Double masked randomised controlled trial to assess the effectiveness of paracetamol in reducing pain in panretinal photocoagulation
Bibliographic record
Abstract
AIM: To assess the effectiveness of pre-emptive analgesia with paracetamol in reducing pain associated with panretinal photocoagulation (PRP) in a prospective, double masked, randomised controlled trial. METHOD: 60 patients undergoing PRP for the first time were enrolled and randomised to paracetamol or placebo, taken for 2 days starting 24 hours before the laser treatment. The laser treatment was performed following a standardised protocol. Pain during and after treatment was assessed using the McGill pain questionnaire (MPQ) and visual analogue scales (VAS). RESULTS: The statistical analysis looked for differences between the two study groups immediately after the laser surgery and 24 hours later. There was no statistically significant difference in the primary outcome measure of perception of pain during and 24 hours after PRP, between the paracetamol and placebo group. However, none of the patients in the paracetamol group reported increased total pain at 24 hours, whereas six patients in the placebo group reported increased pain; this difference (21%) was significant to p = 0.01. CONCLUSIONS: Pre-emptive analgesia with paracetamol did not significantly reduce pain associated with PRP. This study has described for the first time the type of pain associated with PRP, which is perceived mainly as a discomfort. The main attributes of the pain that patients described, were sharp, flashing, tiring, intense, piercing, intermittent, and brief.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".