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. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: J Vasc Surg. 2021 May 31;74(6):1987–1995. doi: 10.1016/j.jvs.2021.04.069

Claudicating Patients with Peripheral Artery Disease have Meaningful Improvement in Walking Speed after Supervised Exercise Therapy

Hafizur Rahman 1,2, Iraklis I Pipinos 2,3, Jason M Johanning 2,3, George Casale 3, Mark A Williams 4, Jonathan R Thompson 3, Yohanis O’Neill-Castro 3, Sara A Myers 1,2
PMCID: PMC8612940  NIHMSID: NIHMS1709961  PMID: 34082001

Abstract

Objective:

Supervised exercise therapy (SET) is a first-line treatment for patients with peripheral artery disease (PAD). The efficacy of SET is most commonly expressed by significant statistical improvement of parameters that do not clarify how each individual patient will benefit from SET. This study examined the minimal clinically important difference (MCID) in walking speed in claudicating patients with PAD after SET.

Methods:

A total of 63 patients with PAD-related claudication (Fontaine stage II PAD) participated in a six-month SET program. Self-selected walking speed was measured before and after SET. Distribution and anchor-based approaches were used to estimate the MCID for small and substantial improvement. The “ability to walk one block” and the “ability to climb one flight of stairs” questions were chosen as anchor questions from the Medical Outcomes Study 36-item Short Form questionnaire (SF-36). Receiver operating characteristics curve analyses were performed to detect the threshold for MCID in walking speed after treatment.

Results:

The distribution-based method estimated 0.03 m/s as a small improvement and 0.08 m/s as a substantial improvement after SET. Small and substantial improvements according to the anchor question “walking one block” were 0.05 m/s and 0.15 m/s, respectively. For the “climbing one flight of stairs” anchor question, 0.10 m/s was a small improvement. Receiver operating characteristics curve analyses identified an increase of 0.04 m/s and 0.03m/s for improvement based on walking one block and climbing one flight of stairs, respectively.

Conclusions:

We report our findings for the MCID for walking speed among claudicating patients receiving SET. Claudicating patients who increase walking speed ≥ 0.03 m/s are more likely to experience a meaningful improvement in walking impairment than those who do not. The MCID reported in this study can serve as a benchmark for clinicians to develop goals and interpret clinically meaningful progress in the care of claudicating patients with PAD.

Keywords: Minimal clinically important difference, walking speed, peripheral artery disease, supervised exercise therapy.

Table of Contents Summary

This study suggests that an increase in walking speed ranging from 0.03 m/s to 0.15 m/s represents a clinically relevant and significant improvement in claudicating patients who complete six months of supervised exercise therapy.

INTRODUCTION

Supervised exercise therapy (SET) is a first-line treatment for patients with peripheral artery disease (PAD)-related claudication, leading to a significant improvement in the distance patients can walk and in quality of life1–6. SET outcomes are usually expressed as statistical comparisons of parameters in quality of life questionnaires, walking distances, and gait biomechanics obtained pre- and post-treatment. However, these comparisons often fail to convey the relevance of the degree of change to patients.

The minimal clinically important difference (MCID) represents the smallest change in an outcome measurement that is significant and relevant to patients7–9. The MCID seeks to express the criteria for clinically relevant improvement, deterioration, or lack of change due to a disease or intervention rather than just state the presence or absence of a statistically significant difference. The concept of MCID was first introduced by Jaeschke et al. to identify the change in quality of life that would result in a clinically relevant change in individuals with asthma7. Since then, the MCID concept has been used for several clinical populations and interventions including those with neurological, cardiovascular, pulmonary, musculoskeletal and degenerative diseases10.

