (eg, spasticity, abnormal muscle activation patterns, and reduced oxygen uptake capacity) have been associated with higher energy demands during walking.2 A higher oxygen cost of walking post stroke has been linked to reduced From the Research Group Lifestyle and Health, Utrecht University of Applied Sciences, Utrecht, the Netherlands. Received June 5, 2019; revision received November 5, 2019; accepted December 31, 2019. Address correspondence to Tim Blatter MSc, Research Group Lifestyle and Health, Institute of Movement Studies, The University of Applied Science Utrecht, Postbus 12011, 3501 AA, Utrecht, the Netherlands. E-mails: [email protected], [email protected]. 1052-3057/$ - see front matter © 2020 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jstrokecerebrovasdis.2020.104637
walking performance and reduced participation in the community.3 Energy demand during hemiparetic gait has been explored in a broad range of studies using different methods.4-16 The most common methods to calculate energy costs are based on measured oxygen uptake during walking a standardized distance or time. Both oxygen consumption (OCS) and oxygen cost (OC) describe the amount of oxygen that is consumed during the test. First, the definition of oxygen consumption is the transportation and utilization of oxygen in a person during exercise and is expressed in VO2 mL O2/kg/ min.5,17-19 Second, oxygen cost is calculated as oxygen consumption during walking divided by walking speed, resulting in a relative VO2 cost per body weight per meter (mL O2/kg/m).17,18 Both oxygen consumption and -cost can be expressed as a gross or net term. Gross OC is the total amount of oxygen expended for a specific activity, while net oxygen consumption is computed as gross oxygen consumption minus the individual’s
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resting oxygen consumption. This term is used to compare the energy cost of specific activities, such as walking, cycling and climbing stairs. A recent review on energy cost of walking in people post stroke2 reported a wide variety of methods between studies in the calculations of oxygen consumption and oxygen cost. In most of the studies, oxygen consumption was measured during steady-state conditions within walking time,6-9,12,20 others used the oxygen consumption and cost over the total walking time.21,22 A standard protocol to determine steady-state in walking among chronic stroke survivors has not been established yet. One of the methods used in previous studies to determine the steady-state as an average VO2 in a time frame of 3 minutes at the end of a 6 minute walk test (6MWT),17 according to an earlier definition of steady-state in healthy subjects.23 Others defined the achievement of a stable VO2-state during a 6MWT as the steady-state8,9,20 but none of these studies used cut-off values or thresholds within the measured parameters. Two earlier studies24,25 used the Kendall’s Tau approach to calculate the occurrence of a steady-state with the use of breath-by-breath data. The authors of the review2 concluded there is an obvious need for a clear definition of steady-state and consistent methods of identifying the steady-state condition during walking post stroke to establish a reproducible method in calculating the oxygen cost during walking. Given the need to study energy cost of walking in stroke survivors, the lack of methodological consistency and knowledge which method is most reliable to determine energy cost of walking, this study aimed to evaluate 3 of the most commonly used methods by assessing testretest reliability and measurement error of energy cost in community dwelling chronic stroke survivors during a 6MWT. Findings from this study can be used in aerobic capacity progress performance evaluation of chronic stroke survivors.
Materials and Methods Study Design This study is a secondary analysis of a cross-sectional study26 on the relation between aerobic capacity and walking capacity in chronic stroke survivors. The present study concerns a test-retest study on metabolic responses in chronic stroke survivors while performing the 6MWT. In the cross-sectional study,26 the participants were tested twice within a timeframe of 1 month. Three physical therapists, experienced in stroke rehabilitation and exercise testing, conducted the assessments. Inter-assessor agreement was optimized during 3 2-hour sessions. The data were collected during 2 sessions.
In this study, no measurements were done, the results that are described in this study are gathered from the cross-sectional study.26 The author of this secondary analysis screened the data from the cross-sectional study to create a complete data-set to answer his research question.
Human Committee Approval The Medical Ethics Review Committee of the University Medical Centre Utrecht (ID041), chaired by Dr. P.D. Siersema, approved the research protocol (ID11/204) in December 2011. The cross-sectional study26 was conducted in accordance with the declaration of Helsinki. All participants provided written consent.
