Placental Pathways: A Case Report on Buprenorphine-Naloxone for Opioid Use Disorder and Placental Pathology
Bibliographic record
Abstract
Opioid use disorder (OUD) during pregnancy is a growing public health concern, and the use of medications for opioid use disorder (MOUD), such as buprenorphine, has become standard for managing OUD to improve maternal and neonatal outcomes. We present the case of a 34-year-old gravida six, para five woman at 38 weeks and 3 days of gestation, treated with buprenorphine, who was admitted for labor induction due to preeclampsia without severe features. The patient had a history of polysubstance use disorder in remission, psychiatric comorbidities, and known placental anomalies, including a two-vessel cord, velamentous cord insertion, and accessory lobe. Following an uncomplicated vaginal delivery, the patient experienced postpartum hemorrhage due to retained placental tissue, requiring medical management and blood transfusion. Pathological examination of the placenta revealed abnormalities consistent with prior literature on opioid exposure during pregnancy. This case is unique in that it highlights the histopathologic impact of long-term opioid exposure and MOUD on placental health, including macroscopic findings of abnormal cord insertion and accessory lobe. We then discuss current literature related to MOUD and placental pathology. Learning points from this case include the need for heightened clinical vigilance in pregnancies involving OUD, MOUD, and the potential effects on placental morphology.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".