The influences of hyperprolactinemia and obesity on cardiovascular risk markers: effects of cabergoline therapy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: In view of the association of hyperprolactinaemia with insulin resistance, we hypothesized that patients with hyperprolactinaemia may present increased cardiovascular risk markers. DESIGN: Descriptive clinical trial. METHODS: Serum glucose, insulin, insulin resistance, lipids, high sensitivity C-reactive protein (hsCRP), interleukin (IL)-6, tumour necrosis factor (TNF)-alpha and soluble E-selectin (sELAM-1) serum levels were determined in 15 patients with hyperprolactinaemia at baseline (compared with 20 healthy subjects) and after 12 weeks of cabergoline therapy (0.5-1 mg twice per week). We also measured mononuclear cell NF-kappaB activation and TNF-alpha production in a subset of subjects. RESULTS: Serum levels of prolactin (PRL), insulin, insulin resistance (HOMA-IR) index and hsCRP were significantly higher in patients than in control subjects. Markers of mononuclear cell activation did not differ between the groups. Hyperprolactinaemia, BMI and age were predictors of hsCRP. BMI was the only predictor of HOMA-IR. Cabergoline therapy significantly reduced serum PRL, insulin, hsCRP and sELAM-1 levels. CONCLUSIONS: These data suggest that hyperprolactinaemia is associated with insulin resistance related to increased BMI and low-grade inflammation independently of BMI. Short-term cabergoline therapy can reduce the inflammatory markers.
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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 it