Postoperative Pain Management in Vitreoretinal Surgery for Retinal Detachment: A Systematic Review of Randomized Controlled Trials
Bibliographic record
Abstract
Purpose: The purpose of this study is to examine the evidence for postoperative pain management in patients undergoing vitreoretinal surgery for retinal detachment by systematic review. Methods: A systematic review of the literature was performed using multiple databases in July 2016 and September 2017. Two independent reviewers screened titles and abstracts and analyzed selected papers in detail. Included studies assessed patients undergoing vitreoretinal surgery for retinal detachment and described postoperative pain management. Risk of bias was assessed using the criteria outlined in the “risk of bias” tool in the Cochrane Handbook for Systematic Reviews of Interventions. Results: Nine randomized controlled studies comprising 517 patients met the inclusion criteria. Pain management included perioperative peribulbar, sub-Tenon, and retrobulbar anesthetic block; perioperative systemic anti-inflammatory and postoperative systemic and topical anti-inflammatory drugs; and ice compress. Pain scores were assessed with nominal, numerical, and visual analog scales. Risk of bias was low for 2 studies, unclear for 4 studies, and high for 3 studies. All studies reported better postoperative pain scores with the active treatment group except for a single study comparing retrobulbar chirocaine with and without clonidine. No serious adverse events were reported for any of the studies. Conclusion: Heterogeneity of studies did not allow for meta-analysis, but qualitative analysis suggests that pain relief can be achieved in the short term with a variety of treatment interventions. Additional study is required to specifically examine pain management strategies according to the characteristics of the anesthesia and surgery as well as the needs of the patient.
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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 | 0.072 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.051 | 0.022 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".