An International, Multicenter Field Trial Comparison Between 3D-Printed and ICRC-Manufactured Transtibial Prosthetic Devices in Low-Income Countries
Bibliographic record
Abstract
ABSTRACT Introduction The gap between the needs of individuals with amputation and access to prosthetists in low-income countries (LICs) is significant. Training new personnel to bridge this gap would exceed the current output of all prosthetic and orthotic programs globally. Strategies are needed to increase the productivity of existing prosthetists in order to serve more patients. Emerging technologies such as 3D scanning, modeling, and printing have been investigated for their ability to decrease the manufacturing time for prosthetic devices; however, few studies have compared the efficacy of 3D-printed devices to traditionally manufactured (e.g., International Committee of the Red Cross [ICRC]) devices. Studies that previously compared these two methods were limited by low population size and restricted timeframes. The purpose of this study was to gather evidence comparing the efficacy of 3D-printed and ICRC transtibial prostheses in large patient populations in LICs over time. Materials and Methods A total of 61participants between the ages of 5 and 25 completed this study's 8-week trial. Participants were recruited from four clinical sites in Uganda, Tanzania, and Cambodia. Ethics approval was obtained from each of the four clinical sites before study initiation. Consent was obtained from each participant before study enrolment. The participants' residual limbs were 3D scanned by local prosthetists using hand-held 3D scanners. Prosthetists digitally rectified the 3D scanned models using Canfit and NiaFit 3D modeling software. The rectified models were fabricated using 3D printers. 3D-printed devices were lined with foam liners and coupled to standard ICRC pylons and feet. Participants used the 3D-printed sockets for 4 weeks, then returned to the clinic to complete a 28-question Likert scale questionnaire, assessing their experiences with their 3D-printed devices. Surveys were based on the Prosthesis Evaluation Questionnaire. Participants were then given a new transtibial prosthetic device manufactured using traditional ICRC methods and instructed to use this device for 4 weeks. They then returned to the clinic to complete the questionnaire as aforementioned. Responses from both surveys were assessed using a two-tailed Student t -test ( P < 0.05). Results Data from the Tanzania Training Centre for Orthopaedic Technologists (n = 10) indicated that their users rated ICRC devices significantly higher in categories measuring stability, including ability to walk, walking up steep slopes and stairs, walking on slippery surfaces, overall fit, comfort while standing, and texture of the device. In contrast, participant data from Comprehensive Rehabilitation Services in Uganda (n = 25), Cambodian School of Prosthetics and Orthotics (n = 10), and Comprehensive Community Based Rehabilitation in Tanzania (n = 16) showed no significant differences across all measured outcomes. Conclusions This is the first study to compare and contrast the efficacy of 3D-printed and ICRC transtibial prosthetic devices across geographic locations in LICs with a large study population. Results demonstrate that, in general, 3D-printed devices were rated comparably to ICRC. This result was consistent at three of four clinical trial sites. Further studies will be required to elucidate the rating differences observed at the fourth site.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".