Safety in cardiovascular profile for the use of Propranolol as co-analgesic treatment in non-cardiac surgery, a pilot study
Bibliographic record
Abstract
Background: Perioperative alternatives to treat pain are still mostly limited to the delivery of systemic opioids. Recently animal and clinical studies have suggested β2-receptors as a possible target to back up analgesia performed by opioids. Co-administration of opioid agonists with β-blockers resulted in substantial synergetic analgesia in animal pain behavioral models. Thus, co-administration of β2-blockers with opioids might be a resourceful synergic combination able to maximize opioids analgesia while minimizing their adverse effects. Despite encouraging results from preclinical studies, a clear understanding of the role of β2-receptor role in human analgesia is still lacking. Thus a randomized controlled trial to clarify the role of β2-blockers as co-analgesic adjuvants was designed and initiated at the McGill University Health Centre (NCT02511483). The hypothesis of the study was that Propranolol would be able to reduce Morphine consumption after surgery without impacting the hemodynamic stability of the patients. However, particularly, concerns related to the hemodynamic effects of β2-receptor blockage prevent their usage. To address this concern, we performed a planned interim-analysis from data of the ongoning randomized control trial to determine the hemodynamic safety of β2-adrenergic antagonist administration in the perioperative setting. Methods: Data from patients recruited in this ongoing, randomized controlled trial were analyzed. Patients undergoing abdominal and gynecological laparoscopic surgery were randomized to receive either Propranolol (Propranolol group) or Placebo (Placebo group) in combination with Morphine as co-analgesic adjuvants. Perioperative blood pressure and heart rate were recorded. Postoperative analgesia, morphine consumption, opioid side-effects, were also measured. Results: Systolic blood pressure (SBP) during the induction and emergency from anesthesia was higher in Propranolol Group versus the Placebo Group (induction of anesthesia: 121 mmHg ±21.5 vs 110 mmHg ±23.7; p-value: 0.04; emergence of anesthesia 117 mmHg ±12.5 vs 108 mmHg ±10.8; p-value: <0.01). No significant difference was find for diastolic blood pressure (DBP). Heart rate (HR) was lower in patients treated with Propranolol at the emergence from anesthesia (61 ±7.4 bpm vs 74 ±6.5 bpm, p-value: <0.01) and continued to be lower during the stay in PACU (67 ±7.1 bpm vs 90 ±21.9 bpm; p-value: 0.05) and on the surgical ward (66 ±6.4 bpm vs. 86 ±12.3 bpm, p-value: 0.02) on the day of the surgery (day 0). Conclusions: The results of this interim analysis suggest that perioperative administration of propranolol as co-analgesic adjuvant at this dosage and regimen is feasible, and does not significantly affect blood pressure and heart rate. Although, few statistically significant differences were observed between the 2 groups, the clinical relevance of these findings is questionable as blood pressure and heart rate always remained within the safety range in the first 24 hours after surgery. On the other side, analgesic benefits related to the administration of Propranolol were not observed. Recruitment of future patients will to better define the analgesic role of administering Propranolol as co-analgesic adjuvant in the context of multimodal analgesia.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".