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Alterations in Aerobic Exercise Performance and Gait Economy Following High-Intensity Dynamic Stepping Training in Persons With Subacute Stroke

Leddy, Abigail L. DPT, MSCI, NCS; Connolly, Mark BS; Holleran, Carey L. MPT, DHS, NCS; Hennessy, Patrick W. MPT, NCS; Woodward, Jane DPT, NCS; Arena, Ross A. PT, PhD; Roth, Elliot J. MD; Hornby, T. George PT, PhD

Erratum

In the article mentioned above, two authors, Kristan A. Leech, DPT, PhD, Gordhan Mahtani, MS, were left off the author list. The correct author list and affiliations are listed below:

Abigail L. Leddy, DPT, MSCI, NCS, Mark Connolly, BS, Carey L. Holleran, MPT, DHS, NCS, Patrick W. Hennessy, MPT, NCS, Jane Woodward, DPT, NCS, Kristan A. Leech, DPT, PhD, Gordhan Mahtani, MS, Ross A. Arena, PT, PhD, Elliot J. Roth, MD, T. George Hornby, PT, PhD.

Sensory Motor Performance Program (A.L.L., M.C., C.L.H., P.W.H., J.W., K.A.L., G.M., T.G.H.), Rehabilitation Institute of Chicago, Chicago, Illinois; Department of Physical Medicine and Rehabilitation (R.A.A., E.J.R., T.G.H.), Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Physical Therapy and Kinesiology & Nutrition (R.A.A.), University of Illinois at Chicago; and Department of Physical Medicine and Rehabilitation (T.G.H.), Indiana University School of Medicine, Indianapolis, Indiana.

Journal of Neurologic Physical Therapy. 41(1):20, January 2017.

Journal of Neurologic Physical Therapy: October 2016 - Volume 40 - Issue 4 - p 239–248
doi: 10.1097/NPT.0000000000000147
Research Articles
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Background and Purpose: Impairments in metabolic capacity and economy (O2cost) are hallmark characteristics of locomotor dysfunction following stroke. High-intensity (aerobic) training has been shown to improve peak oxygen consumption in this population, with fewer reports of changes in O2cost. However, particularly in persons with subacute stroke, inconsistent gains in walking function are observed with minimal associations with gains in metabolic parameters. The purpose of this study was to evaluate changes in aerobic exercise performance in participants with subacute stroke following high-intensity variable stepping training as compared with conventional therapy.

Methods: A secondary analysis was performed on data from a randomized controlled trial comparing high-intensity training with conventional interventions, and from the pilot study that formed the basis for the randomized controlled trial. Participants 1 to 6 months poststroke received 40 or fewer sessions of high-intensity variable stepping training (n = 21) or conventional interventions (n = 12). Assessments were performed at baseline (BSL), posttraining, and 2- to 3-month follow-up and included changes in submaximal

O2 (

O2submax) and O2cost at fastest possible treadmill speeds and peak speeds at BSL testing.

Results: Significant improvements were observed in

O2submax with less consistent improvements in O2cost, although individual responses varied substantially. Combined changes in both

O2submax and

O2 at matched peak BSL speeds revealed stronger correlations to improvements in walking function as compared with either measure alone.

Discussion and Conclusions: High-intensity stepping training may elicit significant improvements in

O2submax, whereas changes in both peak capacity and economy better reflect gains in walking function. Providing high-intensity training to improve locomotor and aerobic exercise performance may increase the efficiency of rehabilitation sessions.

Video Abstract available for more insights from the authors (see Supplemental Digital Content, http://links.lww.com/JNPT/A142).

Sensory Motor Performance Program (A.L.L., M.C., C.L.H., P.W.H., J.W., T.G.H.), Rehabilitation Institute of Chicago, Chicago, Illinois; Department of Physical Medicine and Rehabilitation (R.A.A., E.J.R., T.G.H.), Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Department of Physical Therapy and Kinesiology & Nutrition (R.A.A.), University of Illinois at Chicago; and Department of Physical Medicine and Rehabilitation (T.G.H.), Indiana University School of Medicine, Indianapolis, Indiana.

Correspondence: T. George Hornby, PT, PhD, Department of Physical Medicine and Rehabilitation, Indiana University School of Medicine, 4141 Shore Dr. Indianapolis, IN 46254 (tghornby@iu.edu).

Parts of this work were presented previously at the 2013 Combined Sections Meeting, of the APTA, in San Diego, California.

Funding for the study was provided by National Institute on Disability and Rehabilitation Research grants H133B031127 and H133B140012, and the Bullock Foundation.

The authors declare no conflict of interest.

Supplemental digital content is available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal's Web site (www.jnpt.org).

