<p>Is Cabergoline Safe and Effective for Postpartum Lactation Inhibition? A Systematic Review</p>
Bibliographic record
Abstract
BACKGROUND: Despite its benefits, there are some situations where breastfeeding is impossible or not recommended. Breast milk secretion and engorgement can be distressing to these non-breastfeeding women. There is currently no universal guideline on the most appropriate management for these women. Our objective is to evaluate the effectiveness and safety of cabergoline, a dopamine agonist, in lactation inhibition in postpartum women. METHODS: Studies were identified through electronic database searching (Cochrane library, EMBASE, Medline, IPA and Scopus) to identify all relevant studies that evaluated the use of cabergoline as a lactation inhibitor in postpartum women. Citations were screened and a narrative synthesis was undertaken given the heterogeneity of study designs. RESULTS: A total of six randomized trials met the inclusion criteria. Majority of the studies recruited healthy postpartum women electing for lactation inhibition for personal reasons. A range of 0.4 mg to 1 mg of cabergoline was given within 0 to 50 hrs of delivery. Dose-response relationship is established, and the highest rate of complete success was achieved with 1 mg of cabergoline, with time to cessation between 0 and 1 day. Cabergoline is non-inferior to bromocriptine for lactation inhibition while also associated with fewer rebound symptoms and adverse effects. Commonly reported adverse effects of cabergoline (eg, dizziness, headache and nausea) are self-limited. CONCLUSION: Cabergoline is simple, effective and generally safe when given to postpartum women either wishing or needing to suppress lactation. Further research is needed to improve postpartum care of these women.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".