Pharmacovigilance in Hospice/Palliative Care: Net Effect of Haloperidol for Nausea or Vomiting
Bibliographic record
Abstract
BACKGROUND: Haloperidol is widely prescribed as an antiemetic in patients receiving palliative care, but there is limited evidence to support and refine its use. OBJECTIVE: To explore the immediate and short-term net clinical effects of haloperidol when treating nausea and/or vomiting in palliative care patients. DESIGN: A prospective, multicenter, consecutive case series. SETTING/SUBJECTS: Twenty-two sites, five countries: consultative, ambulatory, and inpatient services. MEASUREMENTS: When haloperidol was started in routine care as an antiemetic, data were collected at three time points: baseline; 48 hours (benefits); day seven (harms). Clinical effects were assessed using the National Cancer Institute's Common Terminology Criteria for Adverse Events (NCI CTCAE). RESULTS: Data were collected (May 2014-March 2016) from 150 patients: 61% male; 86% with cancer; mean age 72 (standard deviation 11) years and median Australian-modified Karnofsky Performance Scale 50 (range 10-90). At baseline, nausea was moderate (88; 62%) or severe (11; 8%); 145 patients reported vomiting, with a baseline NCI CTCAE vomiting score of 1.0. The median (range) dose of haloperidol was 1.5 mg/24 hours (0.5-5 mg/24 hours) given orally or parenterally. Five patients (3%) died before further data collection. At 48 hours, 114 patients (79%) had complete resolution of their nausea and vomiting, with greater benefit seen in the resolution of nausea than vomiting. At day seven, 37 (26%) patients had a total of 62 mild/moderate harms including constipation 25 (40%); dry mouth 13 (21%); and somnolence 12 (19%). CONCLUSIONS: Haloperidol as an antiemetic provided rapid net clinical benefit with low-grade, short-term harms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| 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".