Determining Minimum Effective Anesthetic Concentration of Hyperbaric Bupivacaine for Spinal Anesthesia
Bibliographic record
Abstract
We determined the minimum effective anesthetic concentration (MEAC) of bupivacaine for spinal anesthesia, defined as the median effective concentration at which a spinal anesthetic produces surgically equivalent anesthesia within 20 min of administration in 50% of human subjects. Two doses of spinal bupivacaine (7.5 mg and 10 mg) were administered to 45 volunteers (19–39 yr) in a randomized, double-blinded fashion. Hyperbaric bupivacaine solutions of 0.1% to 0.75% containing 8.25% dextrose were administered intrathecally and MEAC established by using the Dixon’s up-and-down method. Complete anesthesia was defined as: 1) pinprick anesthesia at or higher than T12; 2) anesthesia to transcutaneous tetanic electric stimulation (50 Hz at 60 mA for 5 s) in the knees; and 3) complete leg paralysis, all occurring in both lower extremities within 20 min of intrathecal injection. We found that the MEAC of spinal bupivacaine was 0.43% (95% confidence interval 0.24–0.62) when 10 mg was administered. At this dose, a concentration as low as 0.1% could provide complete anesthesia, but consistent blockade was obtained only with the 0.7% solution. The 7.5-mg dose failed to provide complete anesthesia consistently, even in the presence of 0.75% (maximum). The current commercially available 0.75% concentration of hyperbaric bupivacaine seems to be clinically optimal when 10 mg is used if complete bilateral lower extremity blockade is desired. Implications The value of the minimum effective anesthetic concentration for hyperbaric spinal bupivacaine is dose-dependent. Complete anesthesia can be achieved with smaller concentrations when the dose of spinal anesthetic is increased. The current commercially available 0.75% concentration of hyperbaric bupivacaine seems to be clinically optimal when 10 mg is used if complete bilateral lower extremity blockade is desired.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".