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INTRODUCTION

Approximately 70% to 80% of individuals with hemiparesis poststroke walk without physical assistance,1 although many ambulate at slow speeds and for limited distances.2 Impaired locomotion poststroke not only is linked primarily to neuromuscular impairments but is also associated with deficits in peak metabolic capacity,3,4 defined as peak rate of oxygen consumption (

O2peak [mL O2/kg/min]), and decreased gait economy,2,5,6 defined as increased metabolic cost of walking per unit distance (O2cost; mL O2/kg/m). In individuals with stroke,

O2peak can be 13% to 74% lower than age- and gender-matched controls,7 and the energy expenditure may be doubled during walking.8 These metabolic impairments are correlated to decreased mobility, and gains in metabolic capacity and economy may contribute to improved walking function.2,9

High-intensity (aerobic) exercise interventions are often utilized to target cardiopulmonary impairments to improve walking function poststroke. Most aerobic training strategies utilize lower extremity ergometry,10–14 recumbent stepping,15,16 treadmill training,2,9,17–19 or mixed interventions,20–23 with targeted heart rate (HR) ranges between 60% and 85% of maximum age-predicted HR. However, the resultant changes in metabolic and functional measures vary. Some studies9,24–26 demonstrate improved

O2peak, whereas others reveal improvements (decreases) in gait economy poststroke2,5,24,27; the latter is accomplished by increasing walking speeds, with small gains in VO2,6 decreasing

O2 at similar walking speeds,2,24,27 or both. Despite these improvements, recent studies suggest inconsistent improvements in walking function and small or negligible correlations between metabolic and locomotor changes.2,9,20

Reasons for the inconsistent findings across studies are not clear but may be related to differences in study inclusion criteria or training strategies. In individuals with chronic (>6 months) stroke,9,17,19 consistent improvements in

O2peak are observed with training as compared with those with subacute stroke,14,15 although many of the former studies focus on treadmill training. However, in individuals with subacute stroke, many training strategies focus on nonstepping tasks,10–12,16,20 with inconsistent locomotor improvements. Conversely, and with limited exceptions,22,28 most gait training strategies delivered early poststroke do not focus on achieving higher (aerobic) intensities.

The present investigation represents a secondary analysis from 2 separate studies29–31 detailing the effects of a 10-week (≤40 sessions), high-intensity stepping training protocol on metabolic measures in individuals with subacute stroke. The published experimental interventions focused on providing practice of variable stepping tasks at high aerobic intensities (70%-80% HR reserve). Gains in locomotor and nonlocomotor measures have been described previously from both a randomized controlled trial (RCT) comparing this training strategy with conventional therapy29 and in a pilot experimental study that served as the basis for the RCT.30,31 In the present analysis, we were specifically interested in changes in aerobic performance during graded treadmill testing and overground walking in individuals with subacute stroke at baseline (BSL), following training (POST), and at a 2- to 3-month follow-up (F/U) assessment. We hypothesized that variable stepping training performed at high aerobic intensities would lead to substantial gains in peak metabolic capacity and economy during stepping that would be associated with walking performance.

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METHODS

Changes in locomotor and metabolic functions in individuals 1 to 6 months poststroke were assessed following an 8- to 10-week, experimental, high-intensity stepping training paradigm30,31 or conventional interventions.32,33 Data from both an assessor-blinded RCT comparing the 2 interventions29 and a nonblinded, pilot experimental study30 that used nearly identical inclusion criteria are incorporated in this analysis.

Inclusion criteria for the combined sample consisted of the following: history of unilateral, supratentorial stroke 1 to 6 months previously; 18 to 75 years of age; ability to walk with at least moderate assistance (able to perform at least 50% of work to ambulate) up to walking without physical assistance but with braces and devices as necessary but 0.9 m/s or less overground at self-selected pace; ability to follow 3-step commands or Mini-Mental Status Examination score of more than 22/30; and medical clearance to participate. In addition, metabolic data were available only for participants who were able to walk at 0.1 m/s or more, or the minimum speed, on a motorized treadmill during graded exercise testing. Exclusion criteria consisted of the following: cardiovascular, respiratory, or metabolic instability; inability to ambulate more than 45.7 m independently prior to stroke; history of other nervous system injury; and inability to adhere to study requirements. All procedures were approved by the Northwestern University institutional review board, and participants provided written informed consent.

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Randomization and Intervention

From the experimental pilot study,30 data from 9 of 12 subjects with subacute stroke are included, with 3 excluded because of inability to ambulate on the treadmill at 0.1 m/s (n = 2) or equipment failure (n = 1) at BSL. From the RCT,29 data from 24 of 33 subjects are included (n = 12 experimental; n = 12 control), with 8 others unable to walk at 0.1 m/s at BSL for 2 minutes. For 1 additional experimental subject, an assessor could not be blinded for any outcome, and their data were excluded from all analysis. There were no additional dropouts in the RCT or pilot studies. Data from both studies used similar inclusion criteria and training protocols and are included to demonstrate consistency of outcomes. All participants wore validated accelerometers (StepWatch; Modus, Inc., Washington, D.C.) on their paretic ankle throughout the study duration to evaluate stepping activity both during and outside of therapy sessions.

