Erythromycin Promotes Gastric Emptying During Acute Pain in Volunteers
Bibliographic record
Abstract
In Brief In this double-blind cross-over study, we assessed whether erythromycin infusion is effective as a prokinetic drug against gastroparesis from acute pain. The effect of erythromycin on gastric emptying (GE) was measured in seven volunteers subjected to a standardized acute painful stimulus. The GE rate for solids was measured using the octanoic acid breath test. An acetaminophen absorption test measured the GE rate for liquids. Five minutes after ingestion of a 13C-labeled meal, the subjects received in randomized order either a test (placebo and erythromycin groups) or a control (control group) stimulus consisting of repeated 1-min immersion of a hand into 4°C (test) or 37°C (control) water, with 15 s for recovery between immersions, for a total of 20 min. While the stimulus was applied, 250 mL saline (control and placebo groups) or 250 mg erythromycin (erythromycin group) was infused. Pain and stress were evaluated using visual analog scales, and standard hemodynamic values were recorded throughout the study. Our results show that acute stress decreased GE for solids, which was significantly accelerated in the erythromycin group in comparison with the placebo group. GE for liquids was similar in the three groups. We conclude that erythromycin is effective as a prokinetic drug for solids in acute painful situations. IMPLICATIONS: In volunteers with full stomachs subjected to acute pain, erythromycin is effective as a prokinetic drug on the gastric emptying rate for solids. Its administration could be useful before emergency anesthesia in nonfasting patients with pain to prevent the risk of pulmonary aspiration of gastric contents.
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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 | 0.001 |
| 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 | 0.001 | 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".