Pharmacokinetics of Lidocaine Hydrochloride Administered with or without Adrenaline for the Paravertebral Brachial Plexus Block in Dogs
Bibliographic record
Abstract
Adrenaline is known to prolong the duration of local anesthesia but its effects on the pharmacokinetic processes of local anesthetic drugs are not fully understood. Our objective was to develop a compartmental model for quantification of adrenaline's impact on the pharmacokinetics of perineurally-injected lidocaine in the dog. Dogs were subjected to paravertebral brachial plexus block using lidocaine alone or adrenalinated lidocaine. Data was collected through a prospective, randomised, blinded crossover protocol performed over three periods. Blood samples were collected during 180 minutes following block execution. Compartmental pharmacokinetic models were developed and their goodness-of-fit were compared. The lowering effects of adrenaline on the absorption of lidocaine were statistically determined with one-sided tests. A one-compartment disposition model with two successive zero-order absorption processes best fitted our experimental data. Adrenaline decreased the peak plasma lidocaine concentration by approximately 60% (P < 0.001), decreased this local anesthetic's fast and slow zero-order absorption rates respectively by 50% and 90% (P = 0.046, and P < 0.001), which respective durations were prolonged by 90% and 1300% (P < 0.020 and P < 0.001). Lidocaine demonstrated a previously unreported atypical absorption profile following its paravertebral injection in dogs. Adrenaline decreased the absorption rate of lidocaine and prolonged the duration of its absorption.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".