Non motor symptoms in progressive supranuclear palsy: prevalence and severity
Bibliographic record
Abstract
Abstract NMSs have been extensively studied in PD patients but not in other forms of parkinsonism such as Progressive Supranuclear Palsy (PSP). The primary objective of this study was to analyze the frequency, severity and the type of non-motor symptoms (NMS) in PSP patients using the non-motor symptoms scale (NMSS). The secondary objective was to differentiate NMS between PSP and Parkinson’s disease (PD). We enrolled in this cross-sectional study 50 consecutive PSP and 100 matched Parkinson’s disease (PD) patients, in the proportion PSP/PD = 1/2, matched in age, sex, and disease duration. Motor and Non Motor symptoms (different scales for each disease) were evaluated at baseline using PSP scale, SCOPA Motor, Montreal Cognitive Assessment (MOCA), HADS, Hamilton, and Non Motor Symptom scale (NMSS). Comparative analysis was done using chi-squared test, Mann-Whitney test and Fisher’s exact test. Fifty PSP (56% female) and 100 PD (59% female) patients completed the study protocol and were included for statistical analysis. The NMSS total domains score in the PSP group was 77.58 ± 42.95 (range 14–163) with NMS burden grade: 4, very severe, and the in the PD group was 41.97 ± 35.45 (range: 0–215) with NMS burden grade: 3, severe. The comparative analysis showed that NMS total score ( p < 0.0001), Sleep/Fatigue ( p = 0.0007), Mood/Apathy ( p = 0.0001), Gastrointestinal ( p < 0.0001), and Urinary dysfunction ( p = 0.0001) domains were significantly more severe in PSP patients than in PD. This observational study reports that NMSs are very frequent in PSP patients hence the higher burden of NMS in PSP specifically related to mood/apathy, attention/memory, gastrointestinal, urinary disturbances compared to PD.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".