Studies that measured MCID for patient reported outcomes, claudication distances, and walking parameters in patients with PAD are limited8. Previous studies found an increase of 0.87 points in the Vascular Quality of Life and 0.11 points in the Walking Impairment Questionnaire indicative of a significant improvement after revascularization in patients with intermittent claudication and critical limb ischemia11–14. Gardner et al. reported MCIDs of 38 seconds, 95 seconds, and 152 seconds respectively for small, moderate, and large improvements in peak walking time following completion of a SET program8. There are limitations of using quality of life questionnaires to assess physical function,15 while measurements of walking distance with a treadmill are technically demanding, limited to vascular laboratories and are not practical to complete in a clinical setting16. Walking speed is a relatively quick and easy test that requires minimal equipment (stopwatch and known distance) and can be measured in nearly every environment. For these reasons, walking speed is a more generalizable test for which there are established threshold values for daily activities such as the ability to cross the street, successful community ambulation, ability to carry groceries, ability to do household activities etc10. Hence, expressing the MCID in terms of walking speed can be a helpful tool which can be used to assess whether a treatment improves the ability to perform activities of daily living while allowing comparisons across clinical populations and treatments9,17–22.

This study estimated the MCID in walking speed in patients with PAD after SET. The MCID values were measured by using both distribution and anchor-based methods. Receiver operating characteristics curves were also constructed to identify the increase in walking speed that signifies any improvement after SET.

METHODS

Participants and SET Protocol

The study was approved by the Institutional Review Boards at the Nebraska-Western Iowa Veteran Affairs Medical Center and University of Nebraska Medical Center. A total of 63 patients (age: 64.95 ± 6.60 years, body mass index: 29.24 ± 5.70 kg/m2) diagnosed with Fontaine stage II PAD were recruited through the vascular surgery clinics of these institutions. Patients’ had not previously participated in any SET program or any revascularization treatments prior to enroll for this study. Patients’ consent was obtained before study participation. Patients were free from any gait altering musculoskeletal or neurological conditions that limited or altered walking. Patients’ history and physical examination were evaluated by one of two board-certified vascular surgeons. The demographics and clinical characteristics of patients were reported in Table I.

Table I:

Patients demographics and clinical characteristics.

Characteristics Values
Number of patients 63
Male (%) 100
Age (years) 64.95 (6.60)
Body mass index (kg/m2) 29.24 (5.70)
Ankle brachial index 0.50 (0.17)
Level of disease (%)
 Aortoiliac 20.93
 Femoropopliteal 30.23
 Multilevel 48.84
Smoking (%)
 Current 61.82
 Former 34.55
 Never 3.63
Coronary artery disease (%) 33.93
Diabetes (%) 28.57
Dyslipidemia (%) 63.64
Hypertension (%) 71.70
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Continuous variables are presented as mean (standard deviation). Categorical variables are presented as percentages of the patients under each category/sub-category.

Each patient participated in a six-month, three times per week (total 72 sessions) SET program that followed the American College of Sports Medicine recommendations in line with previous studies that best increase walking distances23,24. The detailed SET protocol utilized in this study was previously described1.

Experimental Procedures and Data Collection

Self-selected walking speed was assessed as part of a larger gait biomechanics assessment at the Biomechanics Research Building at the University of Nebraska at Omaha. Each patient was evaluated twice: 1) before (baseline) and after six-month (post-exercise) participation in SET. A reflective marker was placed at the heel of the leg most affected with PAD based on ABI and claudication symptoms. Patients walked across a 10-meter pathway for at least three trials and the coordinates of the marker were recorded using a 12 high speed infrared camera system (60 Hz, Motion Analysis Corporation, Rohnert Park, CA). A minimum mandatory rest of one-minute was taken between each trial to prevent the onset of claudication pain. Walking speed was calculated as the average distance traveled per second measured based on the reflective marker and averaged across three trials25,26.

MCID Calculation

MCID in walking speed was calculated using both distribution and anchor-based methods. The distribution-based method uses standard deviation of the walking speed to assess the meaningful difference. Thus, this method is influenced by the group variation in walking speed at baseline. In contrast, the anchor-based method is considered a more robust approach to estimate MCID9. The anchor-based method correlates the quantitative change in walking speed after disease/intervention to measured change in function, for example, self-selected mobility response from individuals on questionnaires17. This method provides a more standard clinical assessment as it uses the individual’s perceived change as the reference for the change in the desired outcome variables27.

