A CASE REPORT OF A LOW-BIRTH-WEIGHT INFANT WITH A SUBCAPSULAR LIVER HEMATOMA AND SPONTANEOUS BOWEL PERFORATION
Bibliographic record
Abstract
This case report describes a 27-week, 1040-g infant, whose mother presented with an acute abruption and fetal distress prompting emergency cesarean birth. The birth was further complicated by fetal malposition, manual version, birth trauma, and perinatal depression requiring intubation, ventilation, and chest compressions. On day of life (DOL) 7, the infant suddenly deteriorated with cardiovascular collapse and severe coagulopathy. Coexisting spontaneous bowel perforation (SBP) and ruptured subcapsular liver hematoma (SLH) were confirmed operatively. Although survival with ruptured SLH is rarely reported, with aggressive medical and surgical management, this infant survived and was discharged home at 43 weeks postconceptual age. SBP may occur silently; pneumoperitoneum may be an incidental finding. Conversely, rupture of an SLH typically presents with a sudden clinical deterioration. The common predisposing factor for both conditions is low birth weight (LBW). A review of the known and proposed risk factors, clinical signs and symptoms, pathophysiology, and treatment of both SBP and SLH are provided. A literature review highlighting the potential impact of drug exposures (indomethacin, hydrocortisone, and low molecular weight heparin) is provided, along with a discussion of the implications for clinical practice and research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".