Prevalence of symptoms at the end of life in an acute care hospital: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: There is currently debate over the benefits and harms of physician-assisted death. One of the factors influencing this debate is concern about symptoms in the days before death. The objective of this study was to describe the frequency of symptoms before death and determine patient characteristics associated with these symptoms. METHODS: We reviewed the medical record of every patient who died at a multisite academic teaching hospital over a 3-month period. We determined the number of episodes of pain, dyspnea, agitation and nausea during the final 48 hours of life and assessed the patient and encounter characteristics associated with 2 or more episodes of symptoms. RESULTS: A total of 480 patients died during the study period. Of these patients, 29.2% (140/480) had 2 or more symptoms in the final 48 hours of life. Higher Elixhauser comorbidity scores (relative risk [RR] 1.35, 95% confidence interval [CI] 1.23-1.49), having a family doctor (RR 2.33, 95% CI 1.02-5.38), being admitted to the medical oncology service (RR 1.51, 95% CI 1.11-2.05) and having a documented order for no resuscitation written early during the stay in hospital (RR 1.38, 95% CI 1.01-1.89) were independently associated with symptoms. Admission to intensive care was associated with fewer symptoms (RR 0.39, CI 95% 0.19-0.80). INTERPRETATION: Symptoms are common in the final 48 hours of life, particularly in patients with multimorbidity who want limitations on the aggressiveness of their care. An integrated palliative approach is needed for select at-risk patients.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".