The role of hormone therapy in the management of severe postpartum depression in patients with Turner syndrome
Bibliographic record
Abstract
OBJECTIVE: Premature ovarian failure associated with Turner syndrome presents clinicians with a vast range of health concerns, including infertility, cardiovascular disease, and decreased bone mineral density, in addition to psychological sequelae. Hormone therapy is paramount in managing these complications, but the additional needs in the postpartum period for those who are able to carry out a successful pregnancy have not been described. METHODS: We present a case of severe postpartum depression (PPD) with psychotic features in a patient with Turner syndrome, which presented at 4 weeks after the birth of her first child via egg donation RESULTS:: We describe the case of a previously well 32-year-old patient with an 46 X, i(Xq) karyotype, who went through a 4-week intensive inpatient treatment course for PPD, requiring electroconvulsant therapy for persistent infanticidal and suicidal ideation. It was hypothesized that an estrogen-depleted state secondary to premature ovarian insufficiency and lactation may have been more pronounced during her postpartum course when hormone levels dramatically decrease. To buffer the dramatic drop in sex steroid levels postpartum for her second pregnancy, she was immediately started on estrogen and progesterone replacement, and did not experience any change in mood or similar psychiatric disturbance during this postpartum course. Four years after the PPD episode, her mood remains stable. CONCLUSION: This case highlights the complex interplay between ovarian steroids, depletion of their levels, and psychiatric sequelae. The postpartum period represents a particularly vulnerable time for patients with premature ovarian insufficiency, which requires very close monitoring and early replacement of depleted hormone levels.
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 | 0.000 | 0.001 |
| 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".