Distribution-based method

The standard deviation of the baseline walking speed was used to measure the meaningful differences according to the distribution method. A small improvement was computed as 0.2 x σ, and a substantial improvement was computed as 0.5 x σ, whereas σ is the standard deviation of the group mean baseline walking speed17,27.

Anchor-based method

Patient reported outcomes were measured using the Medical Outcomes Study 36-item Short Form questionnaire (SF-36). Previous studies considered two mobility items from the SF-36 as anchor questions to calculate MCID for walking speed: 1) ability to walk one block and 2) ability to climb one flight of stairs17,27. Self-reported difficulty during walking a short distance or walking upstairs is often used as a definition of mobility disability and walking speed is an important predictor of this outcome17. Therefore, this study used these two questions as the anchor questions to calculate MCID.

Participants rated their ability as limited a lot, limited a little, and not limited at all while answering the two anchor questions. Participants were then categorized into groups based on their responses to the anchor questions at baseline and post-exercise (substantial improvement, small improvement, no change, small decline, and substantial decline). Substantial improvement was defined as change from limited a lot to not limited at all. Small improvement was defined as change from limited a lot to limited a little, or from limited a little to not limited at all. Some participants also reported no change, or declined performance (changed from not limited at all to limited a little, from limited a little to limited a lot, and from not limited at all to limited a lot). Those participants were excluded from anchor-based analysis as we wanted to focus only on improvements in walking speed after SET.

Two approaches were employed for the anchor-based method. First, we used descriptive statistics to calculate MCID for walking speed. Small MCID was estimated as the mean change in walking speed between post-exercise and baseline of the patients who were in the small improvement group according to the anchor question (as defined above). Similarly, substantial MCID was calculated as the mean change in walking speed between post-exercise and baseline of the patients who reported substantial improvement according to the anchor question. This was followed separately for each anchor question.

Secondly, a receiver operating characteristics (ROC) curve was used to estimate the threshold walking speed to predict improvement after SET. For ROC analysis, response to the anchor question was expressed as two dichotomous outcomes variables: any improvement (including small and substantial) versus no change. The participants who reported their conditions as declining (small and substantial) were excluded from ROC analysis as our aim was to determine the threshold walking speed for any improvement as compared no improvement. The sensitivity represents the proportion of the patients who were correctly classified as showing improvement after exercise therapy. Sensitivity was plotted along the y-axis in the ROC graph. The x-axis of the ROC graph was expressed as 1-specificity, representing the proportion of the patients who were incorrectly classified as showing improvement. A cut-point in the ROC curve (i.e. the threshold walking speed), was chosen from the minimal value of the equation (1-sensitivity)2 + (1-specificity)2 17,28. The positive predictive value was calculated using data from patients who met the threshold walk speed (i.e. were predicted to respond), by dividing the number who actually responded by the total number of patients who were predicted to respond. In contrast, the negative predictive value was calculated using data from patients who did not meet the threshold walk speed (i.e. were predicted to be non-responders), by dividing the number who were actual non-responders by the total number of patients who were predicted to be non-responders. Positive likelihood ratio was estimated by dividing sensitivity by 1-specificity. All analyses were performed using SAS software version 9.4 (SAS Institute Inc., Cary, NC).

RESULTS

Distribution-based MCID

The average walking speed of all patients at baseline was 1.11 ± 0.15 m/s. Walking speed increased to an average of 1.16 ± 0.16 m/s after six-months of SET (4.5% improvement, p < 0.001). Based on the standard deviation of walking speed at baseline (0.15), the distribution-based method estimated a change of 0.03 m/s for small improvement and 0.08 m/s for substantial improvement after SET.

Anchor-based MCID

Fifteen patients (23.8%) were substantially limited in walking one block and this decreased to only six patients (9.5%) after SET (Table II). In contrast, the number of patients who were able to walk one block without any limitation increased from seventeen (27.0%) to thirty-one (49.2%) after six-months of SET. A similar pattern was observed for the question regarding climbing one flight of stairs. Initially, nineteen patients (30.1%) were able to climb one flight of stairs without any limitation at baseline. After six-months of SET, nineteen patients (46%) answered that they could climb one flight of stairs without any limitation (Table II).

