P.060 Clinical milestones in PSP and MSA as triggers for palliative care intervention
Bibliographic record
Abstract
Background: Progressive Supranuclear Palsy (PSP) and Multiple System Atrophy (MSA) are neurodegenerative disorders with disabling morbidities and premature death. Variable illness trajectories make the timing for initiating neuropalliative care unclear. This scoping review aims to identify milestones relevant to survival and neuropalliative care in PSP and MSA. Methods: A systematic literature search was performed in Medline and EMBASE databases to identify publications investigating predictors of survival in PSP and MSA. Titles and abstracts of 2091 articles were independently screened by two reviewers and 22 research studies published after 2010 were included. Results were qualitatively combined to suggest triggers for targeted palliative care throughout the disease trajectory. Results: ‘Milestones’ are well documented, clinically relevant disease points prompting further care. Important milestones include frequent falls, cognitive impairment, severe dysarthria, severe dysphagia, wheelchair dependence, urinary catheterisation, and institutionalization. Early disease milestones include falls and cognitive impairment in PSP, and urinary catherization and falls in MSA. Time from milestone to death is variable. Conclusions: Milestones can be used to follow disease progression and help predict survival. We propose a framework in which milestones are used as triggers for targeted neuropalliative care interventions including the early initiation of a primary palliative care or referral to specialised palliative care services.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".