Custom Three-Dimensional Printed Scaffolds or Implants in Patients With Segmental Bone Loss of the Foot and Ankle: A Single-Centre Case Series
Bibliographic record
Abstract
BACKGROUND: Custom three-dimensional (3D)-printed implants are a novel surgical treatment for a subset of patients requiring foot and ankle surgery for segmental bone loss. Limited outcome data exist in the literature due to the limited number of cases and short follow-up. The objective of this case series was to evaluate the survival of implants, bony union rates, and measures of pain and quality of life in patients who received custom 3D-printed implants for critical defects of the foot and ankle. Methods: This is a retrospective case series to assess surgical outcomes of patients who underwent implantation of a custom 3D-printed titanium implant between November 2017 and December 2022 in a single foot and ankle unit. The primary outcome was device failure, defined as the removal of the implant. Radiographic analysis was performed to assess for bony integration of implants. Patients completed Short Form 36 (SF-36) and Ankle Osteoarthritis Scale (AOS) questionnaires postoperatively. Results: Ten consecutive patients, five non-weight bearing on average 10 months (range: eight to 13 months) preoperatively and five weight bearing, underwent surgery with custom implants. The average follow-up was 25 months. To date, no patient has required hardware removal or progressed to amputation. Four patients had radiographic bony union confirmed on CT and one on plain film. Two cases are too early to determine, two are total talus implants with no integration surface, and one has a painless fibrous union. The average SF-36 mental component score was 37.80 (range: 8.1-60.64), and the average physical component score was 32.56 (range: 15.5-54.77). CONCLUSION: This case series adds to the growing body of evidence indicating the clinical utility of 3D-printed implants for use in segmental defects of the foot and ankle, demonstrated by the survivorship of implants, promising bony union rates, and functional outcomes. Due to the costs of these implants, larger sample sizes and longer follow-ups are required to support their use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".