Table II:

Results of two anchor questions from the SF-36 Health survey before and after six-months of supervised exercise therapy. Values presented as number of patients (% of patients/response).

Conditions Walking one block Climbing one flight of stairs
Baseline Post-exercise Baseline Post-exercise
Yes, Limited A Lot 15 (23.8) 6 (9.5) 9 (14.3) 7 (11.1)
Yes, Limited A Little 31 (49.2) 26 (41.3) 35 (55.6) 27 (42.9)
Not Limited At All 17 (27.0) 31 (49.2) 19 (30.1) 29 (46.0)
Total 63 (100) 63 (100) 63 (100) 63 (100)
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Only eight patients (12.7%) reported declines in walking one block and climbing one flight of stairs after six-months of SET (Table III). Twenty-seven (42.9%) and thirty-five (55.6%) patients reported no changes in walking one block and climbing one flight of stairs, respectively, after SET. A total of twenty-four patients (38.1%) had a small improvement and four patients (6.3%) had a substantial improvement in walking one block. In contrast, for climbing one flight of stairs, eighteen patients (28.5%) showed a small improvement and only two patients (3.2%) had a substantial improvement after SET (Table III).

Table III:

Change in patient reported outcomes after six-months of supervised exercise therapy according to the SF-36 Health Survey anchor questions. Substantial decline/improvement was defined as change from not limited at all to limited a lot and vice versa. Small decline/improvement was defined as a change from limited a little to limited a lot, or from not limited at all to limited a little and vice versa. Values are presented as the number of patients reporting (% of patients/group).

Substantial Decline Small Decline No Change Small Improvement Substantial Improvement Total
Walking one block 1 (1.6) 7 (11.1) 27 (42.9) 24 (38.1) 4 (6.3) 63 (100)
Climbing one flight of stairs 2 (3.2) 6 (9.5) 35 (55.6) 18 (28.5) 2 (3.2) 63 (100)
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The patients who reported no change in walking one block had an average 0.03 m/s increase in walking speed (Table IV). The patients who had a small improvement after SET showed an increase of 0.05 m/s in walking speed. A larger improvement in walking speed, 0.15 m/s, was observed for patients having substantial improvement in walking one block. Surprisingly, the average walking speed increased by 0.04 m/s for the small decline group. The only patient who reported substantial decline in walking one block had also increased walking speed (0.14 m/s). For the anchor question regarding climbing one flight of stairs, an improvement of 0.03 m/s was detected for patients who had no change after SET. Walking speed increased by an average of 0.10 m/s in patients reporting a small improvement. Surprisingly, the walking speed decreased by 0.02 m/s for patients who reported substantial improvement, although there were only two patients in this group (Table IV). However, the 6 patients who reported a small declined according to the climbing one flight of stairs anchor-question, decreased their average walking speed by 0.01 m/s following SET. The average walking speed increased by 0.09 m/s for those 2 patients who had substantial declined according to the climbing one flight of stairs question.

Table IV:

Anchor-based minimal clinically important difference in walking one block and climbing one flight of stairs after six-months of supervised exercise therapy. Values are presented as mean (95% confidence interval).

No Change Small Improvement Substantial Improvement
Walking one block 0.03 (−0.01~0.06) 0.05 (0.01~0.10) 0.15 (−0.05~0.34)
Climbing one flight of stairs 0.03 (−0.002~0.06) 0.10 (0.05~0.15) −0.02 (−1.85~1.82)
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The ROC Curve Analysis

The threshold change in walking speed that maximized the sensitivity and specificity in the ROC curve for patients who reported improvement in walking one block after SET was 0.04 m/s (Figure 1). The corresponding sensitivity and specificity were 57.1% and 44.4% respectively. The positive predictive value was 0.52 and the negative predictive value was 0.50 with a positive likelihood ratio of 1.03. The area under the ROC curve was 0.58. In contrast, the threshold walking speed to signify improvement in climbing one flight of stairs was identified as 0.03 m/s with 80.0% sensitivity and 48.6% specificity (Figure 2). This yields a positive likelihood ratio of 1.56. The positive and negative predictive values were 0.47 and 0.81 respectively. The area under the curve was found to be 0.65.

