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Reliability of the walking energy cost test and the six-minute walk test in boys with Duchenne muscular dystrophy J.C.E. Kempen a, J. Harlaar a, A.J. van der Kooi b, I.J.M. de Groot c, J.C. van den Bergen d, E.H. Niks d, J.J.G.M. Verschuuren d, M.A. Brehm a,e,⇑ a
Department of Rehabilitation Medicine and MOVE Research Institute, VU University Medical Center, Amsterdam, The Netherlands b Department of Neurology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands c Department of Rehabilitation, Radboud University Medical Center, Nijmegen, The Netherlands d Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands e Department of Rehabilitation, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Received 20 July 2013; received in revised form 6 November 2013; accepted 27 November 2013
Abstract The walking energy cost test (WECT) is a useful tool when measuring ambulatory function in children with motor disorders. However, data on the reliability of this test in Duchenne muscular dystrophy (DMD) is not available. In this study we established the reliability of the WECT and the commonly used six-minute walk test (6MWT) in 19 boys with DMD, aged 6–12 years. Participants performed the WECT and 6MWT twice within three weeks. Reliability was determined for walking distance (D, m) and gross energy cost (EC, J kg1 m1), using the intraclass correlation coefficient (ICC2,1) and smallest detectable change (SDC). Reliability for walking distance was good, with an ICC of 0.92 [95% CI: 0.81–0.97] and 0.83 [CI: 0.53–0.94] for the 6MWT and WECT, respectively, and an ICC of 0.85 [CI: 0.64–0.94] for gross EC. SDCs were 12.2% for D6MWT, 12.7% for DWECT and 18.5% for gross EC. In conclusion, in young boys with DMD, the reliability of both the WECT and 6MWT for assessing walking distance is adequate. Gross EC, as assessed with the WECT is also reliable and sufficiently sensitive to detect change in walking strain following interventions at group level. Ó 2013 Elsevier B.V. All rights reserved. Keywords: Duchenne muscular dystrophy; Walking ability; Reliability; Energy cost of walking test; Six minute walking test
1. Introduction Duchenne muscular dystrophy (DMD) is an X-linked recessive muscle disorder, affecting 1 in 3500 new born boys [1]. The disease is caused by a mutation in the dystrophin gene, which leads to complete loss of dystrophin in muscle cells [2,3]. This results in a muscle wasting that begins in the lower proximal limbs and eventually leads to loss of ambulation and severe
⇑ Corresponding author. Address: Department of Rehabilitation Academic Medical Center, PO BOX 22660, 1100 DD Amsterdam, The Netherlands. Tel.: +31 20 5663669; fax: +31 20 5669154. E-mail address: [email protected] (M.A. Brehm).
0960-8966/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.nmd.2013.11.015
disability [4]. The median age of survival is approximately 35 years [5]. Although there is currently no cure for DMD, the increasing availability of promising treatment approaches [6–8] requires the use of well-designed measurement tools in order to provide valid information on the effects of treatments and to monitor disease progression. Clinical observation has clearly demonstrated that walking ability in boys with DMD decreases strongly over time [9–11], indicating that measurement instruments that quantify aspects of walking function are clinically relevant. Such measurement tools should be reliable and sensitive to changes in the population in which the instrument is used.
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One instrument that has been proposed for use in clinical trials in ambulant boys with DMD is the six-minute walk test (6MWT) [12]. This test has been applied in a broad range of therapeutic areas and reflects aspects of normal everyday life, including endurance and walking ability [12–14]. The 6MWT has already been validated in various paediatric populations [15–17], and its relevance to neuromuscular diseases has also been clearly established [18–21], although the use in boys with DMD has only been reported recently [8,12,13,22]. McDonald et al. concluded that the 6MWT offers a clinically meaningful method of outcome assessment in a DMD population, and, also, based on the intraclass correlation coefficient (ICC), they showed that reliability was high (ICC = 0.91 for the walked distance) [12]. However, while these authors reported an encouraging ICC, a full evaluation of reliability requires the reporting of both parameters of reliability and measurement error [23]. Information on measurement error (i.e. precision) is especially relevant when interventions at group level need to be evaluated or when the test is used to determine changes in a specific individual. Therefore, an important limitation in current literature is that evidence regarding the precision of the 6MWT is only available for healthy boys [24]. Another limitation of the 6MWT is that it solely measures walking distance as an aspect of ambulatory function, while two patients walking the same distance may experience a differing physical strain. Increased physical strain (i.e. walking energy cost) is a common and significant problem in children with motor disorders [25–27] and an assessment of the walking energy cost might provide an additional measure of ambulatory function in boys with DMD. However, while studies have provided evidence supporting the reliability of the walking energy cost test (WECT) in children [25,27–29], data on the reliability of this test in DMD patients are not yet available. Moreover, the WECT and 6MWT have never been compared in terms of reliability. Information on the influence of measurement error on statistical power and sample size estimation would provide greater insight when choosing the most suitable test in clinical trials. The aim of our study was to determine the test–retest reliability of the WECT and 6MWT in measuring aspects of ambulatory function in ambulant boys with DMD. 2. Patients Boys included in the study were recruited from the All Against Duchenne in the Netherlands network. Inclusion criteria were: a confirmed diagnosis of DMD, aged at least 6 years and capable of walking more than 150 m with or without the use of a walking aid. Children had not undergone surgical procedures in the previous six months and had no behavioral problems that would compromise participation in the study. The medical