Participants The participants were recruited from Dutch rehabilitation centers, daycare centers, and private physical therapy practices. Their attending physical therapists established potential eligibility and willingness to participate in the study and asked for permission to pass contact data on to the researcher. The researcher contacted the potential participant for an initial appointment to assess for inclusion and exclusion criteria and obtain informed consent. The inclusion criteria were: (1) diagnosed stroke according to the WHO definition,27 (2) minimal 3 months post stroke, (3) age over 18 years and (4) the ability to walk independently under supervision, i.e., Functional Ambulation Categories (FAC)-score of 3 and above.28 The presence of a severe cognitive disorder, i.e., Mini Mental State Examination greater than 24 points,29 severe cardiovascular disease and severe communicative disorder (Utrecht Communication State < 4 points)30 were the exclusion criteria for the study.26
Variables Demographics and participants’ characteristics included age, gender, height and weight, time since onset stroke, hemiplegic side, walking ability and stroke severity. The FAC28 describes the ability of a person to walk independently in categories from 0; not able to walk to 5; able to walk independently on level and nonlevel surfaces. The FAC-score is mostly determined by their attending physical therapist and assessed during the 6MWT. The Motricity Index (MI) assesses functional strength and a person’s ability for voluntary knee extension, hip flexion and ankle dorsiflexion. The MI is reliable and valid for stroke survivors.31,32 In this study, the researcher positioned the joint and asked the participant to maintain position while the researcher tried slowly to move the joint in opposite direction. The scores for each movement vary from 0 to 33 points for each dimension, indicating no counter activity (0) to maximal counter strength (33). At maximal scores, 1 point is added to a total score of 100 points.
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The main outcome variables of the study were: walking distance, walking speed, oxygen consumption, and oxygen cost.
Walking Distance and Walking Speed Walking distance and walking speed were assessed with the 6MWT. The 6MWT is a valid and reliable test for the stroke population.6,16,31-35 We performed the 6MWT according to the standardized instructions of the American Thoracic Society Guidelines 36 on a 20-meter straight course. The total distance covered was determined by counting the laps and adding the surplus.
Oxygen Consumption and Oxygen Costs The participants were requested not to eat, drink caffeine or smoke at least 2 hours prior to the 6MWT because this influences exercise capacity and therefore threatens reproducibility. While executing the 6MWT, respiratory gas exchange was measured with a portable metabolic system (Cortex Metamax B3-R2, Cortex Biophysik GmbH, Leipzig, Germany). This system contains a mask which allows expired gas to pass through a flowmeter, oxygen analyzer, and carbon dioxide analyzer. A wireless connection (Bluetooth) with a computer supported the possibility to wirelessly calculate the breath-by-breath minute ventilation (VE), oxygen consumption (VO2), carbon dioxide production (VCO2) and respiratory exchange ratio from conventional equations. Preceding and throughout the 6MWT, an electrocardiogram was obtained with a mobile 12-channel system (Custocor Custo Med, Ottobrunn, Germany). The electrocardiogram signal was screened for ventricular arrhythmia and/or exercise-induced ischemia, i.e., ST-segment depression greater than .10 mV (1mm) for 80 ms.37 Prior to the 6MWT, blood pressure was measured with an OMRON M10-IT device (OMRON Europe, Hoofddorp, Netherlands). The 6MWT was only started if blood pressure (BP) values were below 180 mm Hg systolic and 100 mm Hg diastolic. Before testing started, the participant wore the facemask while seated to become familiarized with the equipment. In the last minute of this procedure, the oxygen consumption was measured to ensure a baseline measurement. Directly following the 6MWT, blood pressure was measured again and the rate of perceived exertion was collected using the 6-20 BORG-scale.38 Oxygen consumption was measured breath by breath and afterwards averaged in 1-second intervals for the Kendall’s Tau steady-state18 and 10-second intervals for all other methods.
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Data Analysis Calculation Oxygen Consumption and Oxygen Cost We performed 3 sets of calculations for gross and net oxygen consumption from oxygen consumption during the 6MWT; Method 1. We used Kendall’s tau to determine steady-state during the entire 6MWT, method 2. We calculated the mean oxygen consumption during minute 3 to 5 as we assumed this time frame to represent a steadystate and method 3. We calculated the mean oxygen consumption over the total walking time.
