Changes in Aqueous Cytokine Levels Following Intravitreal Aflibercept in Treatment-Naive Patients with Diabetic Macular Edema
Bibliographic record
Abstract
Purpose: To investigate the changes in aqueous humor cytokine levels in response to short-term aflibercept therapy in treatment-naive patients with center-involving diabetic macular edema (DME). Methods: This is a prospective cohort study that included patients with treatment-naive DME with central subfield macular thickness ≥310 μm on optical coherence tomography from July 2015 to May 2017. Patients received 3 monthly intravitreal aflibercept injections. Aqueous samples for cytokine analysis were obtained before the first and third injections. Levels of various cytokines were measured using multiplex immunoassay. Main outcome measures were changes in aqueous cytokine levels from baseline to month 2. Results: A total of 17 patients were enrolled and 16 completed the study. The mean age was 57.2 ± 8.1 years. The following cytokines were significantly higher at month 2 versus baseline: transforming growth factor-beta (TGF-β)1 ( P = 0.004), TGF-β2 ( P = 0.017), inducible protein (IP)-10 ( P = 0.011), and hepatocyte growth factor (HGF) ( P = 0.02). There were significant reductions in the levels of vascular endothelial growth factor (VEGF) ( P < 0.001), placental growth factor (PlGF) ( P = 0.028), interleukin (IL)-6 ( P = 0.011), and platelet-derived growth factor-AA (PDGF-AA) ( P = 0.003). Conclusions: In treatment-naive patients with DME, short-term aflibercept therapy not only results in VEGF and PlGF suppression, but also leads to reduced levels of IL-6 and PDGF-AA and higher concentrations of TGF-β1, TGF-β2, HGF, and IP-10.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".