ALS patients and PAD: description and comparison of patients from a neuromuscular clinic in Canada
Bibliographic record
Abstract
Objectives In Canada, patients with ALS (PALS) who meet specific criteria can request Medical Assistance in Dying (MAiD), also known as Physician-Assisted Death (PAD). However, little is known about the characteristics of those patients. This study describes PALS who died of MAiD and compares them with patients who died from natural disease complications.Methods A retrospective study of 209 consecutive PALS’ electronic medical records was performed. Patients selected had follow-up at the CHU de Québec–Université Laval and died between January 2014 and April 2023. Sociodemographic and disease evolution data were collected. Fisher’s exact test and Kolmogorov-Smirnov tests were used.Results The analysis included 174 patients. MAiD PALS (N = 64) were mainly males (54.7%), of median age 67 years, in a relationship (68.7%), and parents of adult children (71.9%). Both cohorts had similar past medical histories of depressive disorders (15%, p > 0.999). MAiD PALS elected to use percutaneous endoscopic gastrostomy (PEG) feeding in 18.7% of cases compared to 28.2% of PALS who died of complications of ALS (p = 0.203). Palliative care teams were significantly more likely to be involved with PALS elected to request MAiD (86.6%, p = 0.023).Discussion PALS who request MAiD share similar demographic and clinical characteristics with those who died from natural disease progression in our cohort. Trends toward differences were observed, namely, in the rate of disease progression, with PALS who requested MAiD more likely to be fast progressors than their counterparts, and in PEG feeding use with ALS MAiD patients less likely to request it. Palliative care involvement was more prevalent with MAiD PALS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".