Comparing the effects of <i>GBA</i> variants and onset age on clinical features and progression in Parkinson's disease
Bibliographic record
Abstract
OBJECTIVE: Glucosylceramidase (GBA) variants and onset age significantly affect clinical phenotype and progression in Parkinson's disease (PD). The current study compared clinical characteristics at baseline and cognitive and motor progression over time among patients having GBA-related PD (GBA-PD), early-onset idiopathic PD (early-iPD), and late-onset idiopathic PD (late-iPD). METHODS: We recruited 88 GBA-PD, 167 early-iPD, and 488 late-iPD patients in this study. A subset of 50 GBA-PD, 81 early-iPD, and 223 late-iPD patients was followed up at least once, with a 3.0-year mean follow-up time. Linear mixed-effects models helped evaluate the rate of change in the Unified Parkinson's Disease Rating Scale motor and Montreal Cognitive Assessment scores. RESULTS: At baseline, the GBA-PD group showed more severe motor deficits and non-motor symptoms (NMSs) than the early-iPD group and more NMSs than the late-iPD group. Moreover, the GBA-PD group had more significant cognitive and motor progression, particularly bradykinesia and axial impairment, than the early-iPD and late-iPD groups at follow-up. However, the early-onset GBA-PD (early-GBA-PD) group was similar to the late-onset GBA-PD (late-GBA-PD) group in baseline clinical features and cognitive and motor progression. CONCLUSION: GBA-PD patients exhibited faster cognitive and motor deterioration than early-iPD and late-iPD patients. Thus, subtype classification based on genetic characteristics rather than age at onset could enhance the prediction of PD disease 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".