TAP AND INJECT VERSUS PARS PLANA VITRECTOMY FOR POSTPROCEDURAL ENDOPHTHALMITIS
Bibliographic record
Abstract
PURPOSE: To compare the visual outcomes after prompt pars plana vitrectomy (PPV) with tap biopsy and intravitreal antimicrobial injection to treat postinjection and postsurgery endophthalmitis. METHODS: The Cochrane Central Register of Controlled Trials, Ovid MEDLINE, and Ovid Embase databases were searched for articles published between January 2010 and November 2020. Two independent reviewers selected articles and extracted data. We analyzed data in RevMan 5.3 and assessed methodological quality using the Cochrane ROBINS-I tool. The mean improvement in visual outcome was compared between PPV and intravitreal antimicrobial injection as a relative risk of improving ≥2 lines and a mean logarithm of the minimal angle of resolution difference in improvement. RESULTS: Fifteen retrospective case series (1,355 eyes), of which 739 eyes (55%) received intravitreal antimicrobial injection and 616 (45%) received PPV as initial treatment, were included. The overall relative risk of improving 2 or more lines in PPV in comparison with intravitreal antimicrobial injection was 1.04 (95% CI 0.88-1.23; P = 0.61; I2 = 0%) with a mean difference of 0.04 (95% CI -0.18 to 0.27; P = 0.69; I2 = 0%). The results stayed robust when subgroup analysis based on causative procedure for endophthalmitis was performed. CONCLUSION: Intravitreal antimicrobial injection is noninferior to PPV for the treatment of postcataract operation, postinjection, and post-PPV endophthalmitis.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".