The goal of experimental training was to provide continuous stepping practice in multiple, variable environments while maintaining the cardiovascular training zone of 70% to 80% of HR reserve or ratings of perceived exertion (RPE) of 15 to 17 on the 6-20 Borg scale.34 Heart rate was monitored during training using pulse oximeters. For individuals on β-blockers, the target HR training zone was lowered to 10 beats/min.35 Participants were provided up to forty 1-hour training sessions over 10 weeks. During each session, subjects performed up to 40 minutes of stepping, with rest breaks as needed. The first 5 to 10 sessions consisted of forward treadmill training, with limited body weight support provided and with body weight support reduced as quickly as possible. The primary focus was on increasing treadmill speed to reach the targeted aerobic intensities as quickly as possible (ie, speed-dependent treadmill training). A safety harness was used during treadmill training only as a safety precaution, with no weight support provided. Remaining sessions included 25% forward treadmill walking, 25% variable walking on the treadmill (skill-dependent treadmill training), 25% overground training, and 25% stair climbing. Skill-dependent treadmill training was performed by applying perturbations to challenge postural stability, propulsion, and limb swing and included walking in multiple directions, over inclines and obstacles, and/or with weighted vests and leg weights, with limited handrail use as tolerated.36 Perturbations were applied such that 2 to 5 different tasks were randomly alternated and repeated within 10-minute periods. Overground training focused on fast walking speeds or variable tasks as described earlier, with use of a gait belt or overhead mobile or rail suspension system for safety. Stair climbing was performed over static or rotating stairs (StairMaster, Vancouver, Washington) using reciprocal gait patterns with progression to higher speeds and reduced handrail use. If specific tasks were not practiced during individual sessions, subsequent sessions focused on missed tasks. Blood pressure was monitored throughout training; subjects were not trained if resting blood pressure was greater than 220/110 mm Hg at rest, and training was discontinued each session if blood pressure surpassed 240/110 mmHg.37 Step activity monitors allowed estimation of the total amount of stepping practice during sessions and comparisons between training groups.

The goal of conventional (control) training was to provide standard physical therapy interventions, consistent with typical clinical practice observed during treatment of persons poststroke. Participants who received conventional training (n = 12) continued with clinical physical therapy as possible without influence from research personnel. Details of the types and amounts of therapeutic activities were extracted from medical records as possible, with stepping activities also recorded during sessions. The number of conventional (control) therapy sessions was supplemented by research staff in an effort to achieve 40 sessions over 10 weeks, similar to experimental therapy. Interventions during supplemented sessions focused on practice of multiple therapeutic tasks consistent with published reports of conventional therapy activities.32 The amounts and types of activities derived from published data included (mean repetitions [confidence intervals]) active lower extremity exercises (75 [58-93]), passive/stretching exercises (12 [9-16]), transfers (11 [9-13]), balance activities (27 [19-35]), gait (357 [296-418]), and stairs (3 episodes [2-4]). The targeted amount of stepping activity delivered during supplemental sessions was augmented on the basis of a separate observational study that provided larger amounts of stepping practice (ie, 800-900 steps per session).2 Stepping practice occurred both on the treadmill and on the overground/stairs, without limitations on cueing and feedback. Intensity of stepping was targeted at 30% to 40% of their HR reserve, consistent with observational data of HR ranges during therapy in subacute stroke.33 The treating physical therapist progressed participants with devices and bracing as appropriate. Of the conventional interventions, approximately 62% were supplemented by research staff, with detailed records of activities available in 70% of all therapies. Additional records from participants performing clinical physical therapy at other rehabilitation centers were often not accessible, or the types and amounts of activities were not well described. In addition, stepping activities was recorded in approximately 76% of all sessions (detailed later and in Table 1).

Table 1

Table 1

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Measures

Metabolic testing was performed at BSL, POST, with a 2- to 3-month F/U during a graded-intensity exercise test on a motorized treadmill and during a 6-Minute Walk Test (6MWT). Cardiopulmonary data were collected on a breath-by-breath basis during testing using a portable indirect calorimeter (CosMed USA Inc, Chicago, Illinois) calibrated prior to each assessment. Data were collected for 2 minutes during quiet sitting (resting

O2). For graded exercise testing, participants walked on a treadmill, with unilateral handrail use if needed and an overhead safety harness in case of loss of balance (ie, no weight support). Testing began at 0.1 m/s for 2 minutes, with speeds increased by 0.1 m/s every 2 minutes. Heart rate was evaluated using a pulse oximeter (Masimo, Irvine, California), and HR and RPE were recorded every 2 minutes. Testing ended when participants could no longer take steps, stated they could not continue, or if HR reached 85% of age-predicted maximum. Testing HRs were limited to 85% predicted maximum consistent with the American College of Sports Medicine guidelines without previous stress testing.38 Given the HR limitations and motor impairments of participants, graded exercise testing was considered a submaximal exercise assessment. For determination of O2cost during the 6MWT, participants walked overground for 6 minutes at their self-selected pace to minimize fall risk, with evaluation of cardiopulmonary measures as described earlier. Two participants (1 experimental RCT, 1 control RCT) who were able to walk at the minimum treadmill speeds could not perform the entire 6MWT without physical assistance, and their data for O2cost are excluded. Additional walking measures included self-selected speeds (SSS) and fastest-possible speeds (FS) performed over an instrumented walking platform (Equitest, Inc, Chalfont, Pennsylvania) and averaged over 2 trials.

