Methods: Twelve healthy subjects (group 1) and 12 patients with IC (group 2) participated in our study, one healthy control subject and three patients with IC were excluded from the study because of exclusion criteria, and remain 20 participants were evaluated (n=11 in group 1, n=9 in group 2). The participants walked on a treadmill at pre-determined speeds for the measurements of oxygen cost of walking by indirect calorimetry method. The IC questionnaire was administered prior to the test.
Results: The mean walking speed in group 1 was 77.8±11.4 m/min and 67.2±10.5 m/min in group 2 (p<0.05). The mean oxygen cost of the walking trial in healthy subjects was 0.14±0.02 mL/kg/m and 0.18±0.04 mL/kg/m in the patient group (p<0.05). In group 2, there was no correlation between the IC questionnaire score and oxygen cost, preferred walking speed, claudication pain scale score, and Borg score. The oxygen cost of walking was significantly correlated with the maximal walking distance (MWD) (p<0.05). There was a significant correlation between the initial claudication distance and Borg score and claudication pain scale score (p<0.001).
Conclusion: The metabolic efficiency of gait and the preferred walking speed may be reduced in PAD patients. Our study results suggest that oxygen cost of walking, preferred walking speed, Borg score, claudication pain scale score, initial claudication distance and MWD are objective parameters which can be used in monitoring the ambulatory limitation of PAD patients with IC.
Intermittent claudication (IC) is the most common symptom of PAD, and it affects approximately 40% of PAD patients.[4,5] While walking, the increased blood demand of the muscles in the lower extremities cannot be supplied by the occluded arterial system, which may cause the symptom of claudication. In addition, altered antioxidant capacity was also reported because of hypoxia.[6] Claudication leads to severe limitations in walking ability, which may result in decreased physical functioning.[1] Crowther et al.[3] declared that the kinematics of walking in IC patients is different than for healthy subjects.
The severity of disease and physical activity of patients with IC can be determined using both quantitative [ankle-brachial index (ABI), invasive or noninvasive radiological monitoring, and initial and maximal claudication distances] and qualitative parameters (the IC questionnaire together with other questionnaires) that can be used for assessing the quality life of patients with IC.[7] It is clear that the diagnosis of IC and the assessment of its treatment outcomes should rely on objective and quantitative criteria. Hiatt[8] reported that the treatment of IC should target an improvement in exercise capacity. To assess walking capacity, the initial claudication distance and the maximal walking distance are assessed for the evaluation of walking capacity, and the maximal walking distance is an important parameter that can be used for classifying the severity of a PAD based on the Fontaine or Rutherford classifications.[9]
The preferred walking speed (PWS) is a gait parameter that may have implications for determining overall gait performance.[10] In addition, the oxygen cost of walking is another gait parameter that revealed gait metabolic efficiency.[11] The energy consumption measurement while exercising on the treadmill is a reproducible method that can be adjusted by medical and surgical treatments of IC. However, exercise testing needs expensive laboratory equipment along with trained staff, and the requirements of an exercise laboratory preclude its use in daily clinical practice.[1] The oxygen cost of walking may lead to a discrimination between the normal and pathological gait.[11,12] Thus, the PWS and the oxygen cost of walking may provide objective and quantitative data for patients with IC.
The IC Questionnaire is an instrument for determining the quality of life in PAD patients with PAD-IC[13] while the Borg score and claudication pain scale serve as valuable tools for the assessment of perceived exertion and pain, respectively.[14,15]
The purpose of this study was to determine the differences in the PWS and oxygen cost of walking in both a group of patients with IC and in a healthy control group and determine how they correlate with the IC questionnaire, claudication pain scale, and Borg scores.
Statistical power analysis (MedCalc Software 11.3.3, Mariakerke, Belgium) was used to establish the appropriate sample size. According to the power analysis of the pilot study performed in our laboratory on patients with PAD-IC and healthy individuals, the minimal required sample size for each group was calculated as eight subjects (Oxygen costs were used in the power analysis; oxygen cost for group 1 = 0.14±0.01 mL/kg/m and for group 2 = 0.18±0.04 mL/kg/m).
