Inter-laboratory comparison of knee biomechanics and muscle activation patterns during gait in patients with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Gait analysis has been used for decades to quantify knee function in patients with knee osteoarthritis; however, it is unknown whether and to what extent inter-laboratory differences affect the comparison of gait data between studies. Therefore, the aim of this study was to perform an inter-laboratory comparison of knee biomechanics and muscle activation patterns during gait of patients with knee osteoarthritis. METHODS: Knee biomechanics and muscle activation patterns from patients with knee osteoarthritis were analyzed, previously collected at Dalhousie University (DAL: n = 55) and Amsterdam UMC, VU medical center (VUmc: n = 39), using their in-house protocols. Additionally, one healthy male was measured at both locations. Both direct comparisons and after harmonization of components of the protocols were made. Inter-laboratory comparisons were quantified using statistical parametric mapping analysis and discrete gait parameters. RESULTS: The inter-laboratory comparison showed offsets in the sagittal plane angles, moments and frontal plane angles, and phase shifts in the muscle activation patterns. Filter characteristics, initial contact identification and thigh anatomical frame definitions were harmonized between the laboratories. After this first step in protocol harmonization, the offsets in knee angles and sagittal plane moments remained, but the inter-laboratory comparison of the muscle activation patterns improved. CONCLUSIONS: Inter-laboratory differences obstruct valid comparisons of gait datasets from patients with knee osteoarthritis between gait laboratories. A first step in harmonization of gait analysis protocols improved the inter-laboratory comparison. Further protocol harmonization is recommended to enable valid comparisons between labs, data-sharing and multicenter trials to investigate knee function in patients with knee osteoarthritis.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".