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Data Analysis

Peak metabolic capacity during submaximal testing (

O2submax) was defined as the average

O2 during the last 30 seconds of the fastest speed achieved, and O2cost was calculated by dividing average

O2 by peak speeds. Metabolic data at POST and F/U were also analyzed at the peak speed achieved during BSL testing (ie, “matched” speeds). Data at these matched speeds (

O2match) were compared separately to estimate the contribution of improvements in O2cost (ie, decreased

O2) at BSL speeds with training. Secondary measures included minute ventilation (

E, mL/min), HR (beats/min), respiratory exchange ratio (RER =

CO2/

O2), and the oxygen uptake efficiency slope (OUES),39 an index of cardiopulmonary reserve that estimates O2 extraction and peripheral utilization. The OUES provides the ability to assess aerobic capacity without the need for maximal effort during testing39,40 and can be utilized in individuals who may not be able to achieve maximal exertion.41 The OUES was calculated as the slope of the log [

E/

O2] for each individual and performed if data were collected at 2 or more speeds (necessary for slope calculation).40 During the 6MWT,

O2 was averaged over the last 3 minutes of walking and O2cost was determined by dividing

O2 by average speed (m/min).

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Statistical Analysis

Outcomes were assessed for normality using the Kolmogorov-Smirnov test with only O2cost not normally distributed, although normalization (square-root) revealed similar changes to non-normalized data and the latter are presented. Primary measures included changes in

O2submax and O2cost at the highest treadmill speeds at each test, the OUES, and

O2match (ie,

O2 achieved during POST or F/U testingat peak BSL speeds). For the RCT, 2-way repeated-measures analysis of variance (ANOVA) was used to compare measures with main effects of groups (experimental vs control) and time (BSL, POST, F/U) but specific interest in the group × time interactions. Significance was adjusted to correct for multiple ANOVAs (ie, α = .0125). For the pilot study, separate repeated-measures ANOVAs were performed.

Secondary measures included

E, percentage of predicted HRmax achieved, RPE, and RER. Separate ANOVAs were performed for comparison of changes between groups at each assessment at peak treadmill speeds (ie, BSL, POST, F/U) and at speeds matched to peak BSL (BSL, POST-match, F/U-match). Repeated-measures ANOVAs were also calculated for testing during the 6MWT, with emphasis on O2cost and

O2 during the last 3 minutes of testing. Separate statistical calculations were made for pilot study. Pearson correlation analyses and multiple linear regressions were used to evaluate the relationship between selected metabolic and clinical measures at BSL and POST assessments. For regressions, we were interested in the relative contributions of changes in

O2submax and

O2match on locomotor outcomes (peak speed and walking speeds overground). Residuals were checked for normality and collinearity was monitored, with variance inflation factors less than 3.0 considered acceptable. Because of the exploratory nature of the correlation analysis, Bonferroni corrections were not performed. SPSS (version 21) and Stat View (SAS Institute Inc, version 5.0.1) were used for all analyses.

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RESULTS

Demographic data from 33 participants who completed the study (RCT: 12 experimental vs 12 control; pilot: 9 experimental) are presented in Table 1, with no differences between groups. Training characteristics are also presented, indicating no differences in the average number of training sessions but large differences in stepping amount and intensity. In the RCT, significant differences were observed for mean steps per session (P < .01) and mean peak HR per session documented in records (P < .01).

Similar stepping amounts and intensities were observed in the pilot study as in the experimental RCT group. Adverse events are also listed in Table 1, with nonsignificant differences across groups. Slightly higher rates of hypertension were observed in the experimental groups, whereas small increases in fall events were observed in the control group. Baseline and changes in clinical locomotor measures have been presented previously.29,30 Data included from the RCT29 indicate significant differences in gains between training groups at POST for SSS (experimental: Δ0.31 ± 0.23 m/s; control: Δ0.10 ± 0.10 m/s), FS (Δ0.40 ± 0.39 vs Δ0.12 ± 0.16 m/s), and 6MWT (141 ± 119 vs 29 ± 28 m), with all differences maintained at F/U. Similar gains following experimental training were observed in the pilot study (eg, SSS: Δ0.34 ± 0.23 m/s; FS: Δ0.47 ± 0.23 m/s; 6MWT: Δ132 ± 93 m).30

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Cardiopulmonary Outcomes During Treadmill Testing

At BSL, graded treadmill testing was terminated in 25 of 33 (76%) participants before reaching 85% maximum predicted HR secondary to gait instability or subjective termination. All data were similar between groups at BSL in the RCT, although specific measures were altered following training. Peak BSL speeds were not different between RCT training groups, with greater gains (group × time interaction; P < .001) observed at POST and F/U. Changes in the pilot study were also significant and slightly larger than those observed in the RCT experimental groups. Assessment of metabolic parameters revealed variable improvements as depicted in Figures 1A and 1B in 2 participants who performed experimental training. In Figure 1A, one subject demonstrated gains in

O2submax with little changes in

O2match, whereas the subject in Figure 1B demonstrated no increase in

O2submax but large decreases in

O2match.