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ethics committees of the two participating university hospitals approved the study, and written informed consent was obtained from all participants over 12 years of age or, for younger participants, from their parents. 3. Method 3.1. Procedures The study was conducted at the departments of Rehabilitation of the VU University Medical Center in Amsterdam and the Radboud University Medical Center in Nijmegen. Each participant visited one of these departments twice over a period of 3 weeks. Test and retest visits were scheduled at the same time of day, and all were performed by the same trained researcher (JK). Two experienced therapists provided training in the 6MWT and WECT. On each visit, a short physical examination was carried out to determine weight, height and leg length, followed by performance of the 6MWT and WECT. To control for influence of fatigue during the experiment, the test order was randomized per child. Furthermore, a 30-min resting period was provided between the two tests (sitting while watching a video). 3.2. Measurements 3.2.1. Walking energy cost test (WECT) The WECT consisted of a rest test and a walk test. Participants were given specific instructions not to eat or drink for at least 1.5 h prior to testing. Subjects first sat comfortably on a chair for the 6-min rest test (sitting while watching a video), and then performed a 6-min walk test at a self-preferred, comfortable speed on an indoor oval track Testing conditions during the measurements were kept as quiet as possible in order to allow the subject to achieve a steady state. Throughout the WECT, heart rate (HRWECT) was recorded with a polar band (Polar RS400, Polar Electro Oy, Kempele, Finland), and oxygen uptake (VO2) and carbon dioxide production (VCO2) were measured with an accurate [30], lightweight gas analysis system (Metamax 3B; Cortex Biophysik, Leipzig, Germany). This system is composed of a facemask, a Triple volume transducer, a gas sample line and a battery-operated unit (650 g) that is worn on the shoulders. After the test, the children’s perception of exhaustion (RPE) was scored using the Children’s OMNI scale of perceived exertion. This scale uses an indexed category format that contains both pictorial and verbal descriptors positioned along a comparatively narrow numerical response range of 0–10 (with 10 = ‘very very tired’) [31]. 3.2.2. Six minute walk test (6MWT) The 6MWT consisted of walking for 6 min at fast speed. The test and encouragements were performed according to the method of the American Thoracic Society [32]. The
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6MWT was performed indoors, along a 25 m straight course, with cones positioned at each end of the course. Boys were instructed to walk as fast as possible from one end to the other, going around the cones, though they were allowed to stop and rest, if necessary. During the test, a safety chaser walked directly behind the participant, giving positive verbal encouragement. The minute-split distances were recorded with tape flags and the number of falls was registered in a log file. HR6MWT was recorded with a polar band, and after the test, the children’s RPE was scored. 3.3. Data analysis Effect parameters derived from the WECT included: distance (DWECT, in m), gross walking energy cost (gross EC, in J kg1 m1) and speed-matched control energy cost (SMC-EC, in %), including a reliability analysis. Furthermore, speed (VWECT, in mmin1) and HRWECT were derived. Gross EC, defined as the energy used per unit distance travelled, was computed as follows: for the rest test and the walk test, respiratory exchange ratios (RERs) were calculated for each breath as VCO2 divided by VO2. Breath-by-breath RER and VO2 values in the last three minutes of both tests were then used to calculate the average steady state energy consumption demands (resting ECS and gross ECS, both in J kg1 min1), as defined by (4.940RER + 16.040)VO2 [33]. To account for differences in gait speed, gross EC was calculated by dividing gross ECS by speed (gross ECS/VWECT). Furthermore, to allow a comparison between the walking energy cost of boys with DMD and healthy children, SMC-EC was calculated [34]. The following effect parameters were derived from the 6MWT: distance (D6MWT, in m (including a reliability analysis)), speed (V6MWT, in mmin1) and HR6MWT. 3.4. Statistical analysis Data were analyzed using the Statistical Package for the Social Sciences (SPSS, version 18.0, Chicago, Illinois). Demographic variables and background variables were analyzed using descriptive statistics. Summary statistics were calculated for all effect parameters. In addition, correlations between the parameters were examined using Spearman correlation coefficients. Test–retest reliability was determined in accordance with the Generalizability Theory, which is based on analyses of variance (ANOVA). A two-way random effects model was used, with a restricted maximum likelihood method. From this ANOVA, three variance components were estimated: the variance between persons (rs), the variance due to measurement occasions (ro), and random error (re). Reliability was expressed using the intraclass correlation coefficient (ICC2,1) and 95% confidence intervals (CI). The ICC was computed as p 2 (r s/(r2s + r2o + r2e)). An ICC value > 0.70 is
considered acceptable and a lower bound of the 95% CI of the ICC > 0.75 is considered to indicate excellent reliability [35]. To quantify the precision of individual scores within the subjects, the standard error of measurement (SEM) was p calculated as (r2o + r2e). The SEM was expressed in the measurement units and as a percentage of the average values over two measurement occasions. As the use of the SEM implies that data are not heteroscedastic, Bland Altman plots were visually inspected to rule out the presence of heteroscedasticity (i.e. the SEM not being independent of the mean) [36]. From the SEM, the smallest detectable change (SDC) was calculated, representing the minimum difference that can be considered a real change between measurements with p 95% certainty. The SDC was calculated as 1.96SEM 2. 4. Results 4.1. Participant characteristics Nineteen boys with DMD participated. Median age of the boys was 7.4 years, mean 7.9 years (range 6–12.4), their median body-mass was 24.3 kg, and their mean height was 126.7 m (SD 10.7 cm) (see Table 1). One child was not able to perform the WECT on the second occasion due to behavioral problems. The median time between the first and second occasion was 7 days (range: 4–21 days). 4.2. Safety and feasibility Both tests were generally well tolerated by all 19 participants. Only 1 fall occurred during the 6MWT, while no falls were registered during the WECT. With respect to feasibility, during the WECT task boys seemed more easily distracted from performing or successfully completing the test than during the 6MWT. One boy showed behavioral problems during the WECT and was therefore unable to perform the test; two other tests were stopped in the final minute, one due to the need for a toilet visit and the other due to a boy becoming tearful.
