HR-pQCT measurements of changes in periarticular bone density and microarchitecture one year after acute knee injury and after reconstructive surgery
Bibliographic record
Abstract
ACL injuries commonly lead to post-traumatic osteoarthritis (PTOA), but the underlying mechanism is not well-understood. One theorized mechanism is pathological bone remodelling following an ACL tear, for which high-resolution peripheral quantitative computed tomography (HR-pQCT) is uniquely positioned to investigate in vivo in humans. In this study, we longitudinally investigate the one-year changes in periarticular bone density and microarchitecture in the human knee following an ACL tear and reconstructive surgery using data sampled from an on-going observational cohort study. We reduce the number of individual microarchitectural parameters using factor analysis and model one-year changes with mixed-effects models, adjusting for the effects of age, sex, meniscus status, and the baseline microarchitectural state. We find significant evidence of persistent bone density losses one year after both injury and surgery. We also observe significant increases in trabecular separation post-injury, indicating significant structural degradation, and significant increases in subchondral bone plate density post-surgery, a sign of early stiffening. Finally, we observe minimal significant contrasts for the effects of age, sex, and meniscus status, while we observe that the state of the microarchitecture at baseline has significant and varied effects on the subsequent changes, suggesting that the influence of PTOA risk factors on post-injury and post-surgery bone changes may be mediated through the state of the periarticular microarchitecture at injury and/or at surgery. In summary, we found that degradation of periarticular bone microarchitecture was observed post-injury, densification of the subchondral bone plate was observed post-surgery, and the state of the bone microarchitecture at baseline may mediate the influence of PTOA risk factors on post-injury microarchitectural adaptations. • Bone microarchitecture was measured at injury and surgery and one year later with HR-pQCT. • Microarchitectural changes were analyzed with factor analysis and mixed-effects models. • Density losses and structural degradation occur post-injury. • Trabecular density decreases and subchondral bone plate density increases post-surgery. • Age, sex, and meniscus status were not independently predictive of changes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".