Norman, Joseph F. PT, PhD, CCS; Bossman, Scott MPT; Gardner, Paul MPT; Moen, Craig MPT
The energy expenditure during gait in children with spastic cerebral palsy (CP) is significantly higher than for children without physical disabilities (ND).1–3 Lower mechanical efficiency during ambulation due to the loss of selective motor control, impaired balance, abnormal tone, weakness, and loss of range of motion contribute to the increased energy cost.2–5 In addition to the decreased mechanical efficiency, fatigue has been identified as a significant limitation for children with CP, which may be reflective of a reduced metabolic capacity at the muscle level.3,6 Being able to assess alterations in energy expenditure as a result of therapeutic interventions has important clinical ramifications in evaluating the effectiveness of interventions.
Oxygen consumption (VO2) is considered the gold standard for assessing energy expenditure during activity. Clinically, the most common method of measuring VO2 during activity has been by indirect calorimetry using a metabolic cart while the individual exercises on stationary equipment such as a treadmill or cycle ergometer. Assessing VO2 during functional activities such as free ambulation typically required the collection of expired gases by the Douglas bag method, which was more cumbersome, especially when evaluating children. Recent advances in technology have led to the development of portable metabolic gas analyzers that accurately measure VO2 and heart rate (HR) during functional activities.7,8 Clinical use of this newer technology is not yet widespread and may be cost prohibitive for many clinics. Until the cost of this newer technology decreases and the availability and use of portable metabolic gas analyzers becomes more commonplace in the clinic, use of more readily obtainable estimates of oxygen cost will still be important for clinicians when evaluating the energy expenditure associated with different interventions.
HR has been shown to be linearly related to oxygen uptake in healthy adults and children at submaximal workloads.9–11 Rose et al12 found a linear relationship between HR and oxygen uptake over a wide range of treadmill walking speeds for children who are ND and children with CP. The Energy Expenditure Index (EEI) has been advocated as a means of using the HR response to assess energy cost during ambulation by relating changes in HR to velocity.13 The EEI (beats/m) is calculated as the ambulation HR (beats/min) minus the resting HR (beats/min) divided by the ambulation velocity (m/min). The EEI has been shown to vary with different ambulatory speeds.14,15 For treadmill walking, Rose et al13 have shown that the oxygen uptake per meter mirrored changes in the EEI at various speeds for children who are ND and children with CP. Clinically, the EEI would appear to provide a convenient means of estimating differences in energy expenditure associated with ambulation at different velocities.
In clinical practice, it may not always be feasible or practical to test children at multiple walking speeds due to equipment or environmental limitations such as those found in a school setting. Also, it would be difficult for many children to consistently sustain multiple walking speeds during ambulation to use for comparisons. Corry et al7 found the oxygen cost, adjusted for velocity, of ambulating at self-paced walking speeds in children with CP and spina bifida were highly repeatable between trials conducted on different days. However, whether the EEI can be used as an estimate of the increase in oxygen cost, over baseline, at self-paced speeds has not been addressed specifically. This information would have clinical significance for assessing the effect on energy expenditure that an intervention may have at the velocity a child would normally ambulate.
This study was undertaken to compare the EEI with the velocity-adjusted oxygen cost of ambulating at self-paced walking speeds by children who are ND and children with spastic diplegia CP. The EEI has been shown to correspond with changes in oxygen uptake during treadmill walking at different speeds, but this measure has not been assessed specifically as predictive of oxygen uptake during free ambulation. The purpose of this study was to determine whether the HR response over baseline, adjusted for velocity (EEI), was predictive of the Oxygen Cost Index (OCI) which is the VO2 over baseline, adjusted for velocity, at self-paced walking speeds for children who are ND and children with spastic diplegia CP. Use of the EEI to estimate OCI would be relevant to clinicians in evaluating their interventions. We hypothesized that the EEI would be predictive of the OCI in children who are ND and children with spastic diplegia CP during ambulation at self-paced walking speeds.
Subjects were recruited from the Omaha, NE, area via newspaper advertisements, flyers, and personal contacts. Inclusion criteria for children with spastic diplegia CP included 1) a diagnosis of spastic diplegia CP; 2) seven to <18 years of age; 3) ambulatory, regardless of use of assistive devices or orthotics; 4) no significant endurance impairments due to cardiovascular limitations; and 5) no surgery within the past year. Study inclusion criteria for the children who were ND included confirmation of good health by a parent or guardian as well as 1) no diagnosis of CP or other neuromuscular disorder, 2) seven to <18 years of age, 3) no significant endurance impairments due to cardiovascular limitations, and 4) no surgery in the past year. Activity level of the children who were ND ranged from those who were sedentary, primarily participating in activities such as computer games, video games, and reading, to individuals active in multiple team sports such as soccer, basketball, and swimming.