Table 1 Patient characteristics (n = 19). Age Mean [IQR] Range
7.9 [1.91] 6.0–12.4
Mean [IQR] Range
29.3 21–66
Mean ± SD Range
127 ± 10.7 109–153
Body mass
Height
Abbreviations: IQR, interquartile range.
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Although there were also instances of behavioral and attention problems during the 6MWT, participants were quite well able to complete the test as instructed through the use of verbal directions and a safety chaser walking behind the participant. The physical strain of performing the 6MWT was much higher compared to the WECT, as shown by the higher HR values (154 bpm on the 6MWT vs. 132 bpm on the WECT) and RPE values (6 on the 6MWT vs. 4 on the WECT).
presented in Tables 3a and 3b. Since heteroscedasticity was not observed in any of the effect parameters, as visually determined by inspection of Bland–Altman plots, the SEM and SDC were used to express measurement error. Measurement error for the walked distance, expressed by the SDC, was 51 m (12.2% of the mean) for the 6MWT, and 43 m (12.7%) for the WECT. Regarding outcomes for physical strain, SDCs ranged from 18.5% for gross EC to 32.7% for SMC-EC.
4.3. Descriptive data of the 6MWT and WECT
5. Discussion
The mean (SD) walking distances on the 6MWT and WECT were respectively 416 m (69.5 m) vs. 336 m (40.7 m) for test, and 421 m (60.5 m) vs. 337 m (32 m) for retest. The correlation between D6MWT and DWECT was 0.865 (p < 0.0001). Correlations between D6MWT and DWECT with gross EC were 0.109 and 0.141, respectively. The median [interquartile range] gross EC was 7.10 J kg1 m1 [1.43 J kg1 m1] for test and 6.90 J kg1 m1 [2.46 J kg1 m1] for retest. Values of SMC-EC on test and retest were 181% and 180%, respectively, indicating that the strain of walking in boys with DMD is 80% higher compared to the energy cost in healthy speed-matched control children. Tables 2a and 2b show the descriptive data for both tests on the 2 occasions, including the norm data for healthy children.
In the present study it was found that reliability of the WECT and 6MWT is high when assessing walking distance in young ambulant boys with DMD. Furthermore, both tests show good estimates of precision for walking distance, as illustrated by low SEM values. The precision of gross EC, as assessed by the WECT, is also good and sufficiently sensitive to detect changes in walking strain following interventions in groups of boys with DMD. To evaluate individual change, we established a difference of at least 18.5% to be interpreted as a real change. Despite the frequent use of the WECT in the evaluation of ambulatory function in children with motor disorders [25,27–29,34,37], the current study is the first to assess reliability of the test in boys with DMD. Based on the ICC, we found that reliability for walking distance and gross EC on this test was high, although still with slightly lower reliability than the 6MWT. The fact that boys appeared to be more easily distracted from performing or successfully completing the WECT might explain the lower reliability relative to the 6MWT. The superior reliability for gross EC found in other paediatric populations [25,27], in which attention deficits and behavioral problems are less common than in DMD [38], may substantiate this hypothesis. However, notwithstanding that the discrimination of individuals
4.4. Test–retest reliability Tables 3a and 3b present the results for test–retest reliability. Reliability for walking distance was excellent on the 6MWT (ICC = 0.92 [95% CI: 0.81–0.97] and acceptable on the WECT (ICC = 0.83 [95% CI: 0.53–0.94]). The WECT also showed acceptable reliability for gross EC (ICC = 0.85 [95% CI: 0.64–0.94]), whereas SMC-EC showed poor reliability (ICC = 0.45 [95% CI: 0.02 to 0.86]). Measurement error results are also Table 2a Descriptive data for the 6MWT.
Distance (m) Speed [mmin1] *
n
Norm data*
Test (T1)
Retest (T2)
D T2 T1 [95% CI for D]
18 16
555.5 92.6
416 (69.5) 69.4 (11.6)
421 (60.5) 70.3 (10.1)
5.1 [8 to 18] 0.85 [1.3 to 3.03]
Based on Goemans et al. [24].
Table 2b Descriptive data for the WECT.
Distance (m) Speed (mmin1) Gross EC (J kg1 m1) SMC-EC (%)
n
Norm data**
Test (T1)
Retest (T2)
D T2 T1 (95% CI for D)
16 18 18 18
452 75.3 4.80 100
336 (40.7) 57.2 (6.0) ^ 7.10 [1.43] 181 (30)
347 (32) 57.2 (5.2) ^ 6.90 [2.46] 180 (29)
11.1 [1–21) 0.06 [1.8 to 1.9] 0.03 [0.38 to 0.32] 1.3 [13 to 25]
Abbreviations: EC, energy cost; SMC EC, speed-matched control energy cost. ^ Data presented as median [interquartile range]. ** Based on Thomas et al. [29] and Brehm et al. [25].
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Table 3a Test–retest reliability outcomes for the 6MWT.
Distance (m)
ICC (95% CI)
SEM
95% LoA
SDC
0.92 (0.81–0.97)
18.4 (4.4)
45.7 to 55.9
51 (12.2)
Table 3b Test–retest reliability outcomes for the WECT.