Figure 1:

Figure 1:

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Receiver operating characteristic (ROC) curve to predict change (small or substantial versus no change) in the ability to walk one block after six-months of supervised exercise therapy in patients with peripheral artery disease. Threshold change in walking speed was 0.04 m/s (sensitivity = 57.1%, specificity = 44.4%, positive likelihood ratio = 1.03, and area under the ROC curve = 0.58). The proportion of patients with any improvement in walking one block among those among those who met the threshold walking speed was 0.52, and the proportion of patients who did not improve among those who did not meet the threshold walking speed was 0.50.

Figure 2:

Figure 2:

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Receiver operating characteristic (ROC) curve to predict change (small or substantial versus no change) in the ability to climb one flight of stairs after six-months of supervised exercise therapy in patients with peripheral artery disease. The threshold change in walking speed was 0.03 m/s (sensitivity = 80%, specificity = 48.6%, positive likelihood ratio = 1.56, and area under the ROC curve = 0.65). The proportion of patients with any improvement in climbing one flight of stairs among those who met the threshold walking speed was 0.47 and the proportion of patients who did not improve among those who did not meet the threshold walking speed was 0.81.

DISCUSSION

The purpose of this study was to estimate the MCID in walking speed after SET in patients with PAD. Both distribution and anchor-based methods were used, including ROC curve analysis to estimate the walking speed that is relevant and predicts meaningful improvement of individual patients. The distribution-based method results suggest that an increase in walking speed of 0.03 m/s after SET predicts a small improvement and an increase of 0.08 m/s predicts a substantial improvement. The anchor-based method estimates resulted in higher increases of walking speed needed to demonstrate similar improvements. Increases in walking speed for small and substantial improvements were 0.05 m/s and 0.15 m/s respectively according to the walking one block anchor-question. Similarly, for the anchor-question climbing one flight of stairs, an estimate of 0.10 m/s was indicative of a small improvement. We were not able to dependably calculate the walking speed that predicts a substantial improvement according to the climbing one flight of stairs question (−0.02 m/s) because we had only two such patients. A relatively large decline in one patient and a smaller increase in the other caused the overall change in walking speed to be negative (−0.02 m/s) for substantial improvement. We excluded the patients from the analysis who did not improve or showed deterioration based on the two anchor-questions. Our primary objective was to estimate the MCID for walking speed improvement following the SET using previously described method17. While looking at two patients for those walking speed increased although they had a substantial declined according to the climbing one flight of stairs question, we found that one of the patients was the same who also reported substantial decline according to walking one block. This patient reported himself as substantial declined for both anchor-questions (changed from not limited at all to limited a lot) while his walking speed actually increased by 0.14 m/s after six-month of SET program. This shows the challenges involved in using the anchor-based method when correlating the quantitative measurement with self-reported questionnaires with mobility limitations17. Previous study also suggests that using the self-reports to validate performance measure such as walking speed is useful, but the limitations of self-reported questionnaires continue to be of central importance17. Future work with a greater number of patients who reported small and substantial decline and substantial improvement with different set of anchor questions may provide further insight.

Previous works have reported the MCID values for walking speed in different clinical populations for several interventions. Walking speed changes ranged from 0.10 m/s to 0.17 m/s for small and 0.17 m/s to 0.26 m/s for substantial improvements following surgical repair of hip fracture17. The MCID in patients with chronic obstructive pulmonary disease ranged from 0.08 m/s to 0.11 m/s after 8 weeks of pulmonary rehabilitation21. The clinically meaningful important difference in walking speed among persons with Parkinson disease while on anti-Parkinsonian medication ranged from 0.05 m/s to 0.22 m/s by distribution-based method and ranged from 0.02 m/s to 0.18 m/s when estimated by the anchor-based method22. Therefore, our estimated MCID values for walking speed in patients with PAD following SET are comparable with those demonstrated in other clinical populations and in a variety of clinical settings and interventions.

