Systemic absorption of mitomycin-C when used in refractive surgery
Bibliographic record
Abstract
PURPOSE: To determine whether corneal topical application of mitomycin-C (MMC) results in measurable plasma levels of systemic absorption. SETTING: Madigan Army Medical Center, Refractive Surgery Center, Fort Lewis, Washington, and Micro-Constants Laboratory, San Diego, California, USA. DESIGN: Case-control study. METHODS: The study comprised male and female active-duty soldiers having excimer laser photorefractive keratectomy with MMC. Patients who met inclusion criteria were asked to provide a blood sample immediately after being treated with MMC 0.2 mg/mL (0.02%) for 30 seconds. Human plasma samples were evaluated by liquid chromatography mass spectrometry to determine whether MMC was present. RESULTS: Thirty samples were submitted for evaluation. There was zero detection of MMC in the submitted samples. The quantifiable limit was greater than 10.0 ng/mL. All samples were below this. CONCLUSIONS: In this study of 30 patients with topical application of MMC for refractive surgery, there was no measurable evidence of systemic absorption. Although systemic absorption has been found with use in larger quantities, it was not known whether MMC toxicity concerns could be extrapolated to the refractive surgery population. This information allows counseling of patients on the extremely low likelihood of systemic absorption or toxicity following current techniques for refractive surgery. FINANCIAL DISCLOSURE: No author has a financial or proprietary interest in any material or method mentioned.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".