Method 1. Oxygen Consumption during Steady-state Kendall’s Tau A custom written MATLAB (MATLAB and Statistics Toolbox Release 2015b, The MathWorks, Inc., Natick, MA) script determined Kendall’s tau as described by Schwartz et al.18 Briefly, Kendall’s tau was calculated for the breathby-breath sampled VO2 versus time data (in 1-second interval) that occurs within a sliding window of the raw data. Steadiness of the VO2 (for the data point that corresponds to the mid-point of the sliding window) was identified when the probability of t = 0 was less than 0.10 in a 2-tailed test (Z-score). A steady-state was determined if the duration of the Z-scores was at least 1 minute.
Method 2. Oxygen Consumption and Oxygen Costs during the Total Walking Time To determine the oxygen consumption during the assumed steady-state between minute 3 and 5 within the 6MWT5,9,20,39, the VO2 of the participant during this timeframe was averaged over 13 (2*6+1) data points using the 10 second time-interval. The breath by breath data was filtered in 10 second intervals during the total 6 minutes walking time of the test. This generated a total of 36 VO2data points. Oxygen consumption was then determined as the mean of these data points, while the oxygen cost was calculated as oxygen consumption divided by walking speed (the walking distance divided by time).
Method 3. Gross and Net Oxygen Consumption or Oxygen Cost in All Calculations As described in earlier studies5,17,18,40 the net oxygen consumption was calculated as the measured gross oxygen consumption during steady-state or total walking time minus the resting oxygen consumption. Due to the difference in duration of resting phase that each participant needed to be familiarized with the mask of the portable metabolic system in this study, the last minute of the resting phase was used to calculate resting oxygen consumption for all calculations. Net oxygen cost was calculated by
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Figure 1. Flowchart participants. The clinical characteristics of the remaining subjects are shown in Table 1 and all variables were normally distributed.
dividing the net oxygen consumption by the average walking speed of the participant during the 6MWT.
Statistical Analysis Descriptives Descriptive statistics were used to report the demographic and clinical characteristics of the sample. The symmetry of the distribution of all continuous variables was assessed using the Shapiro-Wilk test. Thereafter percentages, means and standard deviations were calculated, and nominal data were categorized.
Reproducibility IBM SPSS version 23 was used to determine distribution, mean values and standard deviation. The reproducibility of the OC and OCS calculations of the test-retest was calculated in SPSS with an ICC two-way random single measure with absolute agreement (ICCagreement 2.1), the standard error of measurement (SEM) and the smallest detectable change (SDC). The ICCagreement2.1 is considered poor when it is below .40, fair between .41 and .59, good when its value is .60-.74 and excellent when it exceeds .75.41 The SEM and SDC are both expressed in actual measurement units and therefore useful in individual level evaluations. SEM was calculated using the following formula: SEMagre pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi ement ¼ s ð1ICCÞ where s is the pooled standard deviation of test and retest scores. SEM can be calculated as SEMagreement or SEMconsistency42 SEMagreement takes the systematic difference between test and retest into account
while the SEMconsistency ignores systematic differences. We therefore used SEMagreement in all calculations. The SEM can be convertedpinto ffiffiffi the smallest detectable change (SDC) (SDC ¼ 1:96 2 SEM) which reflects the smallest within-person change in score that, with 95% confidence, can be interpreted as a ‘‘real’’ change, above measurement error, in 1 individual (SDCind).43
Results Participants As shown in Figure 1, there were 62 eligible participants for the cross-sectional study. Four participants decided not to participate. 21 participants preferred not to be tested on 2 separate occasions and 6 participants missed the second session. 31 participants successfully performed the 6MWT twice, unfortunately 3 participants were rescheduled outside the 1-month timeframe between test and re-test. Test-forms from 5 participants were missing data after testing and in three 6MWTs an error occurred in the indirect metabolic measurement due to leakage in the mask, resulting in an invalid measurement of oxygen consumption. All our participants were experienced in walking the 6MWT, hereby precluding a practice effect. Demographic characteristics of our participants are shown in Table 1. The mean BMI score of these participants was 27.9 kg/m2, 5 participants were below a BMI of 25 (normal weight), 9 participants between 25 and 30 (overweight) and 6 participants above 30 (obese). Regarding co-morbidity from these participants, 13 did not suffer from a (known) co-
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morbidity, 2 participants had Diabetes type 2, 1 participant had Cardiovascular Disease, 1 participant had epilepsy, 1 participant had Goiter, 1 participant suffered from lowered kidney function and 1 participant had muscle dystrophy in the left ankle. Most of the participants still went to the physical therapist (median: 2 hours or more) during the cross-sectional study.