Inclusion criteria
Newly diagnosed patients with no previous medical
treatment for PAD-IC participated in our study. Patients
with Fontaine stage IIa and IIb lower-extremity PAD
were chosen if they had an ABI of ≤0.90. This was
determined via invasive (digital subtraction angiography)
and/or non-invasive tests (Doppler ultrasound imaging
or magnetic resonance angiography).[1-9]
Exclusion criteria
Individuals with Fontaine stage III and IV PAD,
acute infectious disease, orthopedic problems,
gait abnormalities, recent lower extremity injuries,
or metabolic disorders (thyroid function disorders,
diabetes mellitus, etc.) along with those taking
medications that may affect their energy expenditure
were excluded from the study. In addition, any patients
that the clinician strongly suspected of having a
cardiovascular disease were excluded. Moreover, those with any contraindication for the exercise testing after
an examination of their medical history, physical
examination, and electrocardiography testing were
also not included.
Vascular testing
The measurements of the systolic pressures of the brachial
arteries, dorsalis pedis, and posterior tibial arteries
were obtained bilaterally while the patients were in the
supine position for 15 minutes using a handheld vascular
Doppler device (Datascope IABP Doppler DS900 8
MHz, Huntleigh, UK] and a standard sphygmomanometer
(Erka, Kallmeyer Medizintechnik GmbH, Germany). The
ABI was calculated by dividing the lowest systolic blood
pressure in the ankle into the higher of the brachial
systolic pressures for each lower limb.[17]
Questionnaire
Each of the participants filled out the IC questionnaire
(Turkish version) prior to the treadmill walking trials.[18]
This questionnaire is a disease-specific questionnaire
for the assessment of health-related quality of life in
patients with IC.[13] The validation and reliability of the
Turkish version of the IC questionnaire was achieved
by Ketenci et al.,[18] and the score is assessed by using
a 0-100 scale in which 0 represents the best possible
score and 100 indicates the worst possible health
condition.[13]
The treadmill walking protocol
The metabolic measurements while walking on the
treadmill were gathered in an exercise laboratory at
Mersin University, the Department of Physiology,
Yenişehir campus. The subjects came to the exercise
laboratory on two occasions. The PWS determination and
habituation trial to the treadmill walking were completed
on the first visit. On the second visit, the subjects only
performed the walking trial on the treadmill to measure
oxygen cost.
All subjects completed a standardized familiarization session on the treadmill for at least 10 minutes.[19] The elevation of the treadmill was set at a 0% grade, and the subjects were instructed to not hold onto the handrails while walking. The PWS of each subject was determined by overground locomotion prior to the treadmill walking tests for oxygen cost measurement to determine the PWS. The subjects were asked to walk at a natural pace along a 14-meter walkway, and the time for each trial was determined by using two infrared timing gates placed at the second and 12th meters. The PWS (meters/second) was calculated by dividing the distance walked (10 meters) by the average time of three walking trials.
Measurements of walking capacity
The subjects were instructed not to eat or drink (except
for water) for at least 12 hours before the testing and
not to perform any kind of physical exercise on the
test day.[20] Each subject walked on the treadmill for
seven minutes using a predetermined overground PWS
to measure the energy expenditure of walking. The
indirect calorimetry method was used to determine
the energy expenditure measurements of the walking
trials on the treadmill (CareFusion Corporation, San
Diego, California, USA). Gas samples were collected
breath-by-breath through a face mask (Hans-Rudolph,
Shawnee, Kansas, USA) during oxygen consumption
measurements of walking. The last two minutes of
oxygen data for each trial were taken as the steady state
and averaged at 10-second intervals for analysis.[21]
The Borg scale is a 15-grade scale for rating perceived exertion that ranges from 6 (no exertion) to 20 (maximal exertion). It was applied at every two minutes of each walking trial in both groups.[14] The claudication pain scale was assigned to determine the participants’ perception of claudication pain. It was determined via a five-point scale (0: no pain, 1: onset of pain, 2: moderate pain, 3: intense pain, 4: maximal pain).[15]
The initial claudication distances and maximal walking distances that the patients could walk just before stopping because of pain were recorded, and the walking trials were stopped if the subjects were able to walk more than one kilometer.
