Single-Dose Haloperidol for the Prophylaxis of Postoperative Nausea and Vomiting After Intrathecal Morphine
Bibliographic record
Abstract
UNLABELLED: Postoperative nausea and vomiting (PONV) occurs frequently with the use of intrathecal morphine. We studied the ability of a single, small dose of the inexpensive, long-acting, dopamine receptor-blocking drug, haloperidol, to prevent PONV after spinal anesthesia using local anesthetic with morphine 0.3 mg. One-hundred-eight adult patients undergoing elective lower limb orthopedic or endoscopic urologic procedures under spinal anesthesia were randomized to receive IM haloperidol 1 mg (H1), haloperidol 2 mg (H2), or placebo (P) after an intrathecal injection. Patients were assessed for 24 h after surgery, with treatment failure being defined as nausea >1 on a 10-cm visual analog scale or any vomiting or request for rescue antiemetic. Most treatment failures occurred during the first 12 h (60% overall), and haloperidol led to a dose-dependent decrease in PONV (first 12 h: 76% P, 56% H1, and 50% H2; P = 0.012). A history of PONV was strongly associated with PONV in the current study, regardless of treatment group. There were no dystonic reactions noted to either dose of haloperidol. We conclude that haloperidol reduces the incidence of PONV after intrathecal morphine, although this incidence remains a significant problem even with treatment. IMPLICATIONS: In this randomized, double-blinded, placebo-controlled trial, a single, small IM dose of haloperidol 1 mg or 2 mg reduced the incidence of postoperative nausea and vomiting after spinal anesthesia with local anesthetic and intrathecal morphine.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".