Droperidol Reduces Postoperative Nausea and Vomiting and Supports the Continuation of Intravenous Patient-Controlled Analgesia with Fentanyl
Bibliographic record
Abstract
PURPOSE: To examine the impact of adding droperidol to fentanyl-based intravenous patient- controlled analgesia (IVPCA) on the discontinuation of IVPCA use due to postoperative nausea and vomiting (PONV). METHODS: Patients who underwent surgeries other than abdominal surgeries and used IVPCA between April 2014 and March 2018 were selected. Patients using IVPCA with fentanyl alone were compared to patients using droperidol added to IVPCA. Patients were allocated to one of two groups depending on the drug used for IVPCA: 1) control group, fentanyl alone; 2) droperidol group, droperidol with fentanyl. The primary endpoint was the discontinuation of IVPCA due to PONV. Secondary endpoints included PONV within 48 hours after surgery, the number of antiemetics used, pain score, and adverse effects. Propensity score matching was used to control the differences in clinical features among patients. RESULTS: Among the 793 patients initially enrolled in this study, 145 were excluded via propensity score matching; 364 of the remaining patients received IVPCA supplemented with droperidol. Propensity score matching showed that discontinuation of IVPCA due to PONV was significantly decreased in the droperidol group compared to the control group (P = 0.01). Further, compared with the control group, the droperidol group had reduced nausea up to 24 hours after surgery (P < 0.01), and the number of vomiting episodes and use of antiemetics decreased within 12 hours after surgery (P < 0.01). CONCLUSIONS: The addition of droperidol to IVPCA is associated with a decrease in PONV, as well as the improved continuation of pain treatment with fentanyl-based IVPCA, similar to IVPCA with morphine. However, it is necessary to monitor the side effects of this treatment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".