Can Self-Reported Measures Help Determine Lower-Limb Amputees’ K-Levels?
Following a lower-limb amputation, clinicians evaluate individuals to determine their ability to utilize a prosthetic limb effectively. The K-levels, used widely in the U.S., are a Medicare rating system that indicates a person's rehabilitation potential. To determine a person's K-level, clinicians employ objective assessment tools, such as the Amputee Mobility Predictor and Distance and Timed Walk Tests, which provide a glimpse into how individuals with limb loss walk and move.
However, new practices are emerging to aid post-amputation rehabilitation. Recently, community walking metrics, like steps per day and cadence, have proved helpful for clinicians to prescribe prosthetic devices and design rehabilitation interventions. And as these metrics become popular among patients and clinicians, researchers sought to determine the variations in data and what amount is considered significant from a clinical perspective.
This study aimed to identify the typical range of walking measurements among people who use lower limb prostheses over six months, as well as establish standard walking data and a method for interpreting significant changes in those community walking metrics.
The researchers assessed the data of 86 lower-limb amputees at least 21 years old and at least six months post-amputation. Each was given a StepWatch 3 Activity Monitor, which was attuned to their walking gait and affixed to their prosthetic limb just above the foot.
The StepWatch is a medical device approved for use by people who have lost a lower limb or have difficulty walking. It can measure several metrics, including daily steps, walking distance, peak performance index, as well as cadence and cadence variability. Additionally, it uses a proprietary algorithm to assess the user's functional level and provide a single number similar to the K-level. Studies have shown that the StepWatch algorithm is highly consistent with clinically determined K-levels in individuals with below-knee amputations.
The participants provided researchers with data using the Global Mobility Change Rating (GMCR) and the StepWatch. However, the researchers discovered that the participants did not accurately report their activity levels, which is a common trend in previous studies involving individuals with colon cancer, low back pain, multiple sclerosis, and post-joint arthroplasty. Because of the findings from this study, the researchers caution clinicians that approximately 50% of their patients may be inaccurate in reporting their activity level.
Because of the findings from this study, the researchers caution clinicians that approximately 50% of their patients may be inaccurate in reporting their activity level.
The researchers pointed out several reasons why the reported mobility changes may not be accurate. One is that participants may have trouble remembering their activities from the previous week. They may also have been confused about which week they experienced changes in mobility, or one positive or negative event may have influenced their overall perception of the week.
Lastly, increased activity may have caused fatigue or residual limb pain, leading to reported reduced GMCR despite actual improvements in walking.
K-level must remain a clinical decision
The authors believe clinicians should still have the last say in determining patients' K-levels. But objective community walking metrics can help them determine what is typical for their patients, and significant changes in walking metrics can prompt further investigation.
For example, a clinician struggling to give a K-level may consult objective community walking metrics to support the decision.
Objective data can still benefit certain patients, mainly if they provide accurate GMCR scores corresponding to changes in walking metrics. For instance, subject 33 in the study experienced a decrease in all metrics due to poor prosthetic socket fit, but the metrics improved after the socket was modified.
When treating patients, it's essential to establish a standard walking pattern and expected variation as a baseline. This helps set realistic goals for improving function after injuries, illnesses, or surgeries. Additionally, a decrease in walking metrics and other information can justify the need for a new prosthetic socket or other changes to insurance providers.