Lipid Emulsion Combined with Epinephrine and Vasopressin Does Not Improve Survival in a Swine Model of Bupivacaine-induced Cardiac Arrest
Bibliographic record
Abstract
BACKGROUND: This study sought to evaluate the efficacy of lipid emulsion in reversing bupivacaine-induced cardiovascular collapse when added to a resuscitation protocol that included the use of epinephrine and vasopressin. METHODS: After induction of general anesthesia and instrumentation, 19 mixed-breed domestic swine had cardiovascular collapse induced by an intravenous bolus of 10 mg/kg bupivacaine. After 5 min of resuscitation including chest compressions, epinephrine (100 microg/kg) and vasopressin (1.5 U/kg), animals were randomized to receive either a bolus of 20% lipid emulsion (4 ml/kg) followed by a continuous infusion (0.5 ml x kg(-1) x min(-1)) or an equal volume of saline. Investigators were blinded to the treatment assignment. The primary endpoint was return of spontaneous circulation (mean arterial pressure of at least 60 mmHg for at least 1 min). RESULTS: Treatment groups were similar with respect to baseline measurements of weight, sex, and hemodynamic and metabolic variables. The rates of return of spontaneous circulation were similar between groups: (3 of 10) in the lipid group and 4 of 9 in the saline group (P = 0.65). Total serum bupivacaine concentrations were higher in the lipid group at the 10-min timepoint (mean +/- SEM: 23.13 +/- 5.37 ng/ml vs. 15.33 +/- 4.04 ng/ml, P = 0.004). More norepinephrine was required in the lipid group compared to the saline group to maintain a mean arterial pressure above 60 mmHg during the 60-min survival period (mean +/- SEM: 738.6 +/- 94.4 vs.. 487.3 +/- 171.0 microg). CONCLUSIONS: In this swine model, lipid emulsion did not improve rates of return of spontaneous circulation after bupivacaine-induced cardiovascular collapse.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".