Gait initiation impairment in patients with Parkinson’s disease and freezing of gait
Bibliographic record
Abstract
Abstract Objective Freezing of gait (FOG) is a sudden episodic inability to produce effective stepping despite the intention to walk. It typically occurs during gait initiation or modulation and may lead to falls and loss of independence. We assessed gait initiation (GI) changes in parkinsonian patients suffering from FOG when off dopaminergic medications, removing correlations with anthropometric measurements, the base of support, and initial stance posture. We also addressed the temporal pattern of segmental body movements subserving gait initiation. Methods We studied 23 subjects with Parkinson’s disease (PD) and FOG (PDF), 20 patients with PD and no previous history of FOG (PDNF), and 20 healthy controls (HC). Kinematic and dynamic analysis of anticipatory postural adjustments (imbalance, unloading, stepping phase) was performed while patients were starting gait from upright standing after a self-selected period, to avoid any effect of cueing on gait initiation. Results The center of pressure (CoP) displacement and velocity during imbalance showed a significant impairment in both PDNF and PDF, more prominent in the latter patients. Several measurements were specifically impaired in PDF patients, especially the CoP displacement along the anteroposterior axis during unloading. The pattern of segmental center of mass (SCoM) movements during gait initiation did not show any differences between groups, but had high inter-subject variability. The standing postural profile preceding GI did not correlate with outcome measurements. Conclusions Our results showed impaired motor programming at gait initiation in parkinsonian patients. The more prominent deterioration of unloading in PDF patients might suggest impaired processing and integration of somatosensory information subserving gait initiation. The unaltered temporal movement sequencing of SCoM in both PDNF and PDF might indicate some compensatory cerebellar mechanisms triggering time-locked models of body mechanics in PD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".