Figure 1

Figure 1

Details regarding changes in primary metabolic measures from BSL to POST and F/U are given in Table 2. In the RCT, significant group × time interactions were observed for

O2submax favoring experimental training (P <.01), with large differences at POST that were sustained at F/U. Similarly, significant group × time interactions (P < .01) were observed for the OUES. In contrast, there were no significant interactions for changes in

O2match at peak BSL speeds (P = .48) or for O2cost (P =.29). Pilot data revealed similar gains in

O2submax as the experimental RCT groups. However, smaller improvements in the OUES were not significant and changes in O2cost were larger.

Table 2

Table 2

Changes in secondary cardiopulmonary and subjective measures at both peak and matched speeds in the RCT and pilot study are provided in Table 3. In the RCT, group × time interactions at peak speeds approached significance for

E and RPE, favoring experimental training. At matched peak BSL speeds, significant interactions were observed only for RER, favoring experimental training. Similar trends were observed in the pilot study as compared with experimental groups, including higher values of

E and lower RPE at peak speeds and lower RER values at matched speeds.

Table 3

Table 3

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Cardiopulmonary Outcomes During Overground Testing

Changes in metabolic parameters collected during the 6MWT were compared between groups (Table 4). While speeds during 6MWT were certainly different between groups, there were no significant group × time interactions for either

O2 or O2cost despite significant time effects for both variables. Similar changes were observed in the pilot study.

Table 4

Table 4

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Associations Between Metabolic and Locomotor Outcomes

Correlation and regression analyses were performed between changes in walking function and metabolic measures from BSL to POST using all data, with selected examples depicted in Figures 2A and B. Significant low to moderate correlations were observed between Δ

O2submax and ΔSSS (r = 0.47, P < .01), ΔFS (r = 0.64, P < .01), and Δpeak treadmill speeds (r = 0.66, P < .01; Figure 2A) but not Δ6MWT (r = 0.24, P = .17). In contrast, Δ

O2match demonstrated low, negative correlations with all walking outcomes (r = −0.19 to −0.34); only the correlation with Δpeak treadmill speed was significant (P = .04; Figure 2B). However, stepwise, multiple linear regression analysis revealed that both Δ

O2submax and Δ

O2match contributed significantly to ΔSSS, ΔFS, and Δpeak treadmill speed:

Figure 2

Figure 2

The resultant regression equations indicate similar β coefficients for Δ

O2submax and Δ

O2match, suggesting these variables may be additive. Accordingly, the association between the difference in Δ

O2submax and Δ

O2match at POST (ie, Δ

O2submax − Δ

O2match) and changes in walking outcomes reveals very similar strength of associations as revealed in the regression analyses. This relation is demonstrated for Δpeak treadmill speed (r2 = 0.80; Figure 2C) but were also similar for ΔSSS (r2 = 0.45) and ΔFS (r2 = 0.49; all Ps < .01). A smaller but significant relation between combined metabolic changes (Δ

O2submax − Δ

O2match) and Δ6MWT was also observed (r2 = 0.26, P = .002).

Secondary correlation analysis revealed no correlations between demographic and BSL functional characteristics with Δ

O2submax or Δ

O2match, with the exception of a low but significant negative correlation between Δ

O2match and BSL

O2submax (r = −0.41, P = .04; ie, those with larger BSL

O2submax demonstrated larger decreases in

O2match).

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DISCUSSION

The present study delineates changes in aerobic performance during treadmill walking following high-intensity stepping training or conventional interventions in individuals with subacute stroke. Greater improvements in

O2submax were observed following experimental training, with smaller decreases in

O2match and O2cost that were not different from changes following conventional training. Nonetheless, regression analyses indicate a potential contribution of improvements in both

O2submax and

O2match to walking outcomes.

The improvements in

O2submax following experimental training were consistent with data from participants with chronic stroke following 3 to 6 months of aerobic treadmill exercise (for review, see the study by Pang et al26). The present study represents one of few performed in participants with subacute stroke that demonstrates substantial gains in both metabolic and locomotor functions and correlations between these changes. We believe these findings are due to the focus on locomotor activities as the primary intervention and assessment of metabolic function with a locomotor task. Conversely, many training studies performed on participants early poststroke provide interventions focused on practice of multiple tasks20,22 or on nonwalking interventions (recumbent stepping15,16 or ergometry10–12,14), with metabolic assessments performed during other nonwalking assessments. Minimal associations between metabolic and locomotor outcomes may be due to the lack of specificity of the metabolic testing protocol either to trained activities or to walking assessments. In contrast, the present data are consistent with a recent study that examined the effects of body weight–supported treadmill training (BWSTT) on combined walking and aerobic outcomes early poststroke.28 In their participant population (mean duration poststroke <30 days), similar (∼30%) changes in

O2peak tested during treadmill stepping were observed, with significant improvements in walking outcomes. This latter trial is of additional interest as the authors focused on providing higher intensity of training, whereas previous BWSTT paradigms have not focused on aerobic capacity.21 The present and previous studies suggest training that simultaneously focuses on stepping practice on a treadmill or over multiple variable environments may improve both walking and metabolic outcomes, as well as their associations.

