Low molecular weight heparin for the treatment of retinal vein occlusion: a systematic review and meta-analysis of randomized trials
Bibliographic record
Abstract
Retinal vein occlusion is a frequent cause of visual loss for which few effective therapies are available. Anticoagulation with low molecular weight heparin might be of value in its treatment. We conducted a systematic review and meta analysis of randomized trials evaluating the effect of low molecular weight heparin in patients with retinal vein occlusion. Data sources included MEDLINE, EMBASE, HealthSTAR, the Cochrane Library, Lilacs, the Investigative Ophthalmology and Visual Science database and gray literature. Main outcome was the mean difference between the visual acuity measured at baseline and at six months expressed in the logMAR scale. Secondary outcome was a composite of any adverse ocular outcome including: worsening of visual acuity, visual fields or fluorescein angiography, or development of iris neovascularization, any neovascularization or neovascular glaucoma. Subgroup analyses for branch versus central retinal vein occlusion were conducted. We identified 1,084 references of which 3 studies comparing low molecular weight heparin with aspirin (229 evaluable patients) were included. Overall, the pooled mean visual acuity difference was -0.23 logMAR (95% CI -0.38, -0.09; P=0.002) in favor of low molecular weight heparin. Low molecular weight heparin was associated with a 78% risk reduction for developing any adverse ocular outcome (pooled RR 0.22; 95% CI 0.10, 0.46; P<0.001). In subgroup analyses benefits seemed lower in branch retinal vein occlusion. No increased vitreous hemorrhages were observed. In patients with retinal vein occlusion treatment with low molecular weight heparin seems to be associated with improvement in the visual acuity and less adverse ocular outcomes. These benefits might differ in patients with central as opposed to branch retinal vein occlusion. Further studies are required to confirm these findings and clarify its benefits in specific subgroups of patients before definitive recommendations can be made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.047 | 0.019 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".