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6MWT and the oxygen cost was the result of the average VO2 during the total walking time. The reliability of these results were both considered excellent. The higher 95% CIs in the OC net and gross calculation (resp. .569-.892 and .727-.952) confirm the higher reliability of the estimates within the group, comparing to the other results.
Discussion Oxygen Consumption and Oxygen Cost The measured and calculated mean results of the 6MWT are described below in Table 2. The mean walking distance was 383.38 meters in the first test (T1) and 391.30 meters in the second test (T2). Average speed (m/s) was calculated using the distance covered divided by 360 seconds. The mean difference in speed between T1 and T2 was .01 m/s. The rate of perceived exertion on BORGscale had a median score of 13 in both tests. The individual and mean OCS during the 6MWT are shown in Figure 2. There were large individual differences in OCS, which ranged after 3 minutes walking from 10 mL O2/ kg/min to 27 mL O2/kg/min in both tests (see Fig 2). There is 1 outlier clearly visible in both tests, this participant performed the first 6MWT with an average OCS of 22 mL O2/kg/min and the second 6MWT with an average OCS of 24 mL O2/kg/min, while the rest performed the test close to 14 mL O2/kg/min. In T2 the average OCS within the group was similar to T1, while the standard deviation was larger in the second test. From the total of 40 measurements among 20 participants, 13 participants reached a steady-state according to Kendall’s tau in both T1 and T2 with a duration of at least 1 minute. Their average OCS during these steady-states was 15.5 mL O2/kg/min in T1 and 16.9 mL O2/kg/min in T2; see Table 2. No participant reached steady-state at the same moment in both tests according to Kendall’s tau. During the assumed steady-state in minute 3 to minute 5 the average OCS was 15.36 mL O2/kg/min and 15.82 mL O2/kg/min. When OCS during total walking time was calculated the participants consumed 14.17 mL O2/kg/min oxygen in T1 and 14.90 mL O2/kg/min in T2. For gross oxygen cost (OC) the means of both trials were .24 mL O2/kg/m.
Reproducibility The results of the reproducibility calculations are described in Table 2. The ICCs for the steady-state (SS) calculations according to Kendall’s Tau were .612 and considered good.41 The ICCs for the assumed steady-state net and gross were higher (resp. .728 and .805) as well for OCS measured during total walking time (resp. .728 and .813) were considered respectively good and excellent. The highest ICCs (resp. .805 and .882) were found when the oxygen cost of walking was calculated with the assumption that no steady-state was reached during the
The use of steady-state as a method to determine oxygen consumption chronic stroke survivors in walking is common practice in most previous studies.10,12,20 The stable cardiorespiratory outcome measures and continuous walking speed can give reliable information about the oxygen consumption and oxygen cost, provided that task is easy enough for the participant to maintain a steadystate condition. Accelerating, decelerating and turning causing balance difficulties, change of muscle activity and intensity could complicate these objectives, especially in chronic stroke survivors. With dozens of different methods to determine oxygen consumption in walking for stroke survivors, the results are difficult to combine and hard to interpret. As described in the introduction, a standard protocol to determine steady-state in walking among chronic stroke survivors has not established yet. This is the first study that determined which method is “best” for calculating oxygen consumption in patients with chronic post stroke hemiparesis. We defined the most reproducible method as the “best method”. Overall, steady-states were difficult to establish, calling into question previous studies in which assumptions were made such as that after 3 minutes walking a steady-state should be visible10 or to expect a plateau value approximately 85% of age-predicted heart rate maximum value within the first 2 minutes.6 Equally, we found that the algorithm described by Schwartz24 to determine a steady-state digitally did not provide a solution for measuring steadystate. None of the 20 participants reached a similar steady-state