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Locally Produced AI-Designed Transtibial Prosthetic Sockets in Rural Sierra Leone: A Prospective Cohort Study
Merel van der Stelt1, Lars Brouwers2, Sallieu Jalloh3
13D Lab Radboudumc, Radboud University Medical Center, Nijmegen, The Netherlands; Masanga Medical Research Unit, Masanga Hospital, Masanga, Sierra Leone; Foundation 3D-Printing in Developing Countries, Vught, The Netherlands.
Objective:
To evaluate artificial intelligence (AI)-based transtibial prosthetic socket shapes in a rural, low-income setting.
Design:
This prospective cohort study evaluates AI-designed prosthetic sockets. Baseline and 10-week follow-up assessments were conducted to evaluate satisfaction, functionality, and quality of life.
Setting:
The study was conducted at the 3D laboratory of Masanga Teaching Hospital in rural Sierra Leone.
Participants:
Thirty-four participants with a transtibial amputation without a functional prosthesis were enrolled. At follow-up, 27 participants completed the assessments.
Interventions:
Local coworkers with limited prosthetic experience autonomously produced transtibial sockets using user-friendly software powered by an AI algorithm trained on expert data.
Main Outcome Measures:
Baseline and 10-week follow-up assessments included (1) satisfaction with the device and service using the adapted Orthotics and Prosthetics User's Survey (OPUS); (2) functioning by quantifying prosthetic wear time and step count (before and after receiving the prosthesis) with activity sensors and the lower extremity functional status using the adapted OPUS survey (range, 0-60); (3) disease-specific health-related quality of life (D-HRQoL) using the adapted OPUS survey (range, 0-36) and generic health-related quality of life using the EuroQol 5-Dimension 3-Level (EQ-5D-3L) and the Visual Analog Scale (VAS) score; and (4) participants' personal goals were evaluated.
Results:
The activity sensors confirmed that all participants used the prosthesis. Median prosthetic wear time was 9.3 (1.6-11.4) hours per day, with a median of 3978 (1746-6545) steps per day, of which 39% (16%-76%) were taken with the prosthesis. Median scores indicated a significant improvement in OPUS lower extremity functional status from 45 (39-49) to 52 (47-54) and in OPUS D-HRQoL from 25 (20-30) to 31 (25-35). EQ-5D-3L and the Visual Analog Scale score did not significantly change; 56% achieved their desired activity goal.
Conclusions:
This study shows that easy-to-use software and AI can support socket design in areas with limited access to skilled prosthetists.
