Levels of vascular endothelial growth factor (VEGF) in serum of patients with endometriosis
Bibliographic record
Abstract
BACKGROUND: Elevated concentrations of vascular endothelial growth factor (VEGF) have been detected in the peritoneal fluid of patients with endometriosis. Furthermore, it was postulated that VEGF is involved in the development of endometriotic lesions. The present study is aimed at determining whether high levels of VEGF could also be found in the serum of patients with endometriosis. METHODS: VEGF levels were measured by enzyme-linked immunosorbent assay (ELISA) in serum from 131 subjects with surgically confirmed endometriosis and 146 controls with no clinical evidence of the disease or detectable endometriotic lesions at the time of surgical examination. Parameters such as demographics, personal habits, menstrual characteristics and clinical profile were collected from each subject included in this study. RESULTS: The mean VEGF levels were not significantly modulated in serum samples of cases compared with controls in a crude general linear model and in a model adjusted for possible confounders. VEGF serum levels did not correlate with the score, stage of endometriosis or the presence of benign gynaecological disorders. However, a correlation was found between circulating concentrations of VEGF and body mass index. CONCLUSION: Although VEGF seems to play a pivotal role locally in the implantation and development of endometriotic lesions, the disease is not associated with a significant modulation in the levels of circulating VEGF.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".