Lower-limb prostheses are prescribed based on each patient's individual needs.1 However, identifying a patient's needs and prescribing the proper prosthesis is not straightforward.2 Presently, the Medicare Functional Classification Level, or K-level, system is used to classify individuals and make prosthetic recommendation based on their potential functional ability.3 Currently, K-level classifications and recommendations for lower-limb prosthetic prescriptions are typically made using clinical evaluations. However, it is not clear how results from clinical evaluations reflect real-world walking performance.4 Moreover, the K-level classification system is subject to substantial controversy as a result of many factors including the “ambiguity in applying the K-level guidelines to classify patients… [and] a lack of scientific evidence.”5 All of these factors may result in improper prosthetic prescription, which could limit an individual's mobility, activity, and participation.
The clinical evaluations used to make prosthetic recommendations may be composed of patient self-reported measures (questionnaires) and/or in-clinic performance-based evaluations. Self-report measures are subjective by nature,2 whereas performance-based evaluations provide more objective data. One performance-based evaluation, the 6-minute walk test (6MWT), measures walking function and evaluates walking endurance.6–9 The 6MWT has been correlated to K-levels10 as well as real-world step counts among individuals with lower-limb amputations.11 Another performance-based evaluation is the 10-m walk test (10MWT), which is used to determine walking speed and has been shown to be valid and reliable in prosthetic users with lower-limb amputations.12,13 Walking speed is an important clinical measure as it is considered the sixth vital sign when assessing the status of any patient.14 To our knowledge, the relationships between the 10MWT and K-level classifications or real-world walking performance have not been reported.
Real-world walking performance of individuals with a lower-limb prosthesis provides knowledge of an individual's actual functional ability and needs, although these data are more difficult to obtain than measures that can be conducted in a clinic. One important real-world walking performance parameter is step count,15 which is quantified over a period such as a day or week. Step count provides an indication of activity level,11 which has implications on an individual's health and quality of life.16 In addition to step count, the amount of time spent in different intensity levels of walking activity is an important measure of functionally relevant walking performance17 as this measure provides information about the “structure of daily walking activity.”18 Activity intensity can be categorized into low, moderate, or high activity based on the number of steps taken each minute.
Real-world walking performance can be quantified using accelerometer-based activity monitors.2,19,20 Step count accuracy of these activity monitors has been demonstrated for healthy adults,21,22 individuals post-stroke and post-traumatic brain injury,23 and individuals with lower-limb amputations.20,24–26 Studies have related step counts over a 7-day observation period to K-levels27 and 6MWT results.11,27 Another study related step activity to other clinical performance-based measures and found correlations between the real-world and in-clinic measures.19 However, this study did not determine how these data differed by K-levels or did it evaluate the 6MWT or 10MWT. Aside from these studies, previous literature only reports select real-world walking performance data, such as step count28,29 or intensity,2 and does not report these data in conjunction with in-clinic performance-based measures for different K-levels.
Using measures of real-world walking performance in conjunction with clinical measures and clinician's expertise may be an ideal way to ensure that patients receive the optimal prosthetic treatment.4 Understanding the relationship among in-clinic performance-based measures, real-world walking performance, and K-level is an important first step toward the goal of ultimately improving the consistency and efficacy of prosthetic recommendations. K2 and K3 prosthetic components are the most commonly prescribed devices, and differentiating between these two functional levels often proves to be difficult. Therefore, the purpose of this study was to investigate outcomes of in-clinic performance-based evaluations (6MWT and 10MWT) and real-world walking performance measures (step count, amount of activity, and activity intensity) for individuals with unilateral lower-limb amputation classified as K2 and K3.
This study was approved by the University of Delaware Institutional Review Board and included two components—a clinical assessment and a 7-day observation of real-world walking performance. Thirty-one individuals participated in this study. Participants were between the ages of 21 and 85 years, and all had a unilateral transfemoral or transtibial amputation. Due to loss of data from 4 participants (see Data Analysis section for details), data from 27 participants were analyzed in this study. These participants included 16 individuals (sex: 11 male, 5 female; amputation level: 10 transtibial, 6 transfemoral) classified as K3 and 11 individuals (sex: 10 male, 1 female; amputation level: 10 transtibial, 1 transfemoral) classified as K2. K-level classifications were determined by each subject's health care provider who prescribed the prosthesis before their participation in this study. Average demographic data for each K-level group are provided in Table 1.
