The Emerging Gait Dysfunction Phenotype in Idiopathic Parkinson’s Disease
Bibliographic record
Abstract
ABSTRACT Objective Severity of motor symptoms in Parkinson’s disease (PD), and rate of change of these symptoms, suggests the existence of disease subgroups. One important PD subgroup is defined by postural instability and gait dysfunction (PIGD), which is associated with disability, lower quality of life, and cognitive deterioration. In this study, we evaluate what clinical factors at baseline are associated with early development of postural instability in PD. Methods Data was downloaded from the Parkinson’s Progressive Markers Initiative (PPMI). Several clinical features predict development of postural instability. We provisionally term the associated phenotype the emerging gait disorder (eGD) phenotype. We evaluate validity of the phenotype in two held-out populations. Results Individuals with the proposed eGD phenotype have a significantly higher risk of developing postural instability in both validation sets (p < 0.00001 in both sets). The proposed eGD phenotype occurred before development of postural instability (HY stage ≥ 3) in 289 of 301 paired comparisons (Fischer Exact Test, p < 0.000001), with a median progression time from development of eGD phenotype to postural instability of 972 days. Individuals with the proposed eGD phenotype at baseline had more rapid cognitive decline as measured by the Montreal Cognitive Assessment (p = 0.002) and Hopkins Verbal Learning Test (Total Recall, p = 0.008). Interpretation We describe a clinical phenotype, detectable at baseline in a subset of individuals with PD, that is associated with accelerated development of postural instability. Within the sample, development of the eGD phenotype reliably precedes development of disability, and is a harbinger of more rapid cognitive progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".