PREGNANCY DISORDERS AND MATERNAL CONSEQUENCES: Postpartum mental health after medically complicated pregnancy
Bibliographic record
Abstract
In brief: Pregnancy complications such as hypertensive disorders, gestational diabetes mellitus, and anaemia may increase the risk of postpartum mental disorders, especially depression; however, the evidence for anxiety and posttraumatic stress disorder is limited. Women with medical complications in pregnancy should be considered at high risk for mental disorders and receive appropriate and timely screening and follow-up. Abstract: Mental health is a crucial aspect of overall well-being. The postpartum period is a vulnerable time for women's mental health, with poor mental health potentially impacting the long-term health of mothers and their children. Common postpartum mental disorders include depression, anxiety, and posttraumatic stress disorder (PTSD). Medical complications during pregnancy, such as hypertensive disorders of pregnancy (HDP), gestational diabetes mellitus (GDM), and anaemia, are prevalent and can make pregnancy, childbirth, and the postpartum periods particularly challenging, sometimes resulting in life-threatening situations for the mother and/or her baby. It is therefore plausible that women who experience a pregnancy complication may be at increased risk of also experiencing a postpartum mental health disorder. Published research indicates that HDP, GDM, and gestational anaemia may increase the risk of postpartum depression (PPD). There may be associations between a higher risk of anxiety and PTSD, but the evidence is unclear or under-researched. Postpartum mental health care is often neglected following medically complicated pregnancies, with a focus primarily on physical recovery. There are limited global guidelines addressing mental health care for mothers and their children, but growing recognition of the connection between medical complications and postpartum mental health has led to the development of some follow-up guidelines. Research is necessary to better understand postpartum mental health in women with medical complications during pregnancy. Until more is known, all pregnant women with medical complications should be considered at high risk for postpartum mental disorders and receive appropriate follow-up care.
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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".