The Importance of a Late First Trimester Placental Sonogram in Patients at Risk of Abnormal Placentation
Bibliographic record
Abstract
Background. Placenta accreta is a potentially life-threatening obstetrical condition and is responsible for many emergency Caesarean hysterectomies. Early prenatal diagnosis may help minimize maternal morbidity and mortality. This report highlights risk factors, early diagnostic findings and complications associated with placenta accreta, and the role of first trimester sonography in diagnosis. Case. A 38-year-old pregnant woman, G2P1L1 with history of one previous Caesarean section, presented with vaginal bleeding at 13 weeks' gestation. Ultrasound examination was highly suspicious of placenta previa with accreta. During an earlier 12-week scan for nuchal translucency measurement, the placenta was suboptimally visualized. She was counselled regarding potential maternal and fetal complications as well as management options. At 33 weeks' gestation Caesarean hysterectomy was performed due to vaginal bleeding. Conclusion. Early ultrasound screening in high-risk patients may be advantageous in order to identify placenta accreta and conduct appropriate patient counseling regarding risks and management options.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".