D.1 Feasibility and impact of palliative care at any stage of amyotrophic lateral sclerosis
Bibliographic record
Abstract
Background: Although palliative care (PC) is recommended for patients with amyotrophic lateral sclerosis (ALS), many patients receive PC very late or not at all. Our study goals included 1) determing the feasibility of early PC 2) describing patient/caregiver satisfaction with early PC and 3) measuring the impact of early PC on quality of life (QOL) and mood. Methods: Patients followed at the multidisciplinary ALS clinic in Ottawa, Canada and their caregivers were eligible for the study irrespective of duration or severity of disease. All participants completed questionnaires tracking QOL and mood and all were offered a palliative care consultation. Participants completed a satisfaction survey post-PC consultation. Results: 32 patients and 20 caregivers received a PC consultation, conducted virtually. All of them found the consult beneficial and none of the patients reported preferring the consultation later in their illness. The PC consultations were most highly rated by patients with high levels of anxiety and worse bulbar function, and by caregivers of patients with low function. There was no statistically significant change in mood or QOL compared to the 7 participants who declined PC consultation. Conclusions: PC consultations are feasible and beneficial at all stages of illness. Patients with anxiety and bulbar dysfunction may benefit most.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".