Management of neurobehavioral changes in PSP
Bibliographic record
Abstract
Progressive supranuclear paralysis (PSP) is an atypical parkinsonian disorder associated with oculomotor features, postural instability along with cognitive problems and neuropsychiatric symptoms. Usually, the treatment focuses on motor symptoms, however addressing behavioral and cognitive symptoms could have a significant impact on functionality and quality of life of patients and their relatives. In this session the attendees will learn how to use widely available tools for screening the most common neuropsychiatric symptoms and how to manage them, both with pharmacological treatment and non-pharmacological interventions. Treatments discussed will include depression, apathy, anxiety, cognitive decline, and other common neuropsychiatric issues. Cognitive impairments in Alzheimer's disease are commonly managed with cholinesterase inhibitors and NMDA receptor antagonists, although their efficacy in non-Alzheimer's dementias is limited. Behavioral and neuropsychiatric symptoms, including agitation, depression, and apathy, are frequently addressed using antidepressants, antipsychotics, and mood stabilizers, despite the challenges of balancing efficacy with adverse effects. During this session, we will emphasize the importance of comprehensive assessment to better capture the multi-faceted neurobehavioral impairments seen in PSP patients.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".