Ten children with spastic diplegia CP and 15 children who were ND participated in this study (Table 1). Written assent and consent were obtained from the children and their parents or guardians, respectively. The study protocol and consent forms were reviewed and approved by the Institutional Review Board of the University of Nebraska Medical Center. The project was conducted in the Movement Science Laboratory and adjacent hallways of the Division of Physical Therapy Education at the University of Nebraska Medical Center.
Each subject and parents or guardians met with the investigators for orientation to the testing procedures and equipment. During that time the subject’s weight and height were obtained and the subject’s body mass index (BMI) calculated using the standard equation; BMI = body mass (kg) ÷ height (m2). Subjects were fitted with a nose and mouth silicone face mask (Hans Rudolph, Inc., Kansas City, MO) and Pneumotach, which were connected to the AeroSport KB1-C portable metabolic gas analyzer (Aero-Sport, Inc., Ann Arbor, MI). Subjects were allowed as much time as needed to become familiar with wearing and breathing through this apparatus; and it was explained that the device was measuring the volume and content of air that they exhaled.
Testing of each subject was performed during a single session, with four individuals agreeing to return for a repeat session. Parents of four of the children who were ND volunteered to bring their child back for repeat testing on the day after their initial test to assess the reliability of the measures. None of the parents of children with CP volunteered to have their child return for a repeat testing session.
Metabolic Gas Analysis
The AeroSport KB1-C portable metabolic gas analyzer was used to measure VO2, carbon dioxide production (VCO2), minute ventilation (VE), and HR during the testing procedure. The AeroSport KB1-C is a compact version of the AeroSport TEEM 100 metabolic gas analyzer, which has been previously shown to be a valid and reliable instrument for measuring VO2.16 Melanson et al16 reported no significant differences between VO2 measures obtained with the AeroSport TEEM 100 metabolic gas analyzer and a reference oxygen analyzer (Model S-3A1, Ametek, Pittsburgh, PA) between repeated trials of submaximal exercise. The mean difference between systems was 0.1 ± 0.1 L · min−1 with an intraclass reliability coefficient of r = 0.94.16
As gas is exhaled through the pneumotach, a sample proportional to the volume of gas exhaled is drawn into the micromixing chamber of the AeroSport KB1-C. As each microsample enters the mixing chamber, an equal volume of gas is emitted from the mixing chamber to the oxygen and carbon dioxide sensors. The AeroSport KB1-C uses a galvanic fuel cell as its oxygen sensor. Carbon dioxide is measured using the standard nondispersive infrared analysis technique.17 A Cardiosport HR transmitter (Sportsbeat/Cardiosport Inc., Deer Park, NY) was fitted to each child by an elastic chest strap allowing the HR receiver in the AeroSport KB1-C to concurrently record HR and VO2. The technology used in the HR monitoring system has accuracy for determining HR similar to that of an electrocardiograph.
The advantage of the AeroSport KB1-C metabolic gas analyzer is its small size and portability (<1 kg), making it ideal for measuring expired gases during normal activities. The AeroSport KB1-C was gas and flow calibrated according to manufacturer’s specifications prior to testing all subjects. The calibration gas used was composed of 20.0% O2, 5.0% CO2, and 75.0% nitrogen. A 3.88-L syringe (SR Medical, Dayton, OH) was used to perform all flow calibrations. During testing, the AeroSport KB1-C received continuous input, which it averaged and recorded every 20 seconds. The absolute VO2 (L · min−1) measured by the AeroSport KB1-C was converted to relative VO2 (mL O2 · kg−1 · min−1) for assessing the energy expenditure of subjects.
A small pilot study, with four of the children who were ND, was conducted concurrently in our laboratory to compare the VO2 and HR measures obtained with the Aero-Sport KB1-C between trials on consecutive days.