in both trials and for a number of participants no steady-state could be calculated. Therefore, the reproducibility results according to Kendall’s Tau shown in Table 2 represent a smaller group within our participants, with a lower ICC and greater SEM and SDC compared to the other 2 methods. Our findings suggest that on group level the participants had a similar pattern in oxygen consumption during the 6MWT. However, the closer a method tried to determine the oxygen consumption on an individual level by identifying the steadiness in VO2 measurement, the smaller the group of participants that achieved steadiness got and the lower its reproducibility became. Therefore, the method that used the overall data and not steady-state data, showed the highest reproducibility. The second method, showing lower reproducibility, assumes a steady-state after 3 minutes walking and uses a shorter interval to average oxygen consumption. The third
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Table 1. Mean and SD and between group differences in demographic and stroke specific characteristics (N = 20) Demographic characteristics
Mean (SD)
Range
Age (years) Height (m) Weight (kg) BMI Male (%) Time since onset (mean months) Walking support (number)
59.4 (10.1) 1.71 (.09) 81.7 (20.00) 27.9 (6.0) 55% 55.65 (49.00) Shoe: 7 Cane: 5 AFO: 2 77.1 (23.5) 3: 9.1% 4: 18.2% 5: 63.6%
41-79 1.55-1.86 50-108 19.5-43.3
Motricity index (0-100) FAC-score (%)
6-170
9-100
Abbreviations: FAC, functional ambulation categories; SD, standard deviation.
(Kendall’s tau) uses 1-sec interval and VO2 data showed the lowest reproducibility here. The lack of steadiness in VO2 we found in our sample, when the second and third method were applied, could imply that the participants were not able to walk the 6MWT with a steady-state in VO2. This may have related to the straight 20 meter course we used in our protocol and the accelerating and decelerating necessary to perform the test.
Most of our participants live a more sedentary life compared to their healthy peers, maybe due to the fact that their walking demands higher energy.2 The result of this lifestyle is shown in Table 1, the mean BMI score of our participants was over 25. Although this is an unfortunate fact, it is not unique. In similar previous studies,6,20,32 the majority of participants has a sufficiently high BMI to be classified as “overweight” or “obese”. One of the main objectives of most physical therapists is to motivate stroke survivors to participate in a more active lifestyle. The ICCs for walking distance and speed in this study were similar to previous studies.6,12,44,45 The highest ICC within the 3 methods was found in gross OC calculated over the total walking time. The 95% CI was in this method also the narrowest, suggesting the most reliable estimation of the methods that were studied. This method had a comparable result as in a previous study5,17,18,21 the highest ICC, a small SEM and SDC. Also, Brehm17 already established that gross OC is more reliable than net OC, first because net OC varied more for people with gait impairments than for healthy subjects and second the measurements of net OC became more variable as the resting period increased, especially for patients. Only a few studies described the SEMs and SDCs of the 6MWT measurements in chronic stroke patients. The SEM in walking distance is similar to earlier studies.44,46 One study in 2003,21 with only 9 stroke survivors, calculated the oxygen cost of walking (mL O2/kg/m) and reported
Table 2. Clinical outcomes and reproducibility of the 3 methods to determine steady-states Measurement Distance (m) Speed (m/s) Rest OCS (mL O2/kg/min) Steady-state Kendall’s tau (N = 13) SS OCS (mL O2/kg/min) Steady-state 3-5min (N = 20) Gross 2 min OCS (mL O2/kg/min) Net 2 min OCS (mL O2/kg/min) Total Walking Time (N = 20) Gross OCS (mL O2/kg/min) Net OCS (mL O2/kg/min) Gross OC (mL O2/kg/m) Net OC (mL O2/kg/m)
95% CI
SEM
SDC
.969
.923-.987
22.92
54.78
.968
.922-.987
.06
.15
.593
.229-.814
.62
.08
3.50 3.30
.612
136-.862
2.12
5.06
15.58 15.38 11.86 11.41
3.44 4.24 3.23 3.77
.805
571-.918
1.70
4.07
.728
434-.882
1.83
4.38
14.28 14.62 10.49 10.65 .25 .25 .18 .18
2.94 3.70 2.73 3.27 .09 .07 .06 .05
.813
590-.921
1.45
3.45
.727
425-.883
.03
.06
.882
727-.952
1.57
3.76
.805
569-.892
.03
.05
Mean
Std. dev.
