Early Findings on the Use of Motion Capture during Simulated Sports Activities to Better Understand Hemophilic Arthropathy
Bibliographic record
Abstract
Abstract Many persons with hemophilia (PwH) have joint bleeding despite prophylaxis. We hypothesize that movement biomechanics play a significant and largely unexplored role in joint bleeding, which could be exploited to develop personalized rehabilitation programs. We have designed a clinical study to test this hypothesis. Here we show data from the first 3 enrollees as case studies of what could potentially be learned. Data were collected from 3 participants with hemophilia A, ages 10-30 years, on prophylaxis with emicizumab, with at least 1 joint bleed in the lower extremity in the past year, using motion capture techniques with force plates and reflective markers collected through a Vicon system. Motion lab activities were designed to simulate sports activities and included walking (barefoot and shod), squatting (double and single leg), hopping on one foot, and jumping from a 30-cm box. Two patients (B and C) routinely take additional factor VIII prophylaxis prior to physical activity and did so before coming to the motion lab. Hemophilia Joint Health Score (HJHS) was obtained by an experienced physical therapist prior to motion lab collection to gauge degree of hemophilic arthropathy by physical exam. A subset of participants and activities are shown graphically. Participant A (not shown) had a higher HJHS in the right knee than left (3 vs 0) and had HJHS of 4 in bilateral ankles, with most recent bleed in the right ankle 8 months prior; primary physical activity was walking. This participant showed subtle differences between the right and left in all activities, including less weight on the right leg during double leg squat, and right single leg hop lower than the left. Participant B had a higher HJHS in the right knee than the left (3 vs 0) and in the right ankle than the left (7 vs 6), and he had had multiple episodes of knee pain but no change in HJHS since 2 years prior. Knee MRIs performed outside of the study were consistent with tendinosis of bilateral quadriceps rather than bleeding. Primary sports were basketball, hiking, biking, and skiing. Participant B had subtle differences between the right and left side that seemed to protect the right, including mildly decreased right knee flexion with weight acceptance during walking (more pronounced when wearing shoes), lower power generation by the right ankle than the left in walking, and lower peak ground reaction force (GRF) on the right than left in forward hopping. Some motions seemed to protect the left side more, with less power generation and absorption by the ankle (double and single leg squats) and hip (single leg squat only), right single leg squat somewhat deeper than the left, and slower time to step onto the left foot than the right. Participant C had a higher HJHS in the right knee than left (2 vs 1) and in the right ankle than left (5 vs 3) but had had worsening HJHS in bilateral ankles compared to his previous scores, with bleeds in both knees in the past year. Primary physical activities were baseball (pitching), basketball, biking, skiing, and golf. He had recently been diagnosed with Osgood Schlatter (patellar tendon/tibial tuberosity inflammation) of the left knee, which had been causing pain for several months, but no bleeding in that knee. Movement analysis reflected left knee pain, including very little flexion with weight acceptance when walking; very little power absorption or generation from the knee in walking, hopping, and squatting; shallower squats and lower hops on the left; and lower ground reaction force on the left than the right with walking. Perhaps related to the left knee protection, both ankles were consistently more plantarflexed in walking, and there was increased power generation in the right ankle compared to the left. These findings suggest the presence of subtle asymmetry related to hemophilic arthropathy and previous bleeding, which were more pronounced in more strenuous activities than with walking. The results of participant C could suggest that pain, even if unrelated to hemophilia, could cause compensatory movement mechanisms that could lead to increased bleeding risk in other lower extremity joints. Ongoing analysis will include tracking of bleeding over 1 year following motion analysis, enrollment of additional participants, comparison with controls, and performing detailed statistical analysis to determine which movement parameters correlate best with HJHS and lower extremity bleeding risk. Figure 1 Figure 1. Disclosures Warren: Novo Nordisk: Consultancy; Hema Biologics: Consultancy; Bayer: Research Funding; CSL Behring: Research Funding; Genentech: Research Funding. Funk: Biomarin: Consultancy; Sanofi Genzyme: Speakers Bureau; Toronto Sick Kids Hospital: Patents & Royalties: Hemophilia Joint Health Score Royalties; Partners: Honoraria.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".