Fibromyalgia and LASIK: outcomes, complication rates, and ocular pain risk
Bibliographic record
Abstract
PURPOSE: To compare post-laser in situ keratomileusis (LASIK) complications and self-reported ocular pain in patients with fibromyalgia (FM) vs healthy controls. SETTING: Multisurgeon multicenter standardized protocol practice. DESIGN: Retrospective case-control series. METHODS: 1148 eyes from 574 patients with confirmed FM and 54 104 eyes from healthy controls were included. Main outcome measures were incidence of postoperative complications, dry eye (punctate epithelial erosions [PEEs] grade ≥ 2), and self-reported ocular pain. Secondary outcomes included visual and refractive outcomes. RESULTS: The median time since surgery was 6 years (range: 3 to 13 years). FM incidence in the study population was 0.25% (1 in 400 patients). Postoperative dry eye incidence (PEE grade ≥ 2) was 0.61% in FM eyes vs 0.37% in controls ( P = .3). Self-reported postoperative pain occurred in 0.97% of FM eyes vs 0.75% of controls ( P = .4). Postoperative complications occurred in 2.00% of FM eyes and 2.35% of controls ( P = .4), with no cases of postoperative corneal neuralgia in patients with FM. Visual outcomes showed good efficacy, with 83% of FM eyes achieving 20/20 uncorrected distance visual acuity monocularly. The safety index was 0.99, with 95% of FM eyes maintaining or improving preoperative corrected distance visual acuity, consistent with controls. CONCLUSIONS: FM was not associated with an increased risk of self-reported pain or post-LASIK corneal neuralgia. Refractive and visual outcomes, as well as postoperative complications, were comparable with non-FM patients. These findings suggest that a preoperative history of FM alone should not be considered an absolute contraindication for LASIK.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".