Incidence of endophthalmitis after phacoemulsification cataract surgery: a Meta-analysis
Bibliographic record
Abstract
AIM: To evaluate the overall endophthalmitis incidence and the effectiveness of potential prophylaxis measures following phacoemulsification cataract surgery (PCS). METHODS: , 2021. We included studies that reported on the incidence of endophthalmitis following PCS. The quality of the included studies was critically evaluated with the Newcastle-Ottawa quality assessment scale. The random effect or the fixed-effects model was used to evaluated the pooled incidence based on the heterogeneity. The publication bias was assessed by Egger's linear regression and Begg's rank correlation tests. RESULTS: A total of 39 studies containing 5 878 114 eyes were included and critically appraised in the Meta-analysis. For overall incidence of endophthalmitis after PCS, the Meta-analysis yielded a pooled estimate of 0.092% (95%CI: 0.083%-0.101%). The incidence appeared to decrease with time (before 2000: 0.097%, 95%CI: 0.060%-0.135%; 2000 to 2010: 0.089%, 95%CI: 0.076%-0.101%; after 2010: 0.063%, 95%CI: 0.050%-0.077%). Compared with typical povidone-iodine solution (0.178%, 95%CI: 0.071%-0.285%) and antibiotics subconjunctival injections (0.047%, 95%CI: 0.001%-0.095%), the use of intracameral antibiotics significantly reduced the incidence of endophthalmitis after PCS (0.045%, 95%CI: 0.034%-0.055%, RR: 7.942, 95%CI: 4.510-13.985). CONCLUSION: Due to the advancement of phacoemulsification technology and the widespread use of intracameral antibiotics, the incidence of endophthalmitis following PCS shows a decreasing trend over time. The use of intracameral antibiotics administration will significantly reduce the risk of endophthalmitis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.009 | 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 teacher head, 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".