Effect of depressive and anxiety symptoms during pregnancy on risk of obstetric interventions
Bibliographic record
Abstract
AIM: The effect of prenatal mental health on the risk of obstetric interventions is unclear. The present study examined the associations between depressive and anxiety symptoms in the second and third trimesters and mode of delivery, epidural use and labor induction in a large community-based pregnancy cohort, in Alberta, Canada. MATERIAL AND METHODS: Women who had singleton pregnancies, delivered in hospital, and had medical data were selected (n = 2825). Obstetric intervention data were obtained from the medical records, and depressive and anxiety symptoms were measured by the Edinburgh Postnatal Depression Scale and the Spielberger State Anxiety Inventory. Data were evaluated with multivariate multinomial and logistic regression analyses using a hierarchical modeling. RESULTS: After accounting for factors known to increase the risk of each intervention, including demographic variables, smoking, hospital site, gestational age, previous history of cesarean delivery, prepregnancy body mass index, assisted conception, and antepartum risk score, the only mental health variable associated with obstetric interventions was depressive symptoms in the third trimester, which increased the risk of emergency cesarean delivery (adjusted odds ratio, 2.04; 95% confidence interval, 1.26-3.29). No associations were found between antenatal depressive and anxiety symptoms and other obstetric interventions. CONCLUSION: The present findings support an association between depressive symptoms and adverse obstetric outcomes and suggest that anxiety and depression may have different effects on obstetric outcomes. Understanding the mechanism in which depression increases the risk of emergency cesarean birth needs further research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".