Distance (m) Gross EC (J kg1 m1) SMC EC (%)
ICC (95% CI)
SEM
95% LoA
SDC
0.83 (0.53–0.94) 0.85 (0.64–0.94) 0.45 (0.02 to 0.86)
14.8 (4.4) 0.473 (6.7) 21 (11.8)
27.7 to 49.9 1.36 to 1.30 68 to 79
43 (12.7) 1.31 (18.5) 59 (32.7)
Abbreviations: 95% CI, 95% confidence interval; ICC, intraclass correlation coefficient; SEM, standard error of measurement, SDC, smallest detectable change for a single individual; LoA, limits of agreement; EC, energy cost; SMC EC, speed-matched control cost. SEM and SDC values are presented absolute (% of mean).
with different levels of ambulatory function is slightly affected by measurement error, our findings indicate that the WECT can reliably assess both walking strain and walking distance. In addition to reliability, we also reported measurement error. Although reliability is useful when distinguishing between individuals (or groups), measurement error is of more interest to clinicians, as they need to determine meaningful differences in the rate of decline of ambulatory function. In our study, measurement error for gross EC, based on the SDC (%) was 1.31 J kg1 m1 (18.5%). To determine whether this implies satisfactory sensitivity, we compared our findings with the mean change score on the WECT following intervention. A study in children with spina bifida, by Duffy et al. [37], reported a 1.70 J kg1 m1 (24%) decrease in energy cost when walking with and without orthoses. In relation to the SDC found in our study, this suggests that measurement error in the present study seems small enough to allow changes to be detected in walking strain following interventions in both in groups boys with DMD. In addition to the reliability of gross EC, we also established the reliability of net non-dimensional SMC-EC. In contrast to gross EC, this measure is suggested in literature to be appropriate when evaluating children over longer time periods [25,39] since it reduces the variability between participants of different ages and sizes, while exclusively evaluating the amount of walking energy used. Unfortunately, the reliability of SMC-EC is only moderate, especially when evaluating changes at individual level. Thus, we suggest that the use of SMC-EC should preferably be limited to evaluation of groups of boys with DMD. Only when therapeutic benefits larger than 33% are expected is this measure of walking strain is adequately sensitive for evaluating changes in single individuals. The current and previous [25,26,29] studies have shown that walking strain in boys with DMD is about 80% greater (range 20–250%) than in healthy children, suggesting that interventions aimed at reducing walking EC may provide valuable treatment options to longer maintain functional
abilities in this group of boys. As such, the WECT offers a relevant additional test for future clinical trials in DMD. Several aspects of ambulatory function can be assessed with this test, including walking distance, speed and walking strain. Based on our finding that there was no correlation between walking distance and walking strain, it appears that these measures provide supplementary information on a patient’s ambulatory status. Moreover, given that the walked distance on the WECT correlated strongly with distance on the 6MWT, this sub-maximal exercise test could represent a valid alternative to the 6MWT. It would also allow a reduction in the rather high physiologic stress experienced when walking function is assessed in boys with DMD using the 6MWT. However, it is important to keep in mind the difficulty of testing boys with attentional deficits and behavioral problems when using the WECT in clinical practice. 5.0.1. Limitations of the study The most important limitation of our study is the small sample size, since this affects both the statistical power and our ability to generalize the results [14]. Furthermore, the small sample size prevented analyses by separate age group. As DMD is characterized by a specific pattern of disease progression in the age ranges between 5 and 12 years, establishing both reliability and descriptive data on walking distance and walking strain in narrow age categories is required to allow monitoring of ambulatory status and possible intervention effects [24]. Future studies should aim to establish these parameters within specific age subcategories of boys with DMD and to describe age-related trends in walking strain in this group of boys. 6. Conclusion In ambulant young boys with DMD, the reliability of both the WECT and the 6MWT for assessing walking distance is high. Furthermore, the two tests also show
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good estimates of precision. Gross EC, as quantified with the WECT, also shows good precision and is adequately sensitive to detect change at group level. Given our finding that walking strain in boys with DMD is high, gross EC offers a relevant additional outcome of ambulatory function for future clinical trials in DMD. Acknowledgment The authors gratefully acknowledge the participating children and their parents. This study was supported by Prosensa Thereapeutics B.V. References [1] Emery AEH. The muscular dystrophies. Lancet 2002;359(9307):687–95. [2] Hoffman EP, Bronson A, Levin AA, et al. Restoring dystrophin expression in Duchenne muscular dystrophy muscle progress in exon skipping and stop codon read through. Am J Pathol 2011;179(1):12–22. [3] Zubrzycka-Gaarn EE, Bulman DE, Karpati G, et al. The Duchenne muscular dystrophy gene product is localized in sarcolemma of human skeletal muscle. Nature 1988;333(6172):466–9. [4] Moser H. Duchenne muscular dystrophy: pathogenetic aspects and genetic prevention. Hum Genet 