Consistent with previous data, however, changes in

O2submax and O2cost at fastest or at matched speeds (

O2match) observed here demonstrated moderate42 or low correlations9 to gains in walking function. Regression analyses and combined changes in

O2submax and

O2match24,27 indicate much stronger associations, however, and account for some of the variability between subjects (Figure 1). This combined measure reflecting changes in both peak metabolic capacity and economy may be helpful in future studies investigating altered metabolic demands with exercise training. Why participants demonstrate gains in metabolic capacity or economy or both is of interest, however. Increasing gait speed during treadmill stepping requires greater oxygen uptake by active musculature43–45 and readily accounts for the observed changes in

O2submax. Walking at higher speeds with smaller changes in

O2 could account for improvements in O2cost, particularly if the individuals poststroke do not walk at their most economical speeds.5 The changes in

O2 at matched speeds are of particular interest, and the negative correlation with BSL

O2submax suggests that initial walking strategies in many participants were metabolically inefficient but improved with training. Mechanisms underlying those changes with training are not clear. Long-standing data suggest that muscle coactivation decreases during motor learning,46 although few studies have indicated that changes in muscle timing occurs in persons poststroke47,48 (see, however, the study by Clark et al49). More recent studies in participants with neurologic impairment8,50 indicate that mechanical factors, such as improved walking symmetry50 or alterations in center-of-mass movement,8 may improve gait economy. Investigation of these factors is beyond the scope of the present study, although warrants further investigation.

A related interesting finding was the lack of significant differences in O2cost between groups during treadmill or overground testing. The increase in

O2 during 6MWT testing may have minimized differences in O2cost, and this measure may not be as sensitive to change in persons with subacute stroke with substantial impairments. Furthermore, the correlations of changes in metabolic measures with gains in the 6MWT were the lowest across walking measures. The combined findings may also suggest that changes in the 6MWT may not be reflective of changes in aerobic endurance or capacity.

Limitations of the present study include the lack of blinding of assessors and a control group for the pilot study. However, changes in locomotor and metabolic outcomes were consistent between the pilot study and the RCT, and preliminary findings corroborate the consistency of metabolic and locomotor changes. Furthermore, the control group was exposed to both regular clinical therapy and more standardized interventions delivered by research staff during supplemental sessions. The activities performed during these clinical sessions were not accessible or well documented, and the tasks performed are not entirely clear. Such treatment is often typical of “usual care” delivered in other training studies, where the amounts and types of activities are often not accounted for. In the present study, we attempted to provide some estimate of activities by monitoring stepping activity during sessions, although alternative strategies may be needed to more precisely document clinical practice patterns performed in remote settings. Another limitation is the estimation of

O2peak during treadmill testing, which was limited by motor impairments in most participants or by HR limitations. As such,

O2submax assessed during the graded treadmill testing is not a definitive measure of individual's maximal aerobic capacity, although this is difficult to avoid in persons with substantial gait impairments poststroke. The use of the OUES was calculated to provide a surrogate measure of aerobic function and helps substantiate the hypothesis that differences in peak

O2 were likely.

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CONCLUSIONS

Training strategies to improve locomotor and metabolic performance using task-specific practice at high aerobic intensities are fairly well-established in persons who are neurologically intact and persons with chronic neurologic injury who are higher functioning. However, these strategies are not well developed, or in many cases have not been tested, in persons early poststroke.51 Simultaneously focusing on both specificity and intensity of training activities, may contribute to changes in neuromuscular, cardiopulmonary, and metabolic systems. This approach may facilitate gains in both mobility and health outcomes, thereby improving the efficiency of rehabilitation sessions.

