Goal-Concordant Care in People With Amyotrophic Lateral Sclerosis Receiving Palliative Care
Bibliographic record
Abstract
Context Although it is known where people with amyotrophic lateral sclerosis (ALS) are dying, less is known about whether they are dying where they want to. Objectives To determine the rate of dying in a preferred place and factors associated with doing so in people with ALS receiving clinic-based specialist palliative care. Methods Retrospective cohort study of people with ALS receiving clinic-based specialist palliative care in Toronto, Canada between July 2022 and February 2024. Association between preferred and actual place of death was determined using a χ 2 test. Factors associated with dying in a preferred place were determined using a multivariable binary logistic regression analysis. Results In 367 individuals, at time of consultation, median age was 67 years; 60.8% had a Palliative Performance Scale score between 50-60%, and 43.3% had non-invasive ventilation. Mortality rate up to February 2024 was 41.7%. 85.4% stated a preference to die at home, 8.7% in hospital, and 5.9% in a hospice facility; whereas, 54.9% died at home, 34% in hospital, and 11.1% in a hospice facility. Of those with known preferred and actual place of death, 70.1% died in a preferred place (χ 2 =36.2; p<0.001). Dying in a preferred place was associated with increasing age (OR=1.1; 95% CI=1.0-1.1) and having non-invasive ventilation (OR=2.5; 95% CI=1.0-6.2). Conclusion Younger age and not having non-invasive ventilation at the time of consultation may suggest a higher risk of goal-discordant end-of-life care and the need to engage in early future planning when these factors are identified.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".