A comparison of general anesthesia versus local anesthesia in open globe injuries: A systematic review and meta-analysis
Bibliographic record
Abstract
ObjectiveLocal anesthesia represents an alternative to general anesthesia in selected patients undergoing repair for open globe injuries. This study aimed to evaluate and compare visual acuity and clinical outcomes in such patients.MethodsA systematic literature search was conducted across PubMed, Embase, Scopus, Cochrane Library, and Google Scholar. Adults (≥18 years) hospitalized with open globe injuries were included. Out of 551 articles screened, four observational studies met the inclusion criteria. Standardized Mean Differences (SMD) for continuous and Risk Ratios (RR) for dichotomous outcomes were pooled using the Inverse Variance method with a Random Effects model. Outcomes included visual acuity, wound location, wound length, and operative time.ResultsFour retrospective case series comprising 1,690 patients were included. All studies had low risk of bias per the Newcastle-Ottawa Scale. No significant difference was observed in best corrected visual acuity between groups (MD = -0.18; 95% CI: -0.45 to 0.08; p = 0.17; I² = 55%). Patients in the local anesthesia group had more anterior wound locations (MD = 1.33; 95% CI: 1.06-1.66; p = 0.01; I² = 65%). Wound length (MD = -4.97; 95% CI: -5.95 to -3.98; p < 0.00001; I² = 0%) and operative time (MD = -33.32; 95% CI: -40.82 to -25.82; p < 0.00001; I² = 0%) were significantly shorter.ConclusionLocal anesthesia was associated with more anterior wounds, shorter wound length, and reduced operative time without compromising visual outcomes. It may be a safe and effective alternative to general anesthesia in selected open globe injuries.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.038 |
| Bibliometrics | 0.007 | 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) | 0.004 | 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".