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REFERENCES

1. Gray CS, French JM, Bates D, Cartlidge NE, James OF, Venables G. Motor recovery following acute stroke. Age Ageing. 1990;19(3):179–184.
2. Moore JL, Roth EJ, Killian C, Hornby TG. Locomotor training improves daily stepping activity and gait efficiency in individuals poststroke who have reached a “plateau” in recovery. Stroke J Cereb Circ. 2010;41(1):129–135.
3. Michael KM, Allen JK, Macko RF. Reduced ambulatory activity after stroke: the role of balance, gait, and cardiovascular fitness. Arch Phys Med Rehabil. 2005;86(8):1552–1556.
4. Patterson SL, Forrester LW, Rodgers MM, et al. Determinants of walking function after stroke: differences by deficit severity. Arch Phys Med Rehabil. 2007;88(1):115–119.
5. Reisman DS, Binder-MacLeod S, Farquhar WB. Changes in metabolic cost of transport following locomotor training poststroke. Top Stroke Rehabil. 2013;20(2):161–170.
6. Reisman DS, Rudolph KS, Farquhar WB. Influence of speed on walking economy poststroke. Neurorehabil Neural Repair. 2009;23(6):529–534.
7. Smith AC, Saunders DH, Mead G. Cardiorespiratory fitness after stroke: a systematic review. Int J Stroke. 2012;7(6):499–510.
8. Stoquart G, Detrembleur C, Lejeune TM. The reasons why stroke patients expend so much energy to walk slowly. Gait Posture. 2012;36(3):409–413.
9. 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 J Cereb Circ. 2005;36(10):2206–2211.
10. Katz-Leurer M, Sender I, Keren O, Dvir Z. The influence of early cycling training on balance in stroke patients at the subacute stage. Results of a preliminary trial. Clin Rehabil. 2006;20(5):398–405.
11. Katz-Leurer M, Shochina M, Carmeli E, Friedlander Y. The influence of early aerobic training on the functional capacity in patients with cerebrovascular accident at the subacute stage. Arch Phys Med Rehabil. 2003;84(11):1609–1614.
12. Katz-Leurer M, Carmeli E, Shochina M. The effect of early aerobic training on independence six months post stroke. Clin Rehabil. 2003;17(7):735–741.
13. Bateman A, Culpan FJ, Pickering AD, Powell JH, Scott OM, Greenwood RJ. The effect of aerobic training on rehabilitation outcomes after recent severe brain injury: a randomized controlled evaluation. Arch Phys Med Rehabil. 2001;82(2):174–182.
14. Tang A, Sibley KM, Thomas SG, et al. Effects of an aerobic exercise program on aerobic capacity, spatiotemporal gait parameters, and functional capacity in subacute stroke. Neurorehabil Neural Repair. 2009;23(4):398–406.
15. Billinger SA, Mattlage AE, Ashenden AL, Lentz AA, Harter G, Rippee MA. Aerobic exercise in subacute stroke improves cardiovascular health and physical performance. J Neurol Phys Ther. 2012;36(4):159–165.
16. Mattlage AE, Ashenden AL, Lentz AA, Rippee MA, Billinger SA. Submaximal and peak cardiorespiratory response after moderate-high intensity exercise training in subacute stroke. Cardiopulmonary Phys Ther J. 2013;24(3):14–20.
17. Luft AR, Macko RF, Forrester LW, et al. Treadmill exercise activates subcortical neural networks and improves walking after stroke: a randomized controlled trial. Stroke J Cereb Circ. 2008;39(12):3341–3350.
18. Macko RF, Ivey FM, Forrester LW. Task-oriented aerobic exercise in chronic hemiparetic stroke: training protocols and treatment effects. Top Stroke Rehabil. 2005;12(1):45–57.
19. Globas C, Becker C, Cerny J, et al. Chronic stroke survivors benefit from high-intensity aerobic treadmill exercise: a randomized control trial. Neurorehabil Neural Repair. 2012;26(1):85–95.
20. Duncan P, Studenski S, Richards L, et al. Randomized clinical trial of therapeutic exercise in subacute stroke. Stroke. 2003;34(9):2173–2180.
21. Duncan PW, Sullivan KJ, Behrman AL, et al. Body-weight-supported treadmill rehabilitation after stroke. N Engl J Med. 2011;364(21):2026–2036.
22. Eich HJ, Mach H, Werner C, Hesse S. Aerobic treadmill plus Bobath walking training improves walking in subacute stroke: a randomized controlled trial. Clin Rehabil. 2004;18(6):640–651.
23. Pang MY, Eng JJ. Determinants of improvement in walking capacity among individuals with chronic stroke following a multi-dimensional exercise program. J Rehabil Med. 2008;40(4):284–290.
24. Macko RF, Smith GV, Dobrovolny CL, Sorkin JD, Goldberg AP, Silver KH. Treadmill training improves fitness reserve in chronic stroke patients. Arch Phys Med Rehabil. 2001;82(7):879–884.
25. Gjellesvik TI, Brurok B, Hoff J, Torhaug T, Helgerud J. Effect of high aerobic intensity interval treadmill walking in people with chronic stroke: a pilot study with one year follow-up. Top Stroke Rehabil. 2012;19(4):353–360.
26. Pang MY, Charlesworth SA, Lau RW, Chung RC. Using aerobic exercise to improve health outcomes and quality of life in stroke: evidence-based exercise prescription recommendations. Cerebrovasc Dis. 2013;35(1):7–22.