ICC2,1
T1 T2 T1 T2 T1 T2
376.91 382.15 1.05 1.06 3.72 3.97
132.87 127.43 .37 .35 .87 1.05
T1 T2
15.61 16.44
T1 T2 T1 T2 T1 T2 T1 T2 T1 T2 T1 T2
Abbreviations: OC, oxygen cost; OCS, oxygen consumption; SS, steady-state.
ARTICLE IN PRESS CALCULATING OCS AND OC DURING WALKING IN CHRONIC STROKE SURVIVORS
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Figure 2. VO2 over time measurement 6MWT first and second trial.
similar SEMs and SDCs (resp. .03 and .06) as found in this study (resp. .03 and .05).
Limitations There are some limitations to this present study that should be considered when interpreting the results. First, the small sample size resulted in a large variation, hereby causing a broad 95% CI and a less precise ICC. It is common to use the ICC calculation to determine the test-retest reliability. An earlier study31 suggested that solely using the ICC for the evaluation of reliability (distance in meters of the 6MWT in their case) can lead to fallacious conclusions, and comprehensive evaluations should assess the effect of measurement error on individual results in a test. Also, differences in filtering the VO2 data within the methods could affect the ICCs. The data in the “assumed” steady-state periods and over total walking time was filtered in 10-sec interval, while the data from Kendall’s tau was filtered in 1-sec interval according to previous studies.18,47 Furthermore, speed was not directly measured in this study but calculated using walking time and distance, forcing the researchers to use an average speed. Variability of walking speed, and its effect on OCS and oxygen cost was not determinable in this study. For instance, the VO2 values of the 3-5 minutes were on average 1.0 mL O2/kg/min higher than the values obtained in the total walking time method. Participants may have walked faster in the last part of the 6MWT, similar to the study of Altenburger,48 or became more fatigued and consequently increased their OCS. What actually caused this difference in OCS remains unclear.
Summary and Conclusion The aim of this study was to evaluate the 3 most commonly used methods for calculating OCS and OC by assessing test-retest reliability and measurement error in community dwelling chronic stroke survivors during a 6MWT. The gross OC calculation over the total walking time seems to be the “best” method for reliable oxygen consumption testing considering the higher ICC (.882) and smaller absolute differences.
Conflict of Interest The authors declare that there is no conflict of interest.
References 1. Kelly-Hayes M, Beiser A, Kase CS, et al. The influence of gender and age on disability following ischemic stroke: the framingham study. J Stroke Cerebrovasc Dis 2003;12: 119-126. 2. Kramer S, Johnson L, Bernhardt J, et al. Energy expenditure and cost during walking after stroke: a systematic review. Arch Phys Med Rehabil 2016;97:61-632. https:// doi.org/10.1016/j.apmr.2015.11.007 http://www.sciencedirect.com/science/article/pii/S0003999315014744. 3. Awad LN, Palmer JA, Pohlig RT, et al. Walking speed and step length asymmetry modify the energy cost of walking after stroke. Neurorehabil Neural Repair 2015;29:416-423. https://doi.org/10.1177/1545968314552528. 4. Bernardi M, Macaluso A, Sproviero E, et al. Cost of walking and locomotor impairment. J Electromyogr Kinesiol 1999;9:149-157. 5. Brehm MA, Knol DL, Harlaar J. Methodological considerations for improving the reproducibility of walking efficiency outcomes in clinical gait studies. Gait Posture 2008;27:196-201.
