Are re-injured ligaments equivalent mechanically to injured ligaments: The role of re-injury severity?
Bibliographic record
Abstract
The consequences of ligament re-injury have received limited attention. Although the mechanical properties of injured ligaments improve over time, these properties are never fully recaptured, rendering these injured ligaments susceptible to re-injury. Previous injury is a significant risk factor for recurrent injury, and this re-injury can result in longer absence from activity than the initial injury. A rabbit medial collateral ligament model was used to compare mechanically re-injured right medial collateral ligaments to injured left medial collateral ligaments. Two groups of different re-injury severity were investigated: 'minor' re-injury comparing transection re-injured right medial collateral ligaments to transection injured left medial collateral ligaments; 'major' re-injury comparing gap re-injured right medial collateral ligaments to transection injured left medial collateral ligaments. Initial injuries for both groups were right medial collateral ligament transections 1 week before re-injury. After 5-6 weeks of healing, mechanical testing was performed to determine (dimensionally) cross-sectional area; (structurally) medial collateral ligament laxity, failure load, and stiffness; and (materially) cyclic creep strain and failure stress. Because we wanted to evaluate whether the mechanical properties of re-injured ligaments were equivalent or, at least, no worse than injured ligaments, we used equivalence/noninferiority testing. This approach evaluates a research hypothesis of equivalence, rather than difference, and determines whether comparisons are 'statistically equivalent', 'noninferior', or 'potentially inferior'. Transection re-injured and gap re-injured ligaments were 'statistically equivalent' structurally to transection injured ligaments. Transection re-injured ligaments were 'noninferior' both materially and dimensionally to transection injured ligaments. Gap re-injured ligaments were 'potentially inferior' both materially and dimensionally to transection injured ligaments. Two differences between the re-injuries, which affect healing, may explain the mechanical outcomes: the presence or lack of healing products and the proximity of ligament ends at the time of re-injury. Our findings suggest that (in the short term) there is a severity of re-injury below which there is no additional disadvantage to the healing process, mechanical behaviour, and resulting potential for re-injury.
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".