Effect of Obersity on Gait Symmetry Following Anterior Cruciate Ligament Transection
Bibliographic record
Abstract
Introduction: Obesity is considered a risk factor for both the onset and progression of osteoarthritis (OA). Obesity, OA and mechanical perturbation have all been identified individually to increase gait asymmetry. The purpose of this study was to assess the effect of obesity on the progression of gait asymmetry as a component of a diet induced obesity (DIO) OA model in the presence of mechanical perturbation . Methods: 28 Sprague Dawley Rats were assigned to a high fat, high sucrose diet or a low fat diet group (LFD). Twelve weeks post DIO groups receive an anterior cruciate ligament transection (ACL-X), or sham surgery. Pre-surgery, 1-week, 8-week, and 16-weeks post-surgery, kinetic data were collected by 3-D force plate analysis. Peak vertical ground reaction force (pVGRF), vertical impulse, and stance times were quantified then compared between limbs to quantify an asymmetry index (AI). Results: There were no differences in normalized pVGRF AI between hind limbs in the DIO or LFD group animals. Stance times decreased for both hind limbs in both DIO group animals. DIO ACL-X group animals had a greater AI compared to LFD group animals at 1-week post-surgery, and both DIO group animals had greater AI at 8 and 16 weeks post-surgery, compared to LFD group animals. Conclusion : DIO group animals exhibited gait patterns with increased asymmetries compared to LFD group animals, regardless of presence or absence of mechanical perturbation, suggesting that obesity causes distinct changes in gait patterns accelerating the onset and progression of knee osteoarthritis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".