ARTICLE IN PRESS 8 6. Eng JJ, Dawson AS, Chu KS. Submaximal exercise in persons with stroke: test-retest reliability and concurrent validity with maximal oxygen consumption. Arch Phys Med Rehabil 2004;85:113-118. 7. Ijmker T, Houdijk H, Lamoth CJ, et al. Energy cost of balance control during walking decreases with external stabilizer stiffness independent of walking speed. J Biomech 2013;46:2109-2114. 8. Jung T, Ozaki Y, Lai B, et al. Comparison of energy expenditure between aquatic and overground treadmill walking in people post-stroke. Physiother Res Int 2014;19:55-64. 9. Macko RF, Smith GV, Dobrovolny CL, et al. Treadmill training improves fitness reserve in chronic stroke patients. Arch Phys Med Rehabil 2001;82:879-884. 10. Macko RF, Ivey FM, Forrester LW, et al. Treadmill exercise rehabilitation improves ambulatory function and cardiovascular fitness in patients with chronic stroke: A randomized, controlled trial. Stroke 2005;36:2206-2211. 11. Olney SJ, Monga TN, Costigan PA. Mechanical energy of walking of stroke patients. Arch Phys Med Rehabil 1986;67:92-98. 12. Platts MM, Rafferty D, Paul L. Metabolic cost of over ground gait in younger stroke patients and healthy controls. Med Sci Sports Exerc 2006;38:1041-1046. 13. Stoquart G, Detrembleur C, Lejeune TM. The reasons why stroke patients expend so much energy to walk slowly. Gait Posture 2012;36:409-413. 14. van Nunen MP, Gerrits KH, de Haan A, et al. Exercise intensity of robot-assisted walking versus overground walking in nonambulatory stroke patients. J Rehabil Res Dev 2012;49:1537-1546. 15. Waters RL, Mulroy S. The energy expenditure of normal and pathologic gait. Gait Posture 1999;9:207-231. 16. Zamparo P, Francescato MP, De Luca G, et al. The energy cost of level walking in patients with hemiplegia. Scand J Med Sci Sports 1995;5:348-352. 17. Brehm MA, Becher J, Harlaar J. Reproducibility evaluation of gross and net walking efficiency in children with cerebral palsy. Dev Med Child Neurol 2007;49:45-48. 18. Schwartz MH. Protocol changes can improve the reliability of net oxygen cost data. Gait & Posture 2007;26:494-500. https://doi.org/10.1016/j.gaitpost.2007.07.014 http://www. sciencedirect.com/science/article/pii/S0966636207001865. 19. Garby L, Astrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand 1987;129:443-444. 20. Dobrovolny CL, Ivey FM, Rogers MA, et al. Reliability of treadmill exercise testing in older patients with chronic hemiparetic stroke. Arch Phys Med Rehabil 2003;84:1308-1312. 21. da Cunha-Filho IT, Henson H, Wankadia S, et al. Reliability of measures of gait performance and oxygen consumption with stroke survivors. J Rehabil Res Dev 2003;40:19. https://doi.org/10.1682/JRRD.2003.01.0019 http://www.ncbi.nlm.nih.gov/pubmed/15150717. 22. Maeda N. Energy expenditure and walking ability in stroke patients: their improvement by ankle-foot orthoses. Isokinet Exerc Sci 2009;17:57-62. 23. Whipp BJ, Wasserman K. Oxygen uptake kinetics for various intensities of constant-load work. J Appl Physiol 1972;33:351-356. 24. Schwartz MH, Koop SE, Bourke JL, et al. A nondimensional normalization scheme for oxygen utilization data. Gait Posture 2006;24:14-22. 25. Plasschaert F, Jones K, Forward M. Energy cost of walking: solving the paradox of steady-state in the presence of variable walking speed. Gait Posture 2009;29:311-316.
