Levobupivacaine 0.75% vs. lidocaine 4% for topical anaesthesia
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to compare the efficacy of topical levobupivacaine drops 0.75% vs. lidocaine drops 4% in cataract surgery. METHODS: We examined 203 patients undergoing cataract surgery by phacoemulsification. They were randomized into two groups: one received four drops of lidocaine 4% and the other received four drops of levobupivacaine 0.75%. The onset and offset times of sensory block were evaluated. Application, intraoperative and postoperative subjective pain was quantified by the patients using a verbal pain score. Complications, rates of supplemental anaesthesia, and the satisfaction of surgeon and patients were also recorded. RESULTS: The mean sensory onset and offset times were significantly higher for the levobupivacaine group (P < 0.01). Pain score was lower in the levobupivacaine group than in the lidocaine one and the difference was statistically significant at all stages (P < 0.01). The mean satisfaction scores of patients and surgeon were also statistically higher for levobupivacaine (P < 0.01). No significant differences for complications and rates of supplemental anaesthesia were found. CONCLUSIONS: Topical levobupivacaine 0.75% shows the same efficacy and safety as lidocaine 4% in cataract surgery by phacoemulsification. There was an adequate block with a good level of satisfaction of surgeon and patients. Levobupivacaine 0.75% offers a new and acceptable choice for topical anaesthesia in cataract surgery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".