Characterizing Difficulties and Management of Sleep Disturbances in a Tertiary Palliative Care Unit—A Retrospective Review
Bibliographic record
Abstract
Objective: Difficulty sleeping is common in palliative care, however often unrecognized by palliative care physicians. This retrospective review aims to gain a better understanding of the causes and treatment of sleeping disturbances in a tertiary palliative care unit. Methods: This study included 200 palliative care inpatients admitted between January 1, 2015, and August 31, 2020. Patients with sleep disturbances were placed into 3 subgroups: insomnia, delirium, and those with an unclear diagnosis. These categories were analyzed by bivariate analysis (ANOVA, Kruskal-Wallis) to determine statistical significance. Results: A total of 156 (78%) patients had symptoms suggestive of sleep disturbance and 163 (81.5%) patients were prescribed a sedative for sleep disturbance. Most patients were prescribed lorazepam (52 [26%]), followed by haloperidol (47 [23.5%]), and zopiclone (33 [16.5%]). Benzodiazepine and zopiclone prescribing decreased over time, while antipsychotic prescribing remained stable. When analyzed according to the most likely cause of the sleep disturbance, patients with insomnia had a higher Palliative Performance Score ( P < .035) and were more likely to have a previous medical history of insomnia ( P < .0003) than those with delirium. Both insomnia and delirium were quickly diagnosed but patients with unclear sleep disturbances took longer to recognize and treat. Conclusion: These results suggest that sleep disturbances are common at the end of life and can be challenging to categorize. Using specific criteria may be helpful in differentiating insomnia versus delirium and ultimately lead to more consistent approaches to management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".