After each subject was familiarized with the equipment and the protocol was reviewed, the subject donned the face mask attached to the AeroSport KB1-C. Resting HR and VO2 were recorded while the subject sat quietly at rest for seven minutes. Rose et al15 reported true resting HR can be measured as the average HR taken over a two-minute period after subjects have been sitting quietly for five minutes. We calculated the average HR and VO2 measurements obtained over the last two minutes of the rest period (minutes six and seven) and used this average as our resting HR and VO2 baseline values. After collection of resting baseline HR and VO2, the subject used whatever assistive devices he or she normally used and was encouraged to walk at his or her normal everyday speed for six minutes. Each subject walked in a series of connecting hallways that formed a continuous 50-m oval path. As a subject walked laps around the hallways, an investigator walked behind for safety carrying the AeroSport KB1-C unit. The average self-paced ambulation velocity was calculated and recorded as meters/minute. Corry et al7 stated that steady-state HR and VO2 occur at approximately three minutes of low-level activity. We averaged the HR and VO2 data obtained over minutes four and five for data analysis. The subjects then rested in a sitting position for approximately 10 minutes until their HR and VO2 returned to near baseline values. The HR, VO2, and velocity data were used to calculate the EEI, oxygen cost, and OCI for comparisons. The EEI represents the increase in HR response, over the resting HR, divided by velocity and reported as beats per meter ambulated.13 The oxygen cost is defined as the overall VO2 per kilogram of body weight per meter walked (mLO2/kg/m).18 The overall VO2 used for calculating the oxygen cost included the resting VO2 value. We defined the OCI as the mean ambulation VO2 minus the mean resting VO2, divided by the velocity in meters per minute. The OCI is reported as mLO2 per kilogram of body weight per meter and indicates the increase in VO2 adjusted for velocity, over resting values, associated with walking. The OCI serves as a more activity specific measure of energy expenditure for a selected activity. These velocity-adjusted indices were used for comparison to account for differences in walking speeds between subjects.
Descriptive statistics and t tests were used to compare subjects’ group characteristics and self-paced ambulation characteristics.19 With the limited number of subjects, a Spearman rank order correlation analysis was selected to compare EEI with OCI during self-paced ambulation. For the test-retest comparison, a Wilcoxon signed rank test and Spearman rank order correlation were conducted. Statistical significance was set at p ≤ 0.05.
There were no significant differences (p > 0.05) between the two groups of children with regard to age, weight, height, BMI, or resting HR (Table 1). A higher resting VO2 was noted in the group of children with spastic diplegia CP compared with the group of children who were ND (Table 1). Comparisons of self-paced ambulation characteristics demonstrated significant differences between the groups with regard to HR, VO2, distance ambulated, velocity, EEI, oxygen cost, and OCI (Table 2).
Correlation analysis showed a fair to good correlation between EEI and OCI during self-paced ambulation for children with spastic diplegia CP (r = 0.61, p = 0.05) but only a moderate correlation for children who were ND (r = 0.40, p = 0.13). Figure 1 illustrates a scatter plot of the subjects’ EEI versus OCI values for each group of children. For the children who were ND, there were relatively small increases, over resting values, in VO2 and HR associated with walking at self-paced speeds. This resulted in a clustering of the data points of the children who were ND, just over resting values, compared with the children with spastic diplegia CP.
Test-retest comparisons demonstrated good repeatability of the VO2 and HR measurements during walking at self-paced speeds. No significant differences between VO2 and HR measures were noted between trials (p = 0.88 and p = 0.63, respectively), and the correlation coefficient for both measurements was r = 1.00.
Therapeutic interventions that affect gross motor ability may directly affect walking efficiency.14 Measuring oxygen uptake may be the best method of quantifying gait efficiency during functional walking.20 Collecting and interpreting energy expenditure values for children with CP during ambulation is an important aspect of the clinical decision-making process in evaluating various interventions and energy economy. We compared the increased HR response adjusted for velocity (EEI) with the increased VO2 adjusted for velocity (OCI) to assess the utility of the EEI as an indicator of energy expenditure for children with spastic diplegia CP and children who are ND at self-paced ambulation speeds. For children with spastic diplegia CP, a fairly strong functional relationship was found between the EEI and OCI during self-paced free ambulation. This would suggest that the EEI may have utility as a clinical indicator of the OCI for children with spastic diplegia CP ambulating at their customary walking speeds. However, for children who are ND, the relationship between EEI and OCI during self-paced ambulation was much weaker due to the relatively small changes in HR and VO2.
Duffy et al21 related the increased VO2 in children with spastic diplegia CP to their abnormal equilibrium reactions, which impair balance and speed control. They found that the VO2 for children with CP ambulating at self-paced speeds to be significantly greater than for normal children ambulating at self-paced speeds. Consistent with Duffy et al, we also found the VO2 for children with spastic diplegia CP, ambulating at self-paced speeds, to be significantly greater than for children who are ND. Duffy et al21 reported the average velocity for children with spastic diplegia CP in their study was 47.5 m/min and for children who were ND 69.1 m/min with a mean VO2 of 28.0 and 18.0 mLO2/kg/min, respectively. The mean self-paced velocities of our subjects were similar to those reported by Duffy et al; however, we found lower VO2 measurements associated with ambulating at those speeds. The mean self-paced velocity for children with CP in our study was 41.5 m/min with a mean VO2 of 19.7 mLO2/kg/min. Our findings were similar to those of Rose et al,12 who reported the VO2 for children with CP walking on a treadmill at approximately 41.5 m/min to be 20 mL/kg/min. For the children who were ND in our study, their mean self-paced velocity was 66.7 m/min with a mean O2 uptake of 6.3 mLO2/kg/min. The finding of Rose et al for children who were ND walking on a treadmill at approximately 66.7 m/min was 12 mLO2/kg/min.12 The difference in the O2 uptake noted between our study and that of Rose et al for the children who are ND can be partially accounted for by the lower mean resting VO2 of our subjects (2.9 ± 1.1 mLO2/kg/min) versus the subjects of Rose et al (4.9 ± 1.0 mLO2/kg/min). Rose et al13 found their estimates of energy expenditure based on HR and VO2 to be two to three times greater in the children with CP compared with children who are ND. Our findings also demonstrated a similar trend with a two- to threefold increase in HR and a three- to fourfold increase in VO2 noted during ambulation at self-paced speeds in children with spastic diplegia CP compared with children who are ND.