First, during the clinical assessment visit, participants' height and weight were recorded. Next, participants performed the 10MWT and 6MWT. For the 10MWT, participants walked along a 10-m walkway with time recorded during the middle 6 m to allow for acceleration and deceleration. The participants performed three trials at their self-selected speed, and results were averaged. For the 6MWT, participants walked at their comfortable walking speed around a loop for 6 continuous minutes while distance walked was measured by an investigator via a measuring wheel. During the 6MWT, participants were allowed rest breaks whenever needed, but the time of the rest breaks counted toward the 6 minutes.
After the clinical assessment, participants were equipped with a Fitbit® One™ activity monitor, which has been shown to accurately count steps for individuals with unilateral lower-limb amputations.26 The activity monitor was secured near the ankle of the prosthesis using the strap included with the FitBit®. For the 7-day observation period, which began the day after the clinical assessment, participants were instructed to perform their regular daily activities. Participants were told to wear the activity monitor at all times that they were wearing their prosthesis. Participants were provided with a prepaid and addressed postage box and instructed to mail the activity monitor back at the conclusion of the observation period.
Upon return of the activity monitor, minute-by-minute step count data were extracted from the device via FitaBase, a cloud-based, fee-for-service data aggregation platform.30 Data were reviewed for irregularities, such as single days with no steps, which may have indicated failure of the activity monitor. If the irregularities could not be explained via discussions with the participants, these data were considered invalid and that participant was excluded from this study's analysis. However, some irregularities were explained, including a participant stating that he/she regularly did not wear the prosthesis on a particular day of the week, which justified a day with no steps recorded.
For each participant with a valid set of data, self-selected walking speed was calculated from the 10MWT, and total distance walked during the 6MWT was determined. From the 7-day observation period, the total number of steps taken, total number of active minutes, and number of minutes spent in low (1–30 steps/min), moderate (>30–60 steps/min), and high (>60 steps/min)19 intensity activity were calculated. To account for differences in the total number of active minutes during the observation period across participants, the percentage of time spent at each intensity level was evaluated by dividing the number of minutes spent in low-, moderate-, and high-intensity activity by the participant's total number of active minutes and multiplying that value by 100.
Participant assigned K-level and the parameters of interest (self-selected walking speed, distance walked during 6 minutes, total number of steps, total number of active minutes, and percentage of time spent in low-, moderate-, and high-intensity activity during the observation period) were analyzed. For each variable, means and standard deviations were calculated for the K2 and K3 groups. In addition, a Welch's t-test with a confidence interval of 0.95 was used to evaluate differences in means between the K2 and K3 groups.
Data from a total of 27 participants were analyzed in this study. Two participants were eliminated from analysis due to invalid days during the 7-day observation period, and two additional participants were excluded because the activity monitor was lost during the observation period.
Demographic data of the participants in this study are shown in Table 1. While there were no differences in height and weight among the K2 and K3 individuals, the individuals classified as K2 were significantly older than those classified as K3. Individuals classified as K2 had, on average, a significantly slower self-selected walking speed, significantly shorter distance walked in 6 minutes, significantly lower total step count over the 7-day observation period, and significantly fewer active minutes over the observation period when compared with those classified as K3 (Table 1, Figure 1). While there were no significant differences seen in the percentage of time spent in low-, moderate-, and high-intensity activity between the two groups, trends (data with a pattern that is not statistically significant) in low- and high-intensity activity were seen. Individuals classified as K2 trended toward spending a higher percentage of time in low-intensity activity and a lower percentage of time in high-intensity activity when compared with the individuals classified as K3.
Although most participants' data aligned with assigned classifications, a few participants' data showed discrepancies (Figure 1, Table 2). Participants D and E were classified as K3, but all of their data (10MWT walking speed, 6MWT distance, total steps, total active minutes, and percentage of time spent in low- and high-intensity activity) reflected K2 level function as these data were near or below the K2 group average. In addition, there was one participant (participant C) classified as a K3 whose data were less definitive. While participant C's 10MWT walking speed, 6MWT distance, total steps, and total active minutes over the 7-day observation period indicated K2 level function, this participant's time spent in high-intensity activity was in line with K3 level function. Furthermore, while two individuals classified as K2 (participants A and B) had in-clinic measures that clearly reflected K2 level function, both individuals had total step counts as well as percentage of time spent in low- and high-intensity activity that reflected K3 level function.
