Kinematic and Coordination Variability in Individuals With Acute and Chronic Patellofemoral Pain
Bibliographic record
Abstract
Altered gait variability occurs in those with patellofemoral pain and may be relevant to pain progression. We examined gait kinematic and coordination variability between individuals with acute and chronic patellofemoral pain and healthy controls. Eighty-three patellofemoral pain runners (37 men and 46 women) and 142 healthy controls (52 men and 90 women) ran on a treadmill while 3-dimensional lower limb kinematic data were collected. Patellofemoral pain runners were split into acute (n = 22) and chronic (n = 61) subgroups based on pain duration (< and ≥3 mo, respectively). Approximate entropy assessed continuous hip, knee, and ankle kinematic variability. Vector coding calculated coordination variability for select joint couplings. Variability measures were compared between groups using 1-way analysis of variance and post hoc comparisons with Cohen d effect sizes. The chronic patellofemoral pain subgroup displayed higher frontal plane knee kinematic variability compared with controls (P = .0004, d = 0.550). No statistically significant effects for any coordination variability couplings were identified. Minimal differences in gait variability were detected between those with acute and chronic patellofemoral pain and healthy controls.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".