Impact insertion of osteochondral grafts: Interference fit and central graft reduction affect biomechanics and cartilage damage
Bibliographic record
Abstract
An osteochondral graft (OCG) is an effective treatment for articular cartilage and osteochondral defects. Impact of an OCG during insertion into the osteochondral recipient site (OCR) can cause chondrocyte death and matrix damage. The aim of the present study was to analyze the effects of graft-host interference fit and a modified OCG geometry on OCG insertion biomechanics and cartilage damage. The effects of interference fit (radius of OCG - radius of OCR), loose (0.00 mm), moderate (0.05 mm), tight (0.10 mm), and of a tight fit with OCG geometry modification (central region of decreased radius), were analyzed for OCG cylinders and OCR blocks from adult bovine knee joints with an instrumented drop tower apparatus. An increasingly tight (OCG - OCR) interference fit led to increased taps for insertion, peak axial force, graft cartilage axial compression, cumulative and total energy delivery to cartilage, lower time of peak axial force, lesser graft advancement during each tap, higher total crack length in the cartilage surface, and lower chondrocyte viability. The modified OCG, with reduction of diameter in the central area, altered the biomechanical insertion variables and biological consequences to be similar to those of the moderate interference fit scenario. Micro-computed tomography confirmed structural interference between the OCR bone and both the proximal and distal bone segments of the OCGs, with the central regions being slightly separated for the modified OCGs. These results clarify OCG insertion biomechanics and mechanobiology, and introduce a simple modification of OCGs that facilitates insertion with reduced energy while maintaining a structural interference fit. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:377-386, 2018.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".