Hemorrhagic hepatic infarction in a pregnant woman with severe pre-eclampsia: a case report
Bibliographic record
Abstract
Introduction and importance: Severe pre-eclampsia is a medical condition that affects women during the last two trimesters of pregnancy. Hemorrhagic hepatic infarction is a hepatic complication and is rarely encountered in women with severe pre-eclampsia. This case report aims to present the characteristics of hemorrhagic hepatic infarction in a pregnant woman with severe pre-eclampsia. Case presentation: A 27-year-old pregnant woman with a 30-week gestation of amenorrhea was admitted with a blood pressure of 160/100 millimeters of Mercury (mmHg), headaches, dizziness, and oedema in the lower limbs. Clinical discussion: These complaints with clinical and paraclinical examinations led to the diagnosis of severe pre-eclampsia, and she underwent an emergency cesarean section, but 6 h later, she presented with hypovolemic shock, and this led to a new surgery. A surgery that made it possible to develop or discover a diffuse hepatic infarction with hemorrhagic infiltration of the gallbladder and the falciform ligament without active bleeding in the liver. Emergency management of pre-eclampsia was adopted, and the postoperative course was simple, with a good clinical outcome when the patient was discharged. Conclusion: Severe pre-eclampsia and hemorrhagic hepatic infarction are complications of pregnancy, which require emergency treatment, and above all, these medical conditions require the termination of the pregnancy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".