TY - JOUR
T1 - Predict the Medicare Functional Classification Level (K-level) using the Amputee Mobility Predictor in people with unilateral transfemoral and transtibial amputation
T2 - A pilot study
AU - Dillon, Michael P.
AU - Major, Matthew J.
AU - Kaluf, Brian
AU - Balasanov, Yuri
AU - Fatone, Stefania
PY - 2018/4/1
Y1 - 2018/4/1
N2 - Background: While Amputee Mobility Predictor scores differ between Medicare Functional Classification Levels (K-level), this does not demonstrate that the Amputee Mobility Predictor can accurately predict K-level. Objectives: To determine how accurately K-level could be predicted using the Amputee Mobility Predictor in combination with patient characteristics for persons with transtibial and transfemoral amputation. Study design: Prediction. Method: A cumulative odds ordinal logistic regression was built to determine the effect that the Amputee Mobility Predictor, in combination with patient characteristics, had on the odds of being assigned to a particular K-level in 198 people with transtibial or transfemoral amputation. Results: For people assigned to the K2 or K3 level by their clinician, the Amputee Mobility Predictor predicted the clinician-assigned K-level more than 80% of the time. For people assigned to the K1 or K4 level by their clinician, the prediction of clinician-assigned K-level was less accurate. The odds of being in a higher K-level improved with younger age and transfemoral amputation. Conclusion: Ordinal logistic regression can be used to predict the odds of being assigned to a particular K-level using the Amputee Mobility Predictor and patient characteristics. This pilot study highlighted critical method design issues, such as potential predictor variables and sample size requirements for future prospective research. Clinical relevance: This pilot study demonstrated that the odds of being assigned a particular K-level could be predicted using the Amputee Mobility Predictor score and patient characteristics. While the model seemed sufficiently accurate to predict clinician assignment to the K2 or K3 level, further work is needed in larger and more representative samples, particularly for people with low (K1) and high (K4) levels of mobility, to be confident in the model’s predictive value prior to use in clinical practice.
AB - Background: While Amputee Mobility Predictor scores differ between Medicare Functional Classification Levels (K-level), this does not demonstrate that the Amputee Mobility Predictor can accurately predict K-level. Objectives: To determine how accurately K-level could be predicted using the Amputee Mobility Predictor in combination with patient characteristics for persons with transtibial and transfemoral amputation. Study design: Prediction. Method: A cumulative odds ordinal logistic regression was built to determine the effect that the Amputee Mobility Predictor, in combination with patient characteristics, had on the odds of being assigned to a particular K-level in 198 people with transtibial or transfemoral amputation. Results: For people assigned to the K2 or K3 level by their clinician, the Amputee Mobility Predictor predicted the clinician-assigned K-level more than 80% of the time. For people assigned to the K1 or K4 level by their clinician, the prediction of clinician-assigned K-level was less accurate. The odds of being in a higher K-level improved with younger age and transfemoral amputation. Conclusion: Ordinal logistic regression can be used to predict the odds of being assigned to a particular K-level using the Amputee Mobility Predictor and patient characteristics. This pilot study highlighted critical method design issues, such as potential predictor variables and sample size requirements for future prospective research. Clinical relevance: This pilot study demonstrated that the odds of being assigned a particular K-level could be predicted using the Amputee Mobility Predictor score and patient characteristics. While the model seemed sufficiently accurate to predict clinician assignment to the K2 or K3 level, further work is needed in larger and more representative samples, particularly for people with low (K1) and high (K4) levels of mobility, to be confident in the model’s predictive value prior to use in clinical practice.
KW - Amputation
KW - Amputee Mobility Predictor
KW - K-level
KW - Medicare Functional Classification Level
KW - mobility
UR - http://www.scopus.com/inward/record.url?scp=85041896034&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041896034&partnerID=8YFLogxK
U2 - 10.1177/0309364617706748
DO - 10.1177/0309364617706748
M3 - Article
C2 - 28534664
AN - SCOPUS:85041896034
SN - 0309-3646
VL - 42
SP - 191
EP - 197
JO - Prosthetics and Orthotics International
JF - Prosthetics and Orthotics International
IS - 2
ER -