Comparison of pain perception in immediate vs delayed sequential bilateral cataract surgery
Bibliographic record
Abstract
PURPOSE: To compare patient-reported pain perception between immediate sequential vs delayed sequential bilateral cataract surgery (ISBCS vs DSBCS). SETTING: King Chulalongkorn Memorial Hospital, Bangkok, Thailand. DESIGN: Prospective cohort study. METHODS: Eligible participants scheduled to undergo ISBCS and DSBCS were consecutively enrolled. Topical anesthesia was administered for all procedures with no sedation used. Pain scores for each eye were assessed separately at 3 timepoints: immediately after surgery, day 1, and day 7 postoperation, using a verbal numeric rating scale from 0 to 10. A linear mixed-effects model was used to analyze the differences in pain scores between the 2 groups and adjusted for covariates, including surgical method, timepoint, operated eye, education level, surgeon experience, and surgical duration. RESULTS: 90 bilateral cataract patients (45 ISBCS and 45 DSBCS) were enrolled. Pain scores on day 0 were low, with medians of 1 (0; 2) for both groups ( P = .476). The linear mixed-effects model revealed no significant impact of surgical methods on pain scores, with a notable decrease in pain levels over time. Surgical duration significantly affected pain, with each minute adding approximately 0.027 to the score. In addition, patients with higher education levels reported higher pain scores. CONCLUSIONS: Pain related to cataract surgery was mild and resolved quickly in both ISBCS and DSBCS groups, with no significant differences between surgical methods and operated eyes. The effect of education level on pain perception suggests the importance of good preoperative counseling to set appropriate expectations.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".