1984;66(1):17–40. [5] Kohler M, Clarenbach CF, Bahler C, Brack T, Russi EW, Bloch KE. Disability and survival in Duchenne muscular dystrophy. J Neurol Neurosurg Psychiatr 2009;80(3):320–5. [6] Cirak S, Arechavala-Gomeza V, Guglieri M, et al. Exon skipping and dystrophin restoration in patients with Duchenne muscular dystrophy after systemic phosphorodiamidate morpholino oligomer treatment: an open-label, phase 2, dose-escalation study. Lancet 2011;378(9791):595–605. [7] Beytia ML, Vry J, Kirschner J. Drug treatment of Duchenne muscular dystrophy: available evidence and perspectives. Acta Myol 2012;31(1):4–8. [8] Goemans NM, Tulinius M, van den Akker JT, et al. Systemic administration of PRO051 in Duchenne’s muscular dystrophy. N Engl J Med 2011;364(16):1513–22. [9] Brooke MH, Fenichel GM, Griggs RC, et al. Duchenne muscular dystrophy: patterns of clinical progression and effects of supportive therapy. Neurology 1989;39(4):475–81. [10] McDonald CM, Abresch RT, Carter GT, et al. Profiles of neuromuscular diseases. Duchenne muscular dystrophy. Am J Phys Med Rehab 1995;74(5 Suppl):S70–92. [11] Boland BJ, Silbert PL, Groover RV, Wollan PC, Silverstein MD. Skeletal, cardiac, and smooth muscle failure in Duchenne muscular dystrophy. Pediatr Neurol 1996;14(1):7–12. [12] McDonald CM, Henricson EK, Han JJ, et al. The 6-minute walk test as a new outcome measure in Duchenne muscular dystrophy. Muscle Nerve 2010;41(4):500–10. [13] Mazzone E, Vasco G, Sormani MP, et al. Functional changes in Duchenne muscular dystrophy: a 12-month longitudinal cohort study. Neurology 2011;77(3):250–6. [14] Bartels B, De Groot JF, Terwee CB. The six-minute walk test in chronic pediatric conditions: a systematic review of measurement properties. Phys Ther 2012;93(4):529–41. [15] De Groot JF, Takken T. The six-minute walk test in paediatric populations. J Physiother 2011;57(2):128. [16] Geiger R, Strasak A, Treml B, et al. Six-minute walk test in children and adolescents. J Pediatr 2007;150(4):395–9. [17] Li AM, Yin J, Yu CCW, et al. The six-minute walk test in healthy children: reliability and validity. Eur Respir J 2005;25(6): 1057–60.
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Reliability of the walking energy cost test and the six-minute walk test in boys with Duchenne muscular dystrophy J.C.E. Kempen a, J. Harlaar a, A.J. van der Kooi b, I.J.M. de Groot c, J.C. van den Bergen d, E.H. Niks d, J.J.G.M. Verschuuren d, M.A. Brehm a,e,⇑ a
Department of Rehabilitation Medicine and MOVE Research Institute, VU University Medical Center, Amsterdam, The Netherlands b Department of Neurology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands c Department of Rehabilitation, Radboud University Medical Center, Nijmegen, The Netherlands d Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands e Department of Rehabilitation, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands Received 20 July 2013; received in revised form 6 November 2013; accepted 27 November 2013
Abstract The walking energy cost test (WECT) is a useful tool when measuring ambulatory function in children with motor disorders. However, data on the reliability of this test in Duchenne muscular dystrophy (DMD) is not available. In this study we established the reliability of the WECT and the commonly used six-minute walk test (6MWT) in 19 boys with DMD, aged 6–12 years. Participants performed the WECT and 6MWT twice within three weeks. Reliability was determined for walking distance (D, m) and gross energy cost (EC, J kg1 m1), using the intraclass correlation coefficient (ICC2,1) and smallest detectable change (SDC). Reliability for walking distance was good, with an ICC of 0.92 [95% CI: 0.81–0.97] and 0.83 [CI: 0.53–0.94] for the 6MWT and WECT, respectively, and an ICC of 0.85 [CI: 0.64–0.94] for gross EC. SDCs were 12.2% for D6MWT, 12.7% for DWECT and 18.5% for gross EC. In conclusion, in young boys with DMD, the reliability of both the WECT and 6MWT for assessing walking distance is adequate. Gross EC, as assessed with the WECT is also reliable and sufficiently sensitive to detect change in walking strain following interventions at group level. Ó 2013 Elsevier B.V. All rights reserved. Keywords: Duchenne muscular dystrophy; Walking ability; Reliability; Energy cost of walking test; Six minute walking test
1. Introduction Duchenne muscular dystrophy (DMD) is an X-linked recessive muscle disorder, affecting 1 in 3500 new born boys [1]. The disease is caused by a mutation in the dystrophin gene, which leads to complete loss of dystrophin in muscle cells [2,3]. This results in a muscle wasting that begins in the lower proximal limbs and eventually leads to loss of ambulation and severe
⇑ Corresponding author. Address: Department of Rehabilitation Academic Medical Center, PO BOX 22660, 1100 DD Amsterdam, The Netherlands. Tel.: +31 20 5663669; fax: +31 20 5669154. E-mail address: [email protected] (M.A. Brehm).
0960-8966/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.nmd.2013.11.015
disability [4]. The median age of survival is approximately 35 years [5]. Although there is currently no cure for DMD, the increasing availability of promising treatment approaches [6–8] requires the use of well-designed measurement tools in order to provide valid information on the effects of treatments and to monitor disease progression. Clinical observation has clearly demonstrated that walking ability in boys with DMD decreases strongly over time [9–11], indicating that measurement instruments that quantify aspects of walking function are clinically relevant. Such measurement tools should be reliable and sensitive to changes in the population in which the instrument is used.
