Contributing factors to postural stability in Prader-Willi syndrome
Bibliographic record
Abstract
Prader-Willi Syndrome (PWS) is a rare neurodevelopmental disorder affecting multiple functional parameters. This study examined postural stability and associated gait and neuromuscular factors in young adults with PWS. Participants included 10 adults with PWS [7 M/3F; Body Fat % 40.61 ± 7.79]; ten normal weight (NW) adults [7 M/3F; Body Fat % 23.42 ± 7.0]; ten obese (OB) adults [7 M/3F; Body Fat % 42.40 ± 5.62]. Participants completed the Sensory Organization Test (SOT)®. Condition (C) specific and a composite equilibrium score (CES) were calculated (maximum = 100). Quadriceps strength was assessed using an isokinetic dynamometer. Three-dimensional gait analyses were completed along a 10 m walkway using a motion capture system and two force plates. A gait stability ratio (GSR) was computed from gait speed and step length (steps/m). The PWS group had lower scores for C1, C3, C4 and CES compared to the NW (p < .039 for all) and lower scores for C4 and CES than the OB (p < .019 for both) groups, respectively. In C5 (eyes closed, sway-referenced support) and C6 (sway-referenced vision and support), 33.3% of participants with PWS fell during the first trial in both conditions (X2 [2] 7.436, p = .024) and (X2 [2] 7.436, p = .024) but no participant in the other groups fell. Those with PWS showed higher GSR than participants with NW (p = .005) and those with obesity (p = .045). Individuals with PWS had more difficulty maintaining standing balance when relying on information from the somatosensory (C3), visual-vestibular (C4) and vestibular systems (C5, C6). A more stable walk was related to shorter steps, slower velocity and reduced peak quadriceps torque. Participation in multisensory activities that require appropriate prioritization of sensory system(s) input for controlling balance in altered sensory environments should be routinely included. In addition, exercises targeting muscular force and power should be included as part of exercise programming in PWS.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".