Statistical analyses
All statistical analyses were carried out using the
SPSS version 11.5 for Windows (SPSS Inc., Chicago,
Illinois, USA). All measurements were expressed as
mean and standard deviation (SD). Group differences
in all variables were assessed by the Mann-Whitney
U-test. Spearman’s correlation was used to test the
statistical significance of any possible correlation, and
the significance level was set at p<0.05.
Table 1: Demographic and anthropometric data of the groups
The mean PWS was 77.76±11.41 m/min and 67.20±10.54 m/min for groups 1 and 2, respectively. (Figure 1), and the difference between the PWS in the groups was statistically significant (p<0.05). The mean oxygen cost of the walking trial was 0.14±0.02 mL/kg/m for the healthy subjects and 0.18±0.04 mL/kg/m for the PAD-IC group (Figure 2). There was also a significant difference in the mean oxygen cost of the walking trail between the patients with IC and the control group (p<0.05). The mean Borg score for the walking trial in group 1 and group 2 was 9.12±1.32 and 12.64±1.02, respectively, and the difference was significant (p<0.05).
In the treadmill walking trials, the mean initial claudication distance was 204.6±179.74 meters, and the mean maximal walking distance was 668.67±417.19 meters in the PAD patient. In group 2, the self-reported initial claudication distance was 266.67±171.39 meters. According to this distance, 66.6% of the patients were in Fontaine stage IIa while the results of the recorded initial claudication distance while walking on the treadmill revealed that 33.3% of the patients were in Fontaine stage IIa.
The IC questionnaire score in group 1 was 3.61±2.02 and 15.94±11.09 in patients with IC, and there was a statistical difference between the groups (p<0.05). The mean claudication pain scale score was 1.82±1.20 in patients with IC. There was no correlation between the IC questionnaire score and the oxygen cost, PWS, claudication pain scale score, Borg score, or initialmaximal claudication distance in the PAD-IC patients (p>0.05). The oxygen cost of walking had significant correlation with the maximal walking distance (r=-0.75; p<0.05), but there was no correlation between the oxygen cost of walking and the IC questionnaire score, PWS, claudication pain scale score, Borg score, or initial claudication distance in group 2 (p>0.05). The Borg score had a significant correlation with the claudication pain scale score (r=0.94; p<0.001) while the initial claudication distance had significant correlations with the Borg score (r=-0.93; p<0.001) and claudication pain scale score (r=-0.90; p<0.001).
The PWS in patients with PAD-IC
The quality of life in patients with IC is diminished
because of ambulatory limitations.[7-22] In our study, the
patients with IC preferred lower speeds than the healthy
control group. Since the PWS is a gait parameter that
can be used for assessing the overall gait performance,[10]
we suggest that the PAD may have affected the gait
performance of our patients with IC. Scherer et al.[23]
postulated that there was no difference in the PWS
between IC patients and their healthy control group.
Myers et al.[7] pointed out that the PWS of IC patients was
higher than their control subjects. It is difficult to explain the higher PWS in claudicant patients while postulating
ambulatory limitations. In accordance with our results,
Crowther et al.[3] and Gardner et al.[24] reported a lower
PWS than their healthy subjects. The PWS was not
reported as a predictor of quality of life in patients with
claudication in Myers et al.’s study.[7] To summarize,
it can be assumed that the PWS is a good predictor
of gait performance. As declared before, altered gait
performance may affect the patients’ quality of life.[22]
The oxygen cost of walking
The oxygen cost of walking is an another gait parameter
that revealed gait efficiency. The age and BMI of
the subject have an effect on the oxygen cost of
walking;[11] therefore, we tried to match these parameters
between the groups in our study. The oxygen cost of
walking in healthy subjects is 0.15 mL/kg/m in people
between 20 and 59 years of age,[11] and it may lead to
discrimination between the normal and pathological
gait.[11,12] We preferred to use the PWS instead of a fixed
walking speed in our study. As previously explained,
the oxygen cost is lowest at the PWS and increases with
a lower or higher PWS (U-shape).[25] The lower PWS in
the IC group led to a higher oxygen cost in the present
study that could be considered as a decreased metabolic
efficiency of walking. Crowther et al.[3] postulated that
the kinematics of walking for IC patients is different than
for healthy subjects. This may lead to higher oxygen cost
in IC patients. The PWS and the oxygen cost of walking
can help to differentiate between normal healthy subjects
and PAD-IC patients. Thus, these two variables can be
used for assessing the outcomes of the different treatment
policies associated with PAD-IC patients.
