Predictors of Early Postoperative Pain After Photorefractive Keratectomy
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: To compare the profiles of postoperative photorefractive keratectomy (PRK) pain between both eyes under the same conditions and to verify the preoperative predictors of pain such as gender, anxiety, knowledge of the procedure, and spherical equivalent refractive error (SERE). METHODS: This prospective study included 86 eyes of 43 patients with myopia who underwent PRK in both eyes at an interval of 14 days between the procedures. Before surgery, subjects answered the State Anxiety Inventory. After surgery, usual PRK pain treatment was given. Subjects answered the Visual Analog Scale, the Brief Pain Inventory (BPI), and the McGill Pain Questionnaire at 1, 24, 48, 72, and 96 hours after surgery. Pain scores and anxiety were compared between each eye using the Wald test and paired Student t test, respectively. The Wald test was performed for gender and SERE for each eye separately. RESULTS: There were no statistically significant differences between both eyes for all time points regarding the Visual Analog Scale, BPI, and McGill Pain Questionnaire-Pain Rating Index pain scores. Subjects were less anxious on average before the second surgery compared with before the first surgery (P < 0.001); however, it was not related to pain ratings after surgery. Gender did not significantly affect any scale of pain, and the SERE between -3 diopters (D) and -5 D (P = 0.035) revealed effects on the BPI. CONCLUSIONS: The profiles of postoperative pain after PRK were similar between both eyes under the same conditions. In this study, a high SERE was the only predictor for increased pain after PRK.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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 it