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One instrument that has been proposed for use in clinical trials in ambulant boys with DMD is the six-minute walk test (6MWT) [12]. This test has been applied in a broad range of therapeutic areas and reflects aspects of normal everyday life, including endurance and walking ability [12–14]. The 6MWT has already been validated in various paediatric populations [15–17], and its relevance to neuromuscular diseases has also been clearly established [18–21], although the use in boys with DMD has only been reported recently [8,12,13,22]. McDonald et al. concluded that the 6MWT offers a clinically meaningful method of outcome assessment in a DMD population, and, also, based on the intraclass correlation coefficient (ICC), they showed that reliability was high (ICC = 0.91 for the walked distance) [12]. However, while these authors reported an encouraging ICC, a full evaluation of reliability requires the reporting of both parameters of reliability and measurement error [23]. Information on measurement error (i.e. precision) is especially relevant when interventions at group level need to be evaluated or when the test is used to determine changes in a specific individual. Therefore, an important limitation in current literature is that evidence regarding the precision of the 6MWT is only available for healthy boys [24]. Another limitation of the 6MWT is that it solely measures walking distance as an aspect of ambulatory function, while two patients walking the same distance may experience a differing physical strain. Increased physical strain (i.e. walking energy cost) is a common and significant problem in children with motor disorders [25–27] and an assessment of the walking energy cost might provide an additional measure of ambulatory function in boys with DMD. However, while studies have provided evidence supporting the reliability of the walking energy cost test (WECT) in children [25,27–29], data on the reliability of this test in DMD patients are not yet available. Moreover, the WECT and 6MWT have never been compared in terms of reliability. Information on the influence of measurement error on statistical power and sample size estimation would provide greater insight when choosing the most suitable test in clinical trials. The aim of our study was to determine the test–retest reliability of the WECT and 6MWT in measuring aspects of ambulatory function in ambulant boys with DMD. 2. Patients Boys included in the study were recruited from the All Against Duchenne in the Netherlands network. Inclusion criteria were: a confirmed diagnosis of DMD, aged at least 6 years and capable of walking more than 150 m with or without the use of a walking aid. Children had not undergone surgical procedures in the previous six months and had no behavioral problems that would compromise participation in the study. The medical
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ethics committees of the two participating university hospitals approved the study, and written informed consent was obtained from all participants over 12 years of age or, for younger participants, from their parents. 3. Method 3.1. Procedures The study was conducted at the departments of Rehabilitation of the VU University Medical Center in Amsterdam and the Radboud University Medical Center in Nijmegen. Each participant visited one of these departments twice over a period of 3 weeks. Test and retest visits were scheduled at the same time of day, and all were performed by the same trained researcher (JK). Two experienced therapists provided training in the 6MWT and WECT. On each visit, a short physical examination was carried out to determine weight, height and leg length, followed by performance of the 6MWT and WECT. To control for influence of fatigue during the experiment, the test order was randomized per child. Furthermore, a 30-min resting period was provided between the two tests (sitting while watching a video). 3.2. Measurements 3.2.1. Walking energy cost test (WECT) The WECT consisted of a rest test and a walk test. Participants were given specific instructions not to eat or drink for at least 1.5 h prior to testing. Subjects first sat comfortably on a chair for the 6-min rest test (sitting while watching a video), and then performed a 6-min walk test at a self-preferred, comfortable speed on an indoor oval track Testing conditions during the measurements were kept as quiet as possible in order to allow the subject to achieve a steady state. Throughout the WECT, heart rate (HRWECT) was recorded with a polar band (Polar RS400, Polar Electro Oy, Kempele, Finland), and oxygen uptake (VO2) and carbon dioxide production (VCO2) were measured with an accurate [30], lightweight gas analysis system (Metamax 3B; Cortex Biophysik, Leipzig, Germany). This system is composed of a facemask, a Triple volume transducer, a gas sample line and a battery-operated unit (650 g) that is worn on the shoulders. After the test, the children’s perception of exhaustion (RPE) was scored using the Children’s OMNI scale of perceived exertion. This scale uses an indexed category format that contains both pictorial and verbal descriptors positioned along a comparatively narrow numerical response range of 0–10 (with 10 = ‘very very tired’) [31]. 3.2.2. Six minute walk test (6MWT) The 6MWT consisted of walking for 6 min at fast speed. The test and encouragements were performed according to the method of the American Thoracic Society [32]. The
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6MWT was performed indoors, along a 25 m straight course, with cones positioned at each end of the course. Boys were instructed to walk as fast as possible from one end to the other, going around the cones, though they were allowed to stop and rest, if necessary. During the test, a safety chaser walked directly behind the participant, giving positive verbal encouragement. The minute-split distances were recorded with tape flags and the number of falls was registered in a log file. HR6MWT was recorded with a polar band, and after the test, the children’s RPE was scored. 