The maximal walking distance of the PAD-IC
patients
There was a negative correlation between the oxygen
cost of walking and the maximal walking distance in
our study. This result implies that when the patients
walk more efficiently (lower oxygen cost), the maximal
walking distance will be longer. The severity of
the PAD can be assessed by using the Fontaine or
Rutherford classifications, and the maximal walking
distance is an important parameter that can be used in
both types of classification.[9] The maximal walking
distance and oxygen cost relationship may serve as
important variables in determining the severity of
the PAD. Determining the maximal walking distance
at the PWS in daily living environments is rather
difficult; hence, it can only be obtained easily by using
the treadmill in the laboratory. The determination of
maximal walking distance on the treadmill walking
trial is the gold standard method for patients with
PAD-IC.[9,27]
The Borg score
The Borg score was used to determine the perceived
exertion while walking on the treadmill in both
groups. A high Borg score showed that the intensity
of the walking trial at the PWS was higher for the
patients than for the healthy controls. We found
that there was a positive correlation between the
Borg score and the claudication pain scale score.
This correlation demonstrated that the pain that
occurred while walking on the treadmill affected the
perceived exertion in PAD-IC patients. In accordance
with our results, it was pointed out that exerciseinduced
ischemic pain decreases the peak exercise
performance during treadmill exercise testing.[26]
Additionally, the higher oxygen cost of the walking
and the higher perceived exertion can serve as the
main reasons for lesser mobilization in PAD-IC
patients. The initial claudication distance can be
easily recorded in the treadmill testing. In our study,
this distance had a negative correlation with both the
Borg score and the claudication pain scale scores.
When the initial claudication distance was shorter,
the scores of both scales were higher. This result
implies that both scores were influenced by the initial
claudication distances.
The IC questionnaire of the patients with PAD-IC
The score of the IC questionnaire was not correlated
with any of the variables in our study. According to the
self-reported initial claudication distance, 66.6% of the
patients were able to walk more than 200 meters. The
initial claudication distance recorded while walking
on the treadmill proved that 33.3% of the patients were
able to walk farther than that. This discrepancy can be
attributed to the perception of a higher quality of life,
which may lead to lower IC questionnaire scores in
those with PAD-IC. This data clearly established that
qualitative parameters, for instance self-reported initial
distance, should be validated by quantitative methods,
such as the determination of the initial claudication
distance on the treadmill walking test.
A limitation of our study was the low number of participants. This was primarily due to the exclusion of IC patients with diabetes since PAD-IC is highly comorbid with diabetes mellitus (DM) and other cardiovascular diseases.[17]
In conclusion, the metabolic efficiency of walking and PWS are decreased in PAD-IC patients. Our results suggest that the oxygen cost of walking, PWS, Borg score, scores on the claudication pain scale, initial claudication distance, and maximal walking distance are objective parameters that can be used to monitor the ambulatory limitations of patients with PAD-IC.
Declaration of conflicting interests
The authors declared no conflicts of interest with respect
to the authorship and/or publication of this article.
Funding
The authors received no financial support for the
research and/or authorship of this article.
1) Hiatt WR, Hirsch AT, Regensteiner JG, Brass EP. Clinical
trials for claudication. Assessment of exercise performance,
functional status, and clinical end points. Vascular Clinical
Trialists. Circulation 1995;92:614-21.
2) Robless P, Mikhailidis DP, Stansby GP. Cilostazol for
peripheral arterial disease. Cochrane Database Syst Rev
2008;CD003748.
3) Crowther RG, Spinks WL, Leicht AS, Quigley F, Golledge
J. Relationship between temporal-spatial gait parameters,
gait kinematics, walking performance, exercise capacity, and
physical activity level in peripheral arterial disease. J Vasc
Surg 2007;45:1172-8.
4) Selvin E, Erlinger TP. Prevalence of and risk factors for
peripheral arterial disease in the United States: results from
the National Health and Nutrition Examination Survey, 1999-
2000. Circulation 2004;110:738-43.
5) Dormandy J, Heeck L, Vig S. The natural history of
claudication: risk to life and limb. Semin Vasc Surg
1999;12:123-37.
