Interventions for reducing bleeding and swelling in eyelid and periocular surgeries: a systematic review of randomized controlled trials
Bibliographic record
Abstract
PURPOSE: To systematically evaluate evidence-based interventions aimed at reducing postoperative edema and ecchymosis in eyelid and periocular surgery, with the goal of improving patient outcomes and recovery. METHODS: A systematic review of 29 randomized controlled trials (RCTs), involving 2,287 patients undergoing eyelid and periocular surgery, was conducted. A comprehensive search was performed across Embase, MEDLINE, Cochrane Central, and Google Scholar up to April 2025. Studies assessing interventions for postoperative edema and ecchymosis were included. Study quality was evaluated using the Cochrane Risk of Bias 2 (RoB 2) tool. RESULTS: Tranexamic acid was the most consistently effective intervention for reducing ecchymosis. Vessel-preserving surgical techniques significantly reduced edema and hematoma, while skin-only excision led to less swelling than combined skin and muscle excision. Carbon dioxide laser - assisted blepharoplasty improved hemostasis and reduced chemosis. Magnesium sulfate dressings were more effective for edema than ice packs, though cold compresses provided short-term relief. Anesthesia modifications (pre-cooling, buffered lidocaine) reduced injection pain but had variable effects on swelling. Herbal and adjunctive therapies, including Arnica montana and bromelain, showed no significant benefits. CONCLUSION: Tranexamic acid, vessel-preserving surgical methods, and magnesium sulfate dressings are among the most effective strategies for minimizing ecchymosis and edema in eyelid and periocular surgery. Further RCTs should explore optimized combinations of these interventions and assess long-term patient-reported outcomes.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.014 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".