Symptom relief during last week of life in neurological diseases
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to investigate symptom prevalence, symptom relief, and palliative care indicators during the last week of life, comparing them for patients with motor neuron disease (MND), central nervous system tumors (CNS tumor), and other neurological diseases (OND). MATERIAL & METHODS: Data were obtained from the Swedish Register for Palliative Care, which documents care during the last week of life. Logistic regression was used to compare patients with MND (n = 419), CNS tumor (n = 799), and OND (n = 1,407) as the cause of death. RESULTS: The most prevalent symptoms for all neurological disease groups were pain (52.7% to 72.2%) and rattles (58.1% to 65.6%). Compared to MND and OND, patients with CNS tumors were more likely to have totally relieved pain, shortness of breath, rattles, and anxiety. They were also more likely to have their pain assessed with a validated tool; to receive symptom treatment for anxiety, nausea, rattles, and pain; to have had family members receive end-of-life discussions; to have someone present at death; and to have had their family members offered bereavement support. Both patients with CNS tumor and MND were more likely than patients with OND to receive consultation with a pain unit and to have had end-of-life discussions. CONCLUSIONS: The study reveals high symptom burden and differences in palliative care between the groups during the last week of life. There is a need for person-centered care planning based on a palliative approach, focused on improving symptom assessments, relief, and end-of-life conversations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".