Longitudinal Study of Depression, Anxiety, Irritability, and Stress in Pregnancy Following Evidence-Based Counseling on the Use of Antidepressants
Bibliographic record
Abstract
BACKGROUND: Pregnant women who suffer from clinical depression and use antidepressant medications may receive conflicting information about fetal safety. Little information exists on the effect of continuation of antidepressants on depressive symptoms during pregnancy. OBJECTIVES: To determine the effectiveness of maintaining antidepressants during pregnancy, as measured by changes in symptoms of depression, anxiety, irritability, and stress following reassuring evidence-based counseling. METHODS: Depressed women who were pregnant and taking antidepressants, and who called the Motherisk program for advice, participated in a study that involved reassuring evidence-based counseling on the risk of antidepressants in pregnancy, followed by four telephone interviews: one in each trimester and one in the postpartum period. Depression, anxiety, irritability, and stress scales were completed at each call. RESULTS: Of the 58 women who enrolled in the study, 38 completed 75% of the follow-ups. Eight women (14%) discontinued their medication during the study. Depression scores were highest at enrollment in the first trimester and decreased as pregnancy progressed. When data from all women, regardless of dose adjustments, were analyzed, no statistically significant differences were seen between depression scores at any time point; mean depression scores were below the cut off for depression throughout the study period. Irritability, anxiety, and stress scores were not found to be statistically different at any time point during the study. CONCLUSION: Evidence-based reassurance and continuous antidepressant pharmacotherapy during gestation can provide pregnant women with effective symptom control for their depression. Women should consult their healthcare provider to ensure that they are being treated effectively; a risk/benefit assessment should be conducted on a case-by-case basis.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".