Should we target insomnia to treat and prevent postpartum depression?
Bibliographic record
Abstract
Postpartum depression (PPD) is a major public health problem that affects approximately 12-18% of women and is associated adverse maternal and infant outcome. Given that untreated maternal depression has negative consequences for both the mother and her child, it is important to deploy effective measures to treat or prevent PPD. Antidepressant treatment after delivery has been proposed for prophylaxis, however, this is not firmly established. Since insomnia is an early sign and a common symptom of PPD in this contribution we argue that management of insomnia may play a key role in the treatment and prevention of PPD. To this aim we by discussed the current evidence about the potential prophylactic role of antidepressants compared to that of insomnia treatment in PPD. We concluded that insomnia symptoms may be a better therapeutic target to prevent or treat PPD which is heterogeneous entity and may be more responsive to interventions addressing a common and early symptom such as insomnia.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".