Intra-arterial thrombolysis for central retinal artery occlusion: a systematic review
Bibliographic record
Abstract
INTRODUCTION: This review provides an updated analysis of the evidence supporting intra-arterial thrombolysis (IAT) for the treatment of central retinal artery occlusion (CRAO). METHODS: A systemic review of the literature indexed by Ovid MEDLINE was performed for the following medical subject headings: central retinal artery occlusion, thrombolysis, intra-arterial, fibrinolysis. Studies were analysed individually and categorised by study type, and extracted data grouped together for statistical analysis. Only studies with five patients or more were included in the review. RESULTS: Twenty-three studies were identified in the original search; eight were selected for the analysis. Of these studies, 158 patients were represented, in which treatment was instituted within an average of 8.4 (SD 4) h of symptom onset. In these patients, visual improvement occurred on average in 93% of patients, with 13% achieving 20/20 or better, 25% achieving 20/40 or better, and 41% achieving 20/200 or better. Complications occurred in 4.5% of cases. CONCLUSION: IAT may produce superior visual outcomes compared with conventional treatments for CRAO when instituted in certain situations. At the moment, there is insufficient evidence to support the routine use of IAT to treat CRAO. Well-designed prospective, randomised trials remain to be done.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.008 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".