Cabergoline therapy for prolactinomas: is valvular heart disease a real safety concern?
Bibliographic record
Abstract
Dopamine agonists (DAs) are the first-line therapy for the treatment of hyperprolactinemia, with cabergoline, an ergot-derived selective D(2)-receptor agonist, being the preferred and most widely used drug. Recent studies reported cardiac valve regurgitations in patients with Parkinson's disease treated with high doses of DA, raising concerns about the safety of cabergoline in patients with hyperprolactinemia. To date, seven case-control studies have examined the potential association between cardiac valvular abnormalities and cabergoline therapy in patients with hyperprolactinemia. Overall, a total of 463 patients exposed to low doses of cabergoline (mean cumulative doses: 204-443 mg) for a mean duration of 45-79 months have been included in these studies. Patients in all the studies were asymptomatic without clinical signs of cardiac disease. Six studies did not show any association between cabergoline therapy and clinically relevant valvular regurgitation, whereas one study found an increased rate of moderate tricuspid regurgitation. In this report, we review and discuss the results of these studies and emphasize the limitations of the methodology used in the published literature. The clinical significance of the present findings has yet to be confirmed by future larger prospective studies with rigorous echocardiographic protocols and prolonged duration of follow-up.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| 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".