Diclofenac for pain associated with intravitreal injections: a prospective, randomized, placebo‐controlled study
Bibliographic record
Abstract
IMPORTANCE: Intravitreal injections (IVI) are often painful. BACKGROUND: To evaluate the analgesic effect of diclofenac in patients undergoing IVI. DESIGN: Single-centre, prospective, randomized, triple-arm, placebo-controlled, interventional study in the University Hospital of Patras. PARTICIPANTS: Seventy-four patients. METHODS: Group 1 (n = 25) received topical diclofenac 45 min before IVI, Group 2 (n = 25) received oral diclofenac 4 h before IVI and topical diclofenac while Group 3 (n = 24) received placebo before IVI. Using the short form of the McGill Pain Questionnaire (SF-MPQ), pain intensity was assessed with the visual analogue scale (VAS), the main component of the SF-MPQ and the Present Pain Intensity (PPI) scores immediately and 6 h post-IVI. MAIN OUTCOME MEASURES: The VAS pain score immediately post-IVI. RESULTS: Immediately post-IVI, patients in Group 2 reported significantly lower VAS pain scores compared to placebo while no statistically significant difference was found between patients that received topical diclofenac and placebo. Six hours post-IVI, patients in both treatment groups reported significant lower VAS pain scores compared to placebo. The scores of the main component of the SF-MPQ were significantly lower in patients of treatment groups compared to placebo at both time-points. Finally, while no statistically significant difference was found between the 3 Groups in PPI scores immediately post-IVI, 6 h later, patients of both treatment groups reported significantly lower PPI scores compared to placebo. CONCLUSIONS AND RELEVANCE: The combination of topical and oral diclofenac demonstrated better analgesic effect than topical diclofenac administration in patients undergoing IVI immediately and up to 6 h post-IVI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| 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".