This study investigated the in-clinic and real-world walking performance of individuals with unilateral lower-limb amputations classified as K2 and K3. Results from this study showed differences in all parameters between the K2 and K3 groups. Most participants' data aligned with their assigned classification levels; however, based on these data, a few participants from both the K2 and K3 levels seemed to be misclassified. This understanding of in-clinic performance-based measures and real-world walking performance for K2 and K3 levels is a step toward developing a standardized method for objectively prescribing prostheses.
Demographically, the K2 participants in this study were, on average, significantly older than the K3 participants, which is likely a good representation of the K2 versus K3 populations. Being older, these K2 individuals might not have had vocational or daily living requirements that require high levels or intensities of activity. However, according to the Clinical Template, the individual's “vocational, therapeutic, exercise, or athletic activities” are to be considered when assigning K-levels.31 Therefore, the difference in age between the 2 groups is likely an accurate and meaningful difference for this study.
This study investigated a series of in-clinic and real-world walking performance measures that are important parameters when considering functional abilities. Furthermore, these measures evaluate constructs highlighted in the Clinical Template via objective data.31 To our knowledge, the 6MWT and step counts are the only measure evaluated in this study that have been previously related to K-levels. In the current study, average K2 and K3 distances walked during the 6MWT were longer than those reported by previous studies; however, results from our study fell within the previously reported ranges for individuals classified as K2 and K3.10,27 The total step count values for individuals classified as K2 and K3 could not be directly compared with those reported in the literature as the only study to relate step counts to K-level reported the number of steps taken outside the house, not the total number of steps taken in a week.27 However, in general, the total number of steps recorded in our study fell within the ranges of step counts reported in the literature for this population.19,28,29
While step count provides information about an individual's activity level, the total number of active minutes and percentage of time spent at different activity intensities provides insightful information about the structure of the activity. Results from this study showed that there are differences in the total number of active minutes between groups, with individuals classified as K3 being active for more time than those classified as K2. Furthermore, trends in the percentage of time spent in low- and high-intensity activity were noted between the groups. With more subjects evaluated, these trends may become statistically significant. A study by Albert and colleagues2 reported activity intensity data for individuals with lower-limb amputation and found a relationship between an individual's K-level and the amount of low- or high-intensity activity. The trends noted in our study agree with the results from Albert and colleagues in that individuals classified as K2 had less high-intensity activity than those classified as K3. However, the study by Albert et al based activity intensity on accelerations instead of number of steps per minute.
Average results from this study showed differences between individuals classified as K2 and K3 for most parameters assessed. These differences were in line with K-level descriptions. Furthermore, these data supported the assigned K-levels for most participants. However, four participants, two classified as K2 and two classified as K3, seemed to be misclassified as most of their data were in line with the other group's averages (Figure 1). Interestingly, participants A and B in-clinic measures reflected K2 level function, but their real-world walking performance indicated K3 level function. Future research is needed to determine why there was a discrepancy between the in-clinic and real-world walking performance measures for these subjects.
While most of the assigned K-level were seemingly “accurate” as they were in line with the outcomes of the in-clinic and real-world walking performance measures, there is a substantial push from third-party payers to provide objective data to justify an individual's K-level. Based on results, this study provides several objective measures that may be useful as part of a standardized method for justifying patients' K-level classification and prosthetic recommendation. However, a larger study is needed to identify the best measures for objectively classifying an individual's functional level.
This study had some limitations. Although the 6MWT and 10MWT are common, objective measures of performance that can be evaluated in the clinic, this study did not evaluate the Amputee Mobility Predictor, which is also a widely used performance-based clinical measure.10 Future studies should investigate the relationship between outcomes of the Amputee Mobility Predictor or other key clinical measures and real-world walking performance. Furthermore, the real-world walking performance data were collected over a period of about one and a half years, meaning the data were collected in different seasons. Step counts may vary with the time of year,28 and therefore some of the subjects' step count data may have been influenced by the season during which the data were collected. However, anecdotally, it was more difficult to enroll subjects in the study during the winter months, and therefore only a few of the subjects' data were collected during the winter. Furthermore, no substantial differences in step count data were seen for the subjects that were collected during the winter compared with those that were collected during other seasons.
This study presented data to quantify the real-world walking performance, in conjunction with in-clinic performance-based data, for individuals classified as K2 and K3. Results from this study provide an increased understanding of the functional ability of individuals with unilateral transfemoral and transtibial amputations classified as K2 and K3. This study is a step forward toward developing an objective and standardized method to classify an individual's functional ability and make prosthetic recommendations.
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