Levobupivacaine versus bupivacaine in peribulbar block for ophthalmic surgeries: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of levobupivacaine versus bupivacaine for peribulbar block in ophthalmic surgery. METHODS: A systematic review and meta-analysis were performed as per the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Publications in MEDLINE, EMBASE, EMCARE, CINAHL, and the Cochrane Central Register of Controlled Trials (CENTRAL) that compared levobupivacaine and bupivacaine for peribulbar block in ophthalmic surgery were screened for eligibility from inception through December 22, 2023. Our analyses were summarized by calculating mean differences (MD) for continuous variables and odds ratios (OR) for dichotomous variables, using either fixed-effects or random-effects meta-analysis based on the level of heterogeneity. RESULTS: Eight randomized control trials enrolling 800 patients were identified in the English literature published between 1998 and 2023. There was no statistically significant difference in akinesia score at 2 minutes (MD = 0.17; p = 0.12) or 10 minutes postinjection (MD = 0.02; p = 0.89). Similarly, there was no statistically significant difference between the 2 groups in terms of time of onset of the anesthetic effect (MD = 0.38; p = 0.36), postoperative diplopia (OR = 0.62; p = 0.17), incidence of systemic hypotension (OR = 1.00; p = 1.00) or verbal pain scales during the block (MD = 0.04; p = 0.66), at the end of surgery (MD = -0.01; p = 0.94) or 4 hours postoperatively (MD = -0.00; p = 0.98). CONCLUSIONS: As a result of conducting this meta-analysis, we conclude that there is no significant difference between levobupivacaine and bupivacaine in terms of akinesia score, time to onset of anesthetic effect, verbal pain scales, postoperative diplopia, or incidence of systemic hypotension.
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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 | 0.018 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.050 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".