6) Köksal C, Konukoğlu D, Ercan M, Arslan C, Kazımoğlu
K, Bozkurt K. Periferik arter hastalarında lipid
peroksidasyonu ve antioksidan kapasite. Turk Gogus Kalp
Dama 1999;7:244-6.
7) Myers SA, Johanning JM, Stergiou N, Lynch TG, Longo
GM, Pipinos II. Claudication distances and the Walking
Impairment Questionnaire best describe the ambulatory
limitations in patients with symptomatic peripheral arterial
disease. J Vasc Surg 2008;47:550-5.
8) Hiatt WR. Medical treatment of peripheral arterial disease
and claudication. N Engl J Med 2001;344:1608-21.
9) Le Faucheur A, Abraham P, Jaquinandi V, Bouyé P, Saumet
JL, Noury-Desvaux B. Measurement of walking distance
and speed in patients with peripheral arterial disease: a
novel method using a global positioning system. Circulation
2008;117:897-904.
10) Teixeira-Salmela LF, Nadeau S, Milot MH, Gravel D, Requião
LF. Effects of cadence on energy generation and absorption
at lower extremity joints during gait. Clin Biomech (Bristol,
Avon) 2008;23:769-78.
11) Waters RL, Mulroy S. The energy expenditure of normal and
pathologic gait. Gait Posture 1999;9:207-31.
12) Tervo RC, Azuma S, Stout J, Novacheck T. Correlation
between physical functioning and gait measures in children with cerebral palsy. Dev Med Child Neurol 2002;44:185-90.
13) Chong PF, Garratt AM, Golledge J, Greenhalgh RM, Davies
AH. The intermittent claudication questionnaire: a patientassessed
condition-specific health outcome measure. J Vasc
Surg 2002;36:764-71.
14) Borg GA. Psychophysical bases of perceived exertion. Med
Sci Sports Exerc 1982;14:377-81.
15) Crowther RG, Spinks WL, Leicht AS, Sangla K, Quigley
F, Golledge J. Effects of a long-term exercise program
on lower limb mobility, physiological responses, walking
performance, and physical activity levels in patients with
peripheral arterial disease. J Vasc Surg 2008;47:303-9.
16) Pate RR, O’Neill JR, Lobelo F. The evolving definition of
“sedentary”. Exerc Sport Sci Rev 2008;36:173-8.
17) Price JF, Stewart MC, Douglas AF, Murray GD, Fowkes
GF. Frequency of a low ankle brachial index in the general
population by age, sex and deprivation: cross-sectional
survey of 28,980 men and women. Eur J Cardiovasc Prev
Rehabil 2008;15:370-5.
18) Ketenci B, Tuygun AK, Gorur A, Bicer M, Ozay B, Gunay
R, et al. An approach to cultural adaptation and validation:
the Intermittent Claudication Questionnaire. Vasc Med
2009;14:117-22.
19) Van de Putte M, Hagemeister N, St-Onge N, Parent G, de
Guise JA. Habituation to treadmill walking. Biomed Mater
Eng 2006;16:43-52.
20) Schwartz MH. Protocol changes can improve the reliability
of net oxygen cost data. Gait Posture 2007;26:494-500.
21) Dal U, Erdogan T, Resitoglu B, Beydagi H. Determination of
preferred walking speed on treadmill may lead to high oxygen
cost on treadmill walking. Gait Posture 2010;31:366-9.
22) Myers SA, Pipinos II, Johanning JM, Stergiou N. Gait
variability of patients with intermittent claudication is similar
before and after the onset of claudication pain. Clin Biomech
(Bristol, Avon) 2011;26:729-34.
23) Scherer SA, Hiatt WR, Regensteiner JG. Lack of relationship
between gait parameters and physical function in peripheral
arterial disease. J Vasc Surg 2006;44:782-8.
24) Gardner AW, Forrester L, Smith GV. Altered gait profile
in subjects with peripheral arterial disease. Vasc Med
2001;6:31-4.
25) Martin PE, Rothstein DE, Larish DD. Effects of age
and physical activity status on the speed-aerobic demand
relationship of walking. J Appl Physiol 1992;73:200-6.