27. Macko RF, DeSouza CA, Tretter LD, et al. Treadmill aerobic exercise training reduces the energy expenditure and cardiovascular demands of hemiparetic gait in chronic stroke patients. A preliminary report. Stroke. 1997;28(2):326–330.
28. Mackay-Lyons M, McDonald A, Matheson J, Eskes G, Klus MA. Dual effects of body-weight supported treadmill training on cardiovascular fitness and walking ability early after stroke: a randomized controlled trial. Neurorehabil Neural Repair. 2013;27(7):644–653.
29. Hornby TG, Holleran CL, Hennessy PW, et al. Variable Intensive Early Walking post-Stroke (VIEWS): a randomized controlled trial. Neurorehabil Neural Repair. 2016;30(5):440–450.
30. Holleran CL, Straube DD, Kinnaird CR, Leddy AL, Hornby TG. Feasibility and potential efficacy of high-intensity stepping training in variable contexts in subacute and chronic stroke. Neurorehabil Neural Repair. 2014;28(7):643–651.
31. Straube DD, Holleran CL, Kinnaird CR, Leddy AL, Hennessy PW, Hornby TG. Effects of dynamic stepping training on nonlocomotor tasks in individuals poststroke. Phys Ther. 2014;94(7):921–933.
32. Lang CE, MacDonald JR, Gnip C. Counting repetitions: an observational study of outpatient therapy for people with hemiparesis post-stroke. J Neurol Phys Ther. 2007;31(1):3–10.
33. MacKay-Lyons MJ, Makrides L. Cardiovascular stress during a contemporary stroke rehabilitation program: is the intensity adequate to induce a training effect? Arch Phys Med Rehabil. 2002;83(10):1378–1383.
34. Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377–381.
35. Cohen-Solal A, Baleynaud S, Laperche T, Sebag C, Gourgon R. Cardiopulmonary response during exercise of a beta 1-selective beta-blocker (atenolol) and a calcium-channel blocker (diltiazem) in untrained subjects with hypertension. J Cardiovasc Pharmacol. 1993;22(1):33–38.
36. Holleran CL, Rodriguez KS, Echauz A, Leech KA, Hornby TG. Potential contributions of training intensity on locomotor performance in individuals with chronic stroke. J Neurol Phys Ther. 2015;39(2):95–102.
37. Pescatello LS, Franklin BA, Fagard R, et al. American College of Sports Medicine position stand. Exercise and hypertension. Med Sci Sports Exerc. 2004;36(3):533–553.
38. Johnsone EP. American College of Sports Medicine: Guidelines for Exercise Testing and Prescription. 6th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2000.
39. Baba R, Nagashima M, Goto M, et al. Oxygen uptake efficiency slope: a new index of cardiorespiratory functional reserve derived from the relation between oxygen uptake and minute ventilation during incremental exercise. J Am Coll Cardiol. 1996;28(6):1567–1572.
40. Hollenberg M, Tager IB. Oxygen uptake efficiency slope: an index of exercise performance and cardiopulmonary reserve requiring only submaximal exercise. J Am Coll Cardiol. 2000;36(1):194–201.
41. Van Laethem C, Bartunek J, Goethals M, Nellens P, Andries E, Vanderheyden M. Oxygen uptake efficiency slope, a new submaximal parameter in evaluating exercise capacity in chronic heart failure patients. Am Heart J. 2005;149(1):175–180.
42. Pohl PS, Perera S, Duncan PW, Maletsky R, Whitman R, Studenski S. Gains in distance walking in a 3-month follow-up poststroke: what changes? Neurorehabil Neural Repair. 2004;18(1):30–36.
43. Grabowski A, Farley CT, Kram R. Independent metabolic costs of supporting body weight and accelerating body mass during walking. J Appl Physiol. 2005;98(2):579–583.
44. Gottschall J, Kram R. Energy cost and muscular activity required for propulsion during walking. J Appl Physiol. 2003;94(5):1766–1772.
45. Gottschall J, Kram R. Energy cost and muscular activity required for leg swing during walking. J Appl Physiol. 2005;99(1):23–30.
46. Enoka RM. Neural adaptations with chronic physical activity. J Biomech. 1997;30(5):447–455.
47. Kautz SA, Duncan PW, Perera S, Neptune RR, Studenski SA. Coordination of hemiparetic locomotion after stroke rehabilitation. Neurorehabil Neural Repair. 2005;19(3):250–258.
48. Den Otter AR, Geurts AC, Mulder T, Duysens J. Gait recovery is not associated with changes in the temporal patterning of muscle activity during treadmill walking in patients with post-stroke hemiparesis. Clin Neurophysiol. 2006;117(1):4–15.
49. Clark DJ, Ting LH, Zajac FE, Neptune RR, Kautz SA. Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke. J Neurophysiol. 2010;103(2):844–857.
50. Awad LN, Palmer JA, Pohlig RT, Binder-Macleod SA, Reisman DS. Walking speed and step length asymmetry modify the energy cost of walking after stroke. Neurorehabil Neural Repair. 2015;29(5):416–423.
51. Katch VL, McArdle WD, Katch FI. Essentials of Exercise Physiology. Baltimore, MD: Lippincott Williams & Williams; 2011.
Keywords:

aerobic; gait training; human movement system; locomotion; rehabilitation

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