Early postoperative intraocular pressure elevation following cataract surgery
Bibliographic record
Abstract
PURPOSE OF REVIEW: The aim of this review was to assess the risk factors and course of postoperative intraocular pressure (IOP) increase in order to determine the optimal the treatment. RECENT FINDINGS: Early postoperative IOP elevation following cataract surgery is a frequent adverse event, and might represent 88% early postoperative complications. The risk factors for IOP elevation following phacoemulsification cataract surgery include residual viscoelastic material, resident performed surgery, glaucoma, pseudoexfoliation syndrome, axial length over 25 mm, tamsulosin intake, topical steroid application in steroid responders. A day-1 postoperative follow-up might be questioned, even in glaucoma patients, as in IOP spikes the topmost IOP elevation occurs 3-4 h postoperatively. SUMMARY: Several IOP-lowering agents have been evaluated, but none has completely prevented the occurrence of IOP spikes. We recommend applying a combination of dorzolamide/timolol and brinzolamide topically in high-risk patients, particularly with preexisting optic nerve damage. Corticosteroid cessation usually results in a reduction of the IOP to normal levels in steroid responders. Additional studies are required to assess the optimal treatment, especially in glaucoma patients.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".