Longitudinal changes of early motor and cognitive symptoms in progressive supranuclear palsy: the OxQUIP study
Bibliographic record
Abstract
BACKGROUND: Progressive supranuclear palsy (PSP) is a rare neurodegenerative condition characterised by a range of motor and cognitive symptoms. Very little is known about the longitudinal change in these symptoms over time. Moreover, the effectiveness of clinical scales to detect early changes in PSP is still a matter of debate. OBJECTIVE: 28 healthy control and 28 PSP participants, with average time since onset of symptoms of 1.9 years, were prospectively studied every 3 months for up to 24 months. Changes from baseline scores were calculated at each follow-up time point using multiple clinical scales to identify longitudinal progression of motor and cognitive symptoms. RESULTS: The Montreal Cognitive Assessment, but not the Mini-Mental State Examination, detected cognitive decline at baseline. Both scales revealed poor longitudinal sensitivity to clinical change in global cognitive symptoms. Conversely, the Movement Disorders Society Unified Parkinson's disease Rating Scale - part III and the PSP Rating Scale (PSPRS) reliably detected motor decline less than 2 years after disease onset. The 'Gait/Midline' PSPRS subscore consistently declined over time, with the earliest change being observed 6 months after baseline assessment. CONCLUSION: While better cognitive screening tools are still needed to monitor cognitive decline in PSP, motor decline is consistently captured by clinical rating scales. These results support the inclusion of multiple follow-up time points in longitudinal studies in the early stages of PSP.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".