T. BLATTER ET AL. 26. Outermans JC, van de Port I, Kwakkel G, et al. The role of postural control in the association between aerobic capacity and walking capacity in chronic stroke: a cross-sectional analysis. Eur J Phys Rehabil Med 2018. https://doi.org/ 10.23736/S1973-9087.18.04987-0. 27. Hatano S. Experience from a multicentre stroke register: a preliminary report. Bull World Health Organ 1976;54: 541-553. 28. Holden MK, Gill KM, Magliozzi MR, et al. Clinical gait assessment in the neurologically impaired. Reliability and meaningfulness. Phys Ther 1984;64:35-40. 29. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189-198. 30. Back P, van der Velden H, Schepers V, et al. De pontane communicatieschaal van het utrechts communicatie onderzoek: Een valide screener van communicatieve vaardigheden. Revalidata 2006;28:5-8. 31. Flansbjer UB, Holmback AM, Downham D, et al. Reliability of gait performance tests in men and women with hemiparesis after stroke. J Rehabil Med 2005;37:75-82. 32. Stookey AD, McCusker MG, Sorkin JD, et al. TestRetest reliability of portable metabolic monitoring after disabling stroke. Neurorehabil Neural Repair 2013;27:872-877. https://doi.org/10.1177/1545968313497103 http://journals.sagepub.com/doi/full/10.1177/1545968313497103. 33. Demers C, McKelvie RS, Negassa A, et al. Reliability, validity, and responsiveness of the six-minute walk test in patients with heart failure. Am Heart J 2001;142:698-703. https://doi.org/10.1067/mhj.2001.118468 http://www. sciencedirect.com/science/article/pii/S0002870301764113. 34. Dunn A, Marsden DL, Nugent E, et al. Protocol variations and six-minute walk test performance in stroke survivors: a systematic review with meta-analysis. Stroke Res Treat 2015;2015:1-28. https://doi.org/ 10.1155/2015/484813 http://search.proquest.com/docview/1709484551. 35. Liu J, Drutz C, Kumar R, et al. Use of the six-minute walk test poststroke: is there a practice effect. Arch Phys Med Rehabil 2008;89:1686-1692. https://doi.org/10.1016/j. apmr.2008.02.026 http://www.sciencedirect.com/science/article/pii/S0003999308004280. 36. ATS statement. Guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;166:111 http://www. ncbi.nlm.nih.gov/pubmed/12091180. 37. Balady GJ, Arena R, Sietsema K, et al. Clinician’s guide to cardiopulmonary exercise testing in adults: a scientific statement from the American heart association. Circulation 2010;122:191-225. 38. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982;14:377-381. 39. Garby L, Astrup A. The relationship between the respiratory quotient and the energy equivalent of oxygen during simultaneous glucose and lipid oxidation and lipogenesis. Acta Physiol Scand 1987;129:443-444. 40. Dawes H, Collett J, Ramsbottom R, et al. Measuring oxygen cost during level walking in individuals with acquired brain injury in the clinical setting. J Sports Sci Med 2004;3:76-82. 41. Cicchetti DV. Guidelines criteria and rules of thumb for evaluating normed and standardized assessment instrument in psychology. Psychol Assess 1994;6:284-290. https://doi.org/10.1037/1040-3590.6.4.284. 42. de Vet HC, Terwee CB, Knol DL, et al. When to use agreement versus reliability measures. J Clin Epidemiol 2006;59:1033-1039.
ARTICLE IN PRESS CALCULATING OCS AND OC DURING WALKING IN CHRONIC STROKE SURVIVORS 43. Terwee CB, Bot SD, de Boer MR, et al. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol 2007;60:34-42. 44. Fulk GD, Echternach JL, Nof L, et al. Clinometric properties of the six-minute walk test in individuals undergoing rehabilitation poststroke. Physiother Theory Pract 2008;24:195-204. 45. Perera S, Mody SH, Woodman RC, et al. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc 2006;54:743-749. https://doi.org/10.1111/j.1532-5415.2006.00701.x http:// onlinelibrary.wiley.com/doi/10.1111/j.1532-5415.2006.00701. x/abstract.
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46. Punt M, van Alphen B, van de Port I G, et al. Clinimetric properties of a novel feedback device for assessing gait parameters in stroke survivors. J Neuroeng Rehabil 2014;11:3-30. 47. Plasschaert F, Jones K, Forward M. Energy cost of walking: a comparison of two recognised methods for defining steady-state in a group of unimpaired children and children with cerebral palsy. Gait Posture 2010;31:537-539. 48. Altenburger PA, Dierks TA, Miller KK, et al. Examination of sustained gait speed during extended walking in individuals with chronic stroke. Arch Phys Med Rehabil 2013;94:2471-2477.