Dynamic evaluation of spine kinematics in individuals with Parkinson’s disease and freezing of gait
Bibliographic record
Abstract
BACKGROUND: Freezing of gait (FoG) is an episodic failure of gait exposing people with Parkinson's disease (PD) to a high risk of falling. Despite growing evidence of the interconnection between impaired trunk control and FoG, a detailed description of spinal kinematics during walking is still lacking in this population. RESEARCH QUESTION: Do spinal alterations impact gait performance in individuals with PD and FoG? METHODS: We analyzed kinematic data of 47 PD participants suffering (PD-FOG, N = 24) or not suffering from FoG (PD-NFOG, N = 23) and 15 healthy controls (HCO) during quiet standing and unperturbed walking. We estimated the main spinal variables (i.e., spinal length, lordosis and kyphosis angles, trunk inclination), the pelvis angles, and the shoulder-pelvis angles during gait and standing. We studied differences across conditions and groups and the relationships between postural and gait parameters using linear regression methods. RESULTS: During standing and walking, both PD groups showed increased trunk inclination and decreased lordosis angle with respect to HCO, as well as a decreased range in variation of kyphosis angle, pelvic obliquity, and shoulder-pelvis angles. Only PD-FOG participants showed reduced range of lordosis angle and spinal length compared to HCO. PD-FOG individuals were also not able to straighten their spine during walking compared to standing. Stride length and velocity were decreased in both patient groups compared to HCO, while swing duration was reduced only in the PD-FOG group. In individuals with FoG, trunk inclination and lordosis angle showed moderate but significant positive correlations with all gait alterations. SIGNIFICANCE: Spine alterations impacted gait performance in individuals with PD suffering from FoG. Excessive trunk inclination and poor mastering of the lordosis spinal region may create an unfavourable postural precondition for forward walking. Physical therapy should target combined spinal and stepping alterations in these individuals.
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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 | 0.000 |
| 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".