ROC curve analyses in the present study suggest that the walking speed improvements that predict meaningful improvement after SET were 0.04 m/s and 0.03 m/s for walking one block and climbing one flight of stairs respectively. The area under the ROC curves ranges from 0.58 – 0.65 showing a marginal discrimination29. A review article summarizing the MCID estimated by ROC analyses from seven different studies has reported that area under the curve ranged from 0.53 to 0.9130. Only 3 of 7 reported studies reported area under the curve values exceeding 0.7030. Although measurement of walking speed is simple and provides useful information regarding patient health status, based on the ROC results, walking speed has marginal ability to distinguish patient improvement following an intervention. It may be interesting to analyze the ROC curves by exploring additional or multiple anchor questions to see how the area under the curve values for ROC curves are impacted. If the participants do not improve walking speed after intervention, MCID values for quality of life may be considered as an alternate to predict the efficacy of intervention. However, quality of life questionnaires only considers the participant’s own perception whereas walking speed provides a quantitative outcome and an objective measurement of the intervention.

The average walking speed of the patients with claudication in this study was 1.11 m/s which is less than the normal walking speed observed in age-matched healthy adults (1.32 m/s – 1.36 m/s)26,31. While looking at other clinical populations, the walking speed in patients with hip fracture after successful fixation and repair ranged from 0.36 m/s to 0.66 m/s17,18. The walking speed in stroke patients ranged from 0.18 m/s to 0.56 m/s9,20. The average walking speed in patients with chronic obstructive pulmonary disease, Parkinson disease, multiple sclerosis, and very mild Alzheimer disease (clinical dementia rating of 0.5 or 1) were 0.90 m/s, 0.98 m/s, 1.3 m/s, and 1.21 m/s respectively21,22,32,33. The average walking speed in patients with incomplete spinal cord injury (both traumatic and non-traumatic) varies from 1.25 m/s to 1.39 m/s based on the time when walking speed was measured after injury34. Thus, on average, claudicating patients with PAD have higher walking speed than patients with hip fracture, stroke, chronic obstructive pulmonary disease, and Parkinson disease, but lower walking speed than patients with multiple sclerosis, mild Alzheimer and incomplete spinal cord injury.

Previous studies from our group and others have reported significant improvement in quality of life and walking distances in patients with PAD after SET1–6. Our findings also show that walking speed significantly improved an overall average of 4.5% from baseline. We found that the walking speed significantly improved by 0.05 m/s in patients with PAD following a six-month SET program. To put this in the context of improvements in speed after intervention in different clinical settings, the walking speed improved by 0.08 m/s in patients with chronic obstructive pulmonary disease after 8 weeks of pulmonary rehabilitation21 and by 0.18 m/s after total hip arthroplasty19 while patients with repaired hip fracture had also improved walking speed by 0.16 m/s following an exercise program with average duration of 10 months17. Our results suggest that an overall increase of 0.03 to 0.10 m/s is seen in patients enjoying a small improvement and 0.08 to 0.15 m/s for substantial improvement after SET. This level of improvement would correspond to a one-mile walking time that is between 101 to 189 seconds faster.

Previous studies have measured the minimally important differences in patients with PAD with critical limb ischemia and intermittent claudication following different treatment methods. Most of these measurements were limited to patient reported outcomes, claudication time, and claudication distances. The minimally important differences in Vascular Quality of Life questionnaire after revascularization treatment in patients with critical limb ischemia are 0.48 and 0.36 points based on the distribution and anchor-based methods, respectively11. Conjin et al. reported an increase of 0.87 in the Vascular Quality of Life and 0.11 in the Walking Impairment Questionnaire in patients with intermittent claudication as indicative of a significant and meaningful improvement after treatment (optimal medical therapy, revascularization, or supervised exercise therapy)12. Another study suggested an improvement range of 1.7 to 2.2 points in Vascular Quality of Life questionnaire as the minimum important difference in patients with intermittent claudication one year after revascularization14. A study by Van Den Houten et al. also reported the functional and absolute claudication distances that signify improvement as 250 m and 305 m, respectively, following three months of supervised exercise therapy35. Gardner et al. estimated MCID values of 38 seconds, 95 seconds, and 152 seconds for small, moderate, and large improvements respectively in peak walking time8. Furthermore, the six-minute walk distance for small, moderate, and large MCID were 9 m, 24 m, and 38 m respectively8. Our current study adds the MCID values of walking speed that signify small and substantial improvements after SET to the existing literature.

