End-of-Life and Hospice Care in Neurologic Diseases
Bibliographic record
Abstract
The care of a patient with neurologic disease at end-of-life requires expertise in addressing advance care planning, hospice, symptom management, and caregiver support. Neurologists caring for patients with advanced neurologic disease often identify changes in disease trajectory, functional status, or goals of care that prompt discussions of advance care planning and hospice. Patients nearing end-of-life may develop symptoms such as dyspnea, secretions, delirium, pain, and seizures. Neurologists may be the primary clinicians managing these symptoms, particularly in the hospitalized patient, though they may also lend their expertise to non-neurologists about expected disease trajectories and symptoms in advanced neurologic disease. This article aims to help neurologists guide patients and caregivers through the end-of-life process by focusing on general knowledge that can be applied across diseases as well as specific considerations in severe stroke and traumatic brain injury, amyotrophic lateral sclerosis, Parkinson's disease, and dementia.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".