Factors Associated with Poor Clinical Outcomes in Patients with Post- Cataract Surgery Endophthalmitis: A systematic review
Bibliographic record
Abstract
Introduction & Objectives : Postoperative Endophthalmitis has remained one of the rare yet most devastating complications of cataract surgery. The previous study mentioned that 15-30% of POE patients have an unfavorable outcome on visual acuity of less than 20/200 and may even result in the loss of the eye. Thus, this study aims to review and summarize prognostic factors that can affect the final outcome of postoperative endophthalmitis from cataract surgery.
 Methods : We systematically searched with PRISMA 2020 across 5 databases (PubMed, Scopus, SAGE, Embase, and Cochrane) with the search term “(prognosis OR prognostic factor) AND postoperative endophthalmitis) AND (cataract surgery)”, as well as reference screening for any additional relevant studies. The risk of bias from included studies will be assessed using Newcastle-Ottawa Quality Assessment Scale.
 Results : Out of 314 studies, we decided to only include 13 studies that match our inclusion and exclusion criteria. All of the studies are cohort studies with a total of 753 patients affecting 753 eyes and most of them are coming from Asian countries. Both diagnosis and intervention given are based on Endophthalmitis Vitrectomy Study (EVS) result.
 Conclusion : Prognostic factors for post-cataract surgery endophthalmitis are corneal involvement, microbiological investigation result, intervention timing, treatment modality, comorbidities, and other complications
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".