3.3. Data analysis Effect parameters derived from the WECT included: distance (DWECT, in m), gross walking energy cost (gross EC, in J kg1 m1) and speed-matched control energy cost (SMC-EC, in %), including a reliability analysis. Furthermore, speed (VWECT, in mmin1) and HRWECT were derived. Gross EC, defined as the energy used per unit distance travelled, was computed as follows: for the rest test and the walk test, respiratory exchange ratios (RERs) were calculated for each breath as VCO2 divided by VO2. Breath-by-breath RER and VO2 values in the last three minutes of both tests were then used to calculate the average steady state energy consumption demands (resting ECS and gross ECS, both in J kg1 min1), as defined by (4.940RER + 16.040)VO2 [33]. To account for differences in gait speed, gross EC was calculated by dividing gross ECS by speed (gross ECS/VWECT). Furthermore, to allow a comparison between the walking energy cost of boys with DMD and healthy children, SMC-EC was calculated [34]. The following effect parameters were derived from the 6MWT: distance (D6MWT, in m (including a reliability analysis)), speed (V6MWT, in mmin1) and HR6MWT. 3.4. Statistical analysis Data were analyzed using the Statistical Package for the Social Sciences (SPSS, version 18.0, Chicago, Illinois). Demographic variables and background variables were analyzed using descriptive statistics. Summary statistics were calculated for all effect parameters. In addition, correlations between the parameters were examined using Spearman correlation coefficients. Test–retest reliability was determined in accordance with the Generalizability Theory, which is based on analyses of variance (ANOVA). A two-way random effects model was used, with a restricted maximum likelihood method. From this ANOVA, three variance components were estimated: the variance between persons (rs), the variance due to measurement occasions (ro), and random error (re). Reliability was expressed using the intraclass correlation coefficient (ICC2,1) and 95% confidence intervals (CI). The ICC was computed as p 2 (r s/(r2s + r2o + r2e)). An ICC value > 0.70 is
considered acceptable and a lower bound of the 95% CI of the ICC > 0.75 is considered to indicate excellent reliability [35]. To quantify the precision of individual scores within the subjects, the standard error of measurement (SEM) was p calculated as (r2o + r2e). The SEM was expressed in the measurement units and as a percentage of the average values over two measurement occasions. As the use of the SEM implies that data are not heteroscedastic, Bland Altman plots were visually inspected to rule out the presence of heteroscedasticity (i.e. the SEM not being independent of the mean) [36]. From the SEM, the smallest detectable change (SDC) was calculated, representing the minimum difference that can be considered a real change between measurements with p 95% certainty. The SDC was calculated as 1.96SEM 2. 4. Results 4.1. Participant characteristics Nineteen boys with DMD participated. Median age of the boys was 7.4 years, mean 7.9 years (range 6–12.4), their median body-mass was 24.3 kg, and their mean height was 126.7 m (SD 10.7 cm) (see Table 1). One child was not able to perform the WECT on the second occasion due to behavioral problems. The median time between the first and second occasion was 7 days (range: 4–21 days). 4.2. Safety and feasibility Both tests were generally well tolerated by all 19 participants. Only 1 fall occurred during the 6MWT, while no falls were registered during the WECT. With respect to feasibility, during the WECT task boys seemed more easily distracted from performing or successfully completing the test than during the 6MWT. One boy showed behavioral problems during the WECT and was therefore unable to perform the test; two other tests were stopped in the final minute, one due to the need for a toilet visit and the other due to a boy becoming tearful.
Table 1 Patient characteristics (n = 19). Age Mean [IQR] Range
7.9 [1.91] 6.0–12.4
Mean [IQR] Range
29.3 21–66
Mean ± SD Range
127 ± 10.7 109–153
Body mass
Height
Abbreviations: IQR, interquartile range.
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Although there were also instances of behavioral and attention problems during the 6MWT, participants were quite well able to complete the test as instructed through the use of verbal directions and a safety chaser walking behind the participant. The physical strain of performing the 6MWT was much higher compared to the WECT, as shown by the higher HR values (154 bpm on the 6MWT vs. 132 bpm on the WECT) and RPE values (6 on the 6MWT vs. 4 on the WECT).
presented in Tables 3a and 3b. Since heteroscedasticity was not observed in any of the effect parameters, as visually determined by inspection of Bland–Altman plots, the SEM and SDC were used to express measurement error. Measurement error for the walked distance, expressed by the SDC, was 51 m (12.2% of the mean) for the 6MWT, and 43 m (12.7%) for the WECT. Regarding outcomes for physical strain, SDCs ranged from 18.5% for gross EC to 32.7% for SMC-EC.
4.3. Descriptive data of the 6MWT and WECT
5. Discussion
The mean (SD) walking distances on the 6MWT and WECT were respectively 416 m (69.5 m) vs. 336 m (40.7 m) for test, and 421 m (60.5 m) vs. 337 m (32 m) for retest. The correlation between D6MWT and DWECT was 0.865 (p < 0.0001). Correlations between D6MWT and DWECT with gross EC were 0.109 and 0.141, respectively. The median [interquartile range] gross EC was 7.10 J kg1 m1 [1.43 J kg1 m1] for test and 6.90 J kg1 m1 [2.46 J kg1 m1] for retest. Values of SMC-EC on test and retest were 181% and 180%, respectively, indicating that the strain of walking in boys with DMD is 80% higher compared to the energy cost in healthy speed-matched control children. Tables 2a and 2b show the descriptive data for both tests on the 2 occasions, including the norm data for healthy children.
In the present study it was found that reliability of the WECT and 6MWT is high when assessing walking distance in young ambulant boys with DMD. Furthermore, both tests show good estimates of precision for walking distance, as illustrated by low SEM values. The precision of gross EC, as assessed by the WECT, is also good and sufficiently sensitive to detect changes in walking strain following interventions in groups of boys with DMD. To evaluate individual change, we established a difference of at least 18.5% to be interpreted as a real change. Despite the frequent use of the WECT in the evaluation of ambulatory function in children with motor disorders [25,27–29,34,37], the current study is the first to assess reliability of the test in boys with DMD. Based on the ICC, we found that reliability for walking distance and gross EC on this test was high, although still with slightly lower reliability than the 6MWT. The fact that boys appeared to be more easily distracted from performing or successfully completing the WECT might explain the lower reliability relative to the 6MWT. The superior reliability for gross EC found in other paediatric populations [25,27], in which attention deficits and behavioral problems are less common than in DMD [38], may substantiate this hypothesis. However, notwithstanding that the discrimination of individuals
4.4. Test–retest reliability Tables 3a and 3b present the results for test–retest reliability. Reliability for walking distance was excellent on the 6MWT (ICC = 0.92 [95% CI: 0.81–0.97] and acceptable on the WECT (ICC = 0.83 [95% CI: 0.53–0.94]). The WECT also showed acceptable reliability for gross EC (ICC = 0.85 [95% CI: 0.64–0.94]), whereas SMC-EC showed poor reliability (ICC = 0.45 [95% CI: 0.02 to 0.86]). Measurement error results are also Table 2a Descriptive data for the 6MWT.
