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Войти в исследования PM & R : the journal of injury, function, and rehabilitation · 2026
Creating adjusted scores targeting mobility empowerment (CASTLE 2): Using response probabilities to expand interpretation of prosthetic limb users survey of mobility (PLUS-M) scores for individuals with lower limb amputation.
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Fylstra Bretta L, Hafner Brian J, Saenz Sophia, Wurdeman Shane R
Аннотация
BACKGROUND: Prosthetists and other rehabilitation specialists often need to identify which aspects of mobility should be prioritized in order to make meaningful changes in a patient's health outcomes. By comparing a patient's responses on the Prosthetic Limb Users Survey of Mobility (PLUS-M) to predicted responses, clinicians can identify areas for improvement and provide more targeted rehabilitation.
OBJECTIVE: To generate PLUS-M T-score maps based on patient presentation (ie, etiology and amputation level) to provide guidance on the next steps in a patient's rehabilitation care.
DESIGN: A frequency response method was used to generate PLUS-M T-score maps. The maps predicted the most probable response to each item on the PLUS-M based on the T-score. The maps were then tested using a separate test dataset. Accuracy was evaluated by comparing differences and Spearman correlation coefficients between predicted and actual scores.
SETTING: Clinical orthotics and prosthetics care.
PARTICIPANTS: Maps were generated based on a training dataset from a large sample (N = 28,719) of patients with lower limb amputation. A separate test dataset (N = 26,535) was used to test the model. Individuals were included in the training and test datasets if they were adults with unilateral above-knee or below-knee amputation.
INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURE(S): PLUS-M 12-item short form (v1.2).
RESULTS: PLUS-M T-score maps were generated for two amputation levels (above and below knee) and two etiologies (dysvascular and nondysvascular), in addition to one for all patients. PLUS-M T-score maps predicted patient scores with high accuracy (difference scores >91.5% and Spearman correlation coefficients >0.801).
CONCLUSIONS: Clinicians can use the developed PLUS-M T-score maps to better understand patients' mobility. This insight can help clinicians improve care by identifying key rehabilitation goals for their patients.
OBJECTIVE: To generate PLUS-M T-score maps based on patient presentation (ie, etiology and amputation level) to provide guidance on the next steps in a patient's rehabilitation care.
DESIGN: A frequency response method was used to generate PLUS-M T-score maps. The maps predicted the most probable response to each item on the PLUS-M based on the T-score. The maps were then tested using a separate test dataset. Accuracy was evaluated by comparing differences and Spearman correlation coefficients between predicted and actual scores.
SETTING: Clinical orthotics and prosthetics care.
PARTICIPANTS: Maps were generated based on a training dataset from a large sample (N = 28,719) of patients with lower limb amputation. A separate test dataset (N = 26,535) was used to test the model. Individuals were included in the training and test datasets if they were adults with unilateral above-knee or below-knee amputation.
INTERVENTIONS: Not applicable.
MAIN OUTCOME MEASURE(S): PLUS-M 12-item short form (v1.2).
RESULTS: PLUS-M T-score maps were generated for two amputation levels (above and below knee) and two etiologies (dysvascular and nondysvascular), in addition to one for all patients. PLUS-M T-score maps predicted patient scores with high accuracy (difference scores >91.5% and Spearman correlation coefficients >0.801).
CONCLUSIONS: Clinicians can use the developed PLUS-M T-score maps to better understand patients' mobility. This insight can help clinicians improve care by identifying key rehabilitation goals for their patients.