Bowen et al18 reported oxygen cost to be a more reliable oxygen-use measurement of energy expenditure than VO2 alone. The oxygen cost of ambulating at self-selected walking speeds for children with CP has been reported to range from 0.42 to 0.64 mLO2/kg/m.7,13,18,21 The calculated oxygen cost measurement for children with CP in our study was 0.55 mLO2/kg/m, which is consistent with values reported by other investigators. The oxygen cost measure takes into account the oxygen requirement on a per-meter basis and provides a means for comparing individuals or the same individual over time despite differences in walking velocity.
Although the overall oxygen cost takes into account walking speed, the VO2 value used to calculate it includes the individual’s resting VO2 value in addition to the increase in VO2 associated with activity.7,13,18,21 To more accurately evaluate the energy expenditure of a particular activity, the focus should be on the oxygen uptake of the activity alone and not on an oxygen cost calculation based on the resting and activity VO2 values. We calculated the increase in VO2 over resting value to determine the increase in oxygen uptake associated specifically with ambulation. By using the increase in oxygen uptake over resting levels and adjusting it for speed (OCI), a more accurate oxygen-use measurement of energy expenditure associated with ambulation could be determined. This methodology is consistent with the recommendation of the American College of Sports Medicine to use the increase in VO2 over resting VO2 to determine the actual oxygen uptake of physical activities.22 In addition, this approach is comparable with how the EEI is calculated and is a more accurate measure to use for comparing the change in oxygen uptake to the change in HR response for a particular activity.
The EEI has been shown to be responsive to different ambulatory speeds and use of various ambulatory aids.13,15,23 In addition, the EEI has been reported to decrease to a region of maximum energy economy for individuals at self-paced, comfortable walking speeds.15 Butler et al24 found that the EEI was not age related, making the EEI a convenient method for following a child with CP longitudinally over an extended period of time.
The unique aspect of this study was its design to assess EEI in a manner that would be of practical value in a variety of clinical settings. We used one ambulation speed, self-paced ambulation, versus multiple ambulatory speeds that would be difficult to duplicate in many settings in which children are treated. In addition, subjects were tested during free ambulation as opposed to treadmill walking, which can introduce artificial constraints on gait patterns in individuals with various gait deviations, thus altering their ambulation energy costs. The findings of this preliminary study suggest that EEI may be a valid clinical indicator of OCI for children with spastic diplegia CP ambulating at self-paced speeds but not for children who are ND ambulating at self-paced speeds. These findings are encouraging but warrant further investigation in a larger population of children with spastic diplegia CP.
There were a number of limitations to this study that would argue for caution in the general application of our findings. The small sample size, despite vigorous recruitment efforts to enroll more children with spastic diplegia CP, raises concerns of the applicability of using EEI to predict OCI in the overall population of children with spastic diplegia CP. The children with CP in this study may not be representative of all children with spastic diplegia CP as they had to ambulate independently for at least six minutes, without stopping to rest, and all were children able to ambulate safely in the public school setting. Also, with the small sample size in this study, differences, if any, that might exist between genders were not able to be adequately addressed. Additionally, all testing in this study was performed in a controlled setting on level, unobstructed hallways, which may limit the applicability of our findings to other terrains over which children with spastic diplegia CP walk.
Direct measurement of VO2 by indirect calorimetry is still considered the gold standard for accurately determining the energy expenditure of an activity such as ambulation. Currently, the equipment cost, practicality, and environmental limitations of certain clinical practice sites do not always lend themselves to using this methodological approach. Our preliminary findings suggest that for children with spastic diplegia CP who are able to ambulate on level terrain, the EEI may potentially prove to be a good clinical measure for estimating changes in the OCI associated with ambulation at self-paced speeds. This would have clinical significance for clinicians treating children with spastic diplegia CP in that the EEI, which is easily obtained clinically, could serve as a reasonable indicator of energy expenditure to assess therapeutic interventions.
We thank Elizabeth Lyden, MA, MS, Department of Preventative and Societal Medicine, University of Nebraska Medical Center, for her assistance with the statistical analysis of the data.
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