Intracameral lidocaine reduces pain in cataract surgery, but only a little bit
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of intracameral lidocaine during routine cataract surgery. DESIGN: Prospective, single-blinded, randomized, controlled trial. PARTICIPANTS: Adult patients undergoing routine phacoemulsification cataract extraction in a chartered surgical facility in Edmonton, Alberta, Canada, were enrolled in the study. METHODS: Patients were randomized to receive intracameral lidocaine or control (intracameral balanced salt solution). Patients rated their pain at the time of intracameral injection and at the conclusion of the surgery, on a scale from 0 to 10. RESULTS: The study included 106 eyes from 82 patients. The overall pain score was lower (p = 0.004) in the lidocaine group (0.43 ± 0.94/10) than in the control group (0.72 ± 2.79/10). Pain was higher (p = 0.002) in more myopic (1.80 ± 4.04/10) than less myopic patients (0.50 ± 1.67/10). There was no difference in pain experienced at the time of injection (p = 0.270). There was no difference in same-day postoperative logMAR visual acuity (p = 0.837). CONCLUSIONS: Intracameral lidocaine reduces pain during cataract surgery, but the effect is small; it is most effective in myopic patients.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".