Depression during pregnancy: the potential impact of increased risk for fetal aneuploidy on maternal mood
Bibliographic record
Abstract
Depression during pregnancy can have serious consequences for families. Indications of fetal aneuploidy can induce maternal stress, a risk factor for depression. Few studies have assessed symptoms of depression in pregnant women soon after they receive results indicating increased risk for fetal aneuploidy. We compared symptoms of depression in women who had increased risks for fetal aneuploidy with two other groups of pregnant women at similar gestational ages: controls, and women taking antidepressant medications (MEDS). Eighty-one women attending the British Columbia (BC) Medical Genetics (MG) Program regarding positive maternal serum screens or ultrasound soft marker findings completed the Edinburgh Postnatal Depression Scale (EPDS). Control (n = 41) and MEDS (n = 41) groups were recruited from the community or the BC Reproductive Mental Health program. A threshold score of 12 on the EPDS was used to calculate percentages of women likely to be depressed. Mean EPDS scores were compared using anova, followed by post-hoc tests. In the control, MG, and MEDS groups, 2.4%, 35%, and 52.4% of women, respectively, scored above 12. Mean EPDS score was significantly higher in the MG group than in the control group (p < 0.0001). These results suggest a place for depression screening in prenatal genetic counseling.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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".