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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".