Using novel porous metal pillars for tibial bone defects in primary total knee arthroplasty
Bibliographic record
Abstract
BACKGROUND: The optimal method to treat tibial bone defects during primary total knee arthroplasty (TKA) is still unclear. A novel technique of porous metal pillar augmentation has been applied recently. This study aimed to assess the short-term outcomes of primary TKA with the use of novel porous metal pillars for tibial bone defects. METHODS: A total of 24 cases (22 patients) of primary TKA between January 2019 and December 2020 using porous metal pillars for tibial bone defects were reviewed. Clinical results were evaluated using the Knee Society knee score (KSKS) and function score (KSFS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and range of motion (ROM). Hip-knee-ankle angle (HKAA), femorotibial angle (FTA), and radiolucent lines were assessed radiologically. RESULTS: The median follow-up period was 36.0 months (interquartile range: 31-37 months). The KSKS, KSFS, WOMAC score, and ROM improved significantly at the final follow-up assessment compared with the preoperative evaluation. Both of the HKAA and FTA were corrected after surgery. Only one knee had a nonprogressive radiolucent line at the bone-cement interface. No radiolucent lines were detected around the pillar in any of the cases. There were no cases of prosthesis loosening and revision. CONCLUSIONS: The use of novel porous metal pillars yielded satisfactory clinical outcomes and reliable radiological evidence of fixation in this study with a minimum 2-year follow-up. Porous metal pillar augmentation can be considered as a valuable and easy-to-use method for the management of tibial bone defects in primary TKA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".