The efficacy of zuranolone in postpartum depression and major depressive disorder: a review & number needed to treat (NNT) analysis
Bibliographic record
Abstract
Introduction Major depressive disorder (MDD) is a common and debilitating mental illness. Postpartum depression (PPD) impacts women globally and is one of the most common complications of childbirth that is underdiagnosed and undertreated, adversely impacting the mental health of women, children, and partners.Available antidepressant medications require weeks to months before showing effect. In this setting, zuranolone, an oral neuroactive steroid and a positive allosteric modulator of GABAA receptors, is an attractive alternative as a rapid-acting antidepressant treatment.Areas covered This article reviews zuranolone (SAGE217), focusing on available clinical studies in individuals with PPD and MDD. This paper adds to the extant literature by presenting the efficacy data as Number Needed to Treat (NNT) to facilitate indirect comparisons with other antidepressants.Expert opinion Zuranolone is a novel rapid-acting (i.e. two week course) oral antidepressant for the treatment of adults with PPD with ongoing clinical trials evaluating its efficacy in adults with MDD. Zuranolone is well tolerated with no significant safety concerns in any clinical trials completed to date. Zuranolone will be scheduled by the Drug Enforcement Agency (DEA).
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".