Propranolol and Oxytocin-induced Contractility in Gravid Human Myometrium: An Ex Vivo Laboratory Study
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of propranolol on myometrial contractions induced by low dose and high dose oxytocin. DESIGN: Prospective ex vivo laboratory study. SETTING: Mount Sinai Hospital, Toronto. POPULATION: Full-term parturients who underwent elective caesarean deliveries (CD). METHODS: Two models were developed in the organ bath chamber using myometrial samples obtained during CDs: (i) Labor induction-augmentation model with low-dose oxytocin consisting of 3 groups with the administration of propranolol before and during simulated labor, and a control group. (ii) Postpartum haemorrhage (PPH) model with high-dose oxytocin consisting of 4 groups with the administration of propranolol during and/or after augmented labor (desensitised with oxytocin), and a control group. MAIN OUTCOME MEASURES: Myometrial contractility was recorded using force transducers. RESULTS: In the labor induction-augmentation model, propranolol pre-treatment produced a higher area under the curve (AUC) of myometrial contractility induced by low-dose oxytocin (relative percentage difference [diff]: 20.4%; 95% CI [1.4%, 43.2%], p = 0.035) compared to control; however, no difference was observed when propranolol was given after the initiation of labor. In the oxytocin-desensitised PPH model, the AUC of myometrial contractility induced by high-dose oxytocin was improved with propranolol pre-treatment (diff 25.4% [0.2%, 56.8%], p = 0.048), co-treatment (diff 26.7% [3.7%, 54.7%], p = 0.02), and both pre- and co-treatment (diff 28.4% [7.0%, 54.1%], p = 0.007) when compared to the control group. CONCLUSIONS: Our ex vivo study suggests that propranolol can augment uterine activity by approximately 20%-25% when administered early during labor induction and augmentation. Clinical studies are warranted to determine the relevance of these findings in vivo. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03434444; https://clinicaltrials.gov/.
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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) | 0.000 | 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 | 0.001 |
| 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".