The measurement of walking speed is simple, inexpensive, and can be easily implemented in a clinical setting. Although we used a reflective marker placed in heel to calculate the walking speed; however, several wearable technologies and inertial measurement units are being used to measure walking speed36. A smart phone app called 6th Vital Sign has been developed that can directly measure the walking speed from a 2-minute walk test37. The smartphone-based assessment of gait parameters such as step length, step time, walking speed are reliable and valid38. Therefore, several wearable technologies are available to measure the walking speed accurately in a clinical setting36. Walking speed is an outcome of the complex interplay of several body structures and their functions including proactive and reactive postural control, lower extremity muscle strength, aerobic capacity, motor control, visual effects etc10. Walking speed can be a significant indicator of functional recovery or deterioration and has been emerging as a “sixth vital sign” in health care10. Walking speed is a more generalizable test and is used to establish threshold values for several daily activities such as the ability to cross the street, successful community ambulation, the ability to carry groceries, and the ability to do household activities10. Establishing improvement ranges based on walking speed could also lay the groundwork for using walking speed from wearable devices to monitor PAD progression and treatment progress in real-world environments. On the basis of this progressively increasing literature, walking speed is now considered a global indicator of overall health and functional status especially in older populations with or without chronic diseases and is being commonly used as a key reference to estimate the efficacy of a treatment18.

While comparing the outcomes before and after any type of treatment statistically, sample size and patient to patient individual performance variability can prevent meaningful differences from reaching statistical significance22. Alternatively, very large sample sizes that include small differences following a treatment can lead to statistically significant differences that have little practical meaning or impact on patients’ quality of life39. In both situations, the efficacy of an intervention is more meaningfully interpreted by comparing the outcomes with established parameters of clinically important and significant improvements22,27 such as the MCID for walking speed.

There are limitations to this study. First, the majority of our participants were white males with claudication and the MCID estimation for walking speed may need to be evaluated for different demographics. Second, the number of patients we evaluated, in combination with the anchor questions we selected, produced a small number of patients in the substantial improvement groups. We also excluded the patients from the anchor-based analyses who did not improve or showed declined performance based on the two anchor-questions. Increasing the number of patients evaluated and selecting additional anchor questions may further improve the process of estimating the MCID for treatment of patients with PAD-related claudication.

CONCLUSION

In summary, we measured the MCID values of change in walking speed that indicate small and substantial improvements in claudicating patients with PAD after SET. Our data indicate that the clinically important difference in walking speed among claudicating patients ranged from 0.03 m/s to 0.08 m/s by distribution-based analysis and ranged from 0.03 m/s to 0.15 m/s per level based on anchor-based metrics. The MCID reported in this study can serve as a benchmark for clinicians to develop goals and interpret clinically meaningful progress in the care of claudicating patients with PAD.

ARTICLE HIGHLIGHTS.

Type of Research:

Single-center retrospective longitudinal study.

Key Findings:

An increase in walking speed ranging from 0.03 m/s to 0.15 m/s indicates a clinically relevant and significant improvement in claudicating patients with peripheral artery disease after supervised exercise therapy.

Take home Message:

The minimal clinically important difference in walking speed reported in this study can serve as a benchmark for clinicians to develop goals and interpret clinically meaningful progress in the care of patients with peripheral artery disease-related claudication.

ACKNOWLEDGEMENT

This work was supported by grants from the National Institute of Health (R01AG034995, R01HD090333, R01AG049868), United States Department of Veterans Affairs Rehabilitation Research and Development Service (I01RX000604, I01RX003266), and the National Aeronautics and Space Administration (NASA) Nebraska Space Grant. We thank Mahdi Hassan for his assistance in data collection and Cody Anderson for his assistance in calculating the walking speed.

Footnotes

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