Distance (m) Speed [mmin1] *
n
Norm data*
Test (T1)
Retest (T2)
D T2 T1 [95% CI for D]
18 16
555.5 92.6
416 (69.5) 69.4 (11.6)
421 (60.5) 70.3 (10.1)
5.1 [8 to 18] 0.85 [1.3 to 3.03]
Based on Goemans et al. [24].
Table 2b Descriptive data for the WECT.
Distance (m) Speed (mmin1) Gross EC (J kg1 m1) SMC-EC (%)
n
Norm data**
Test (T1)
Retest (T2)
D T2 T1 (95% CI for D)
16 18 18 18
452 75.3 4.80 100
336 (40.7) 57.2 (6.0) ^ 7.10 [1.43] 181 (30)
347 (32) 57.2 (5.2) ^ 6.90 [2.46] 180 (29)
11.1 [1–21) 0.06 [1.8 to 1.9] 0.03 [0.38 to 0.32] 1.3 [13 to 25]
Abbreviations: EC, energy cost; SMC EC, speed-matched control energy cost. ^ Data presented as median [interquartile range]. ** Based on Thomas et al. [29] and Brehm et al. [25].
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Table 3a Test–retest reliability outcomes for the 6MWT.
Distance (m)
ICC (95% CI)
SEM
95% LoA
SDC
0.92 (0.81–0.97)
18.4 (4.4)
45.7 to 55.9
51 (12.2)
Table 3b Test–retest reliability outcomes for the WECT.
Distance (m) Gross EC (J kg1 m1) SMC EC (%)
ICC (95% CI)
SEM
95% LoA
SDC
0.83 (0.53–0.94) 0.85 (0.64–0.94) 0.45 (0.02 to 0.86)
14.8 (4.4) 0.473 (6.7) 21 (11.8)
27.7 to 49.9 1.36 to 1.30 68 to 79
43 (12.7) 1.31 (18.5) 59 (32.7)
Abbreviations: 95% CI, 95% confidence interval; ICC, intraclass correlation coefficient; SEM, standard error of measurement, SDC, smallest detectable change for a single individual; LoA, limits of agreement; EC, energy cost; SMC EC, speed-matched control cost. SEM and SDC values are presented absolute (% of mean).
with different levels of ambulatory function is slightly affected by measurement error, our findings indicate that the WECT can reliably assess both walking strain and walking distance. In addition to reliability, we also reported measurement error. Although reliability is useful when distinguishing between individuals (or groups), measurement error is of more interest to clinicians, as they need to determine meaningful differences in the rate of decline of ambulatory function. In our study, measurement error for gross EC, based on the SDC (%) was 1.31 J kg1 m1 (18.5%). To determine whether this implies satisfactory sensitivity, we compared our findings with the mean change score on the WECT following intervention. A study in children with spina bifida, by Duffy et al. [37], reported a 1.70 J kg1 m1 (24%) decrease in energy cost when walking with and without orthoses. In relation to the SDC found in our study, this suggests that measurement error in the present study seems small enough to allow changes to be detected in walking strain following interventions in both in groups boys with DMD. In addition to the reliability of gross EC, we also established the reliability of net non-dimensional SMC-EC. In contrast to gross EC, this measure is suggested in literature to be appropriate when evaluating children over longer time periods [25,39] since it reduces the variability between participants of different ages and sizes, while exclusively evaluating the amount of walking energy used. Unfortunately, the reliability of SMC-EC is only moderate, especially when evaluating changes at individual level. Thus, we suggest that the use of SMC-EC should preferably be limited to evaluation of groups of boys with DMD. Only when therapeutic benefits larger than 33% are expected is this measure of walking strain is adequately sensitive for evaluating changes in single individuals. The current and previous [25,26,29] studies have shown that walking strain in boys with DMD is about 80% greater (range 20–250%) than in healthy children, suggesting that interventions aimed at reducing walking EC may provide valuable treatment options to longer maintain functional
abilities in this group of boys. As such, the WECT offers a relevant additional test for future clinical trials in DMD. Several aspects of ambulatory function can be assessed with this test, including walking distance, speed and walking strain. Based on our finding that there was no correlation between walking distance and walking strain, it appears that these measures provide supplementary information on a patient’s ambulatory status. Moreover, given that the walked distance on the WECT correlated strongly with distance on the 6MWT, this sub-maximal exercise test could represent a valid alternative to the 6MWT. It would also allow a reduction in the rather high physiologic stress experienced when walking function is assessed in boys with DMD using the 6MWT. However, it is important to keep in mind the difficulty of testing boys with attentional deficits and behavioral problems when using the WECT in clinical practice. 5.0.1. Limitations of the study The most important limitation of our study is the small sample size, since this affects both the statistical power and our ability to generalize the results [14]. Furthermore, the small sample size prevented analyses by separate age group. As DMD is characterized by a specific pattern of disease progression in the age ranges between 5 and 12 years, establishing both reliability and descriptive data on walking distance and walking strain in narrow age categories is required to allow monitoring of ambulatory status and possible intervention effects [24]. Future studies should aim to establish these parameters within specific age subcategories of boys with DMD and to describe age-related trends in walking strain in this group of boys. 6. Conclusion In ambulant young boys with DMD, the reliability of both the WECT and the 6MWT for assessing walking distance is high. Furthermore, the two tests also show
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