Anterior chamber cytokine production and postoperative macular edema in patients with diabetes undergoing FLACS
Bibliographic record
Abstract
PURPOSE: To evaluate the effect of femtosecond laser-assisted cataract surgery (FLACS) and manual cataract surgery (MCS) on proinflammatory cytokine expression in patients with diabetes vs nondiabetic patients. SETTING: Outpatient surgical center in Vaughan, Ontario, Canada. DESIGN: Prospective cohort study. METHODS: Patients with diabetes and nondiabetic patients undergoing noncomplicated MCS or FLACS were assigned into 4 cohorts: MCS nondiabetic (n = 30), FLACS nondiabetic (n = 42), MCS diabetic (n = 40), and FLACS diabetic (n = 40). Aqueous humor inflammatory mediator concentrations were evaluated at MCS onset and after femtosecond laser treatment. The presence of cystoid macular edema, anterior chamber (AC) inflammation, central retinal thickness, macular volume, and retinal microvascular changes (through optical coherence tomography angiography) were evaluated preoperatively and on postoperative day 1, week 1, month 1 (POM1), and month 3 (POM3). RESULTS: Patients with diabetes receiving FLACS had a higher concentration of interleukin (IL)-7, IL-13, and interferon-induced protein-10 than MCS diabetic patients; they also demonstrated higher levels of vascular endothelial growth factor and lower levels of interferon (IFN)-γ, granulocyte colony-stimulating factor, and IFN-α2 compared with MCS nondiabetic patients. Macular volume appeared to be significantly higher in MCS diabetic vs MCS non-diabetic patients at POM1 and between FLACS diabetic vs FLACS nondiabetic patients at POM3. There were no other significant differences between the cohorts for any parameter. CONCLUSIONS: FLACS use in patients with diabetes demonstrated some differences in AC cytokine expression compared with non-diabetic FLACS or diabetic patients undergoing MCS; however, there was no increase in clinical inflammatory biomarkers. FLACS seems to be a safe technique to use in patients with diabetes.
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How this classification was reachedexpand
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".