P.008 Spontaneous retropulsion in autopsy verified PSP
Bibliographic record
Abstract
Background: Postural instability is a common symptom of progressive supranuclear palsy (PSP). Retropulsion is one form of postural instability. Spontaneous retropulsion involves loss of balance without external provocation. Others have reported on retropulsion in the clinical setting while testing for postural instability but rates of spontaneous retropulsion in the community have not been described. This study examines the prevalence of spontaneous retropulsion in PSP. Methods: A retrospective chart review examined 60 patients from the Saskatchewan Movement Disorders Program with clinical and pathology-confirmed diagnosis of PSP. We identified patients who endorsed spontaneous retropulsion. The data was analysed with univariate logistic regression. Results: The study included 43 males and 17 females. Spontaneous retropulsion was reported in 18 (30%) patients. Among the variables, only sex showed a statistical significance (p = 0.0184) with females more likely to report spontaneous retropulsion (OR = 4.25). Other variables (PSP onset age, onset age of balance impairment, gait impairment, and disease duration) were not statistically significant. Conclusions: Our data suggest that spontaneous retropulsion is common in PSP, with females being at a significantly higher risk than males. This is useful information when counselling patients on risk-avoidance behaviour to prevent falls.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.012 | 0.001 |
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".