Use of extracorporeal membrane oxygenation for pediatric post-traumatic pulmonary hemorrhage: A Case report and literature review
Bibliographic record
Abstract
Chest trauma in children presents unique diagnostic challenges due to physiological and anatomical differences from adults. While pulmonary contusion remains the most common injury, meticulous evaluation with CT scan is crucial to rule out occult pathologies and ensure timely intervention for potential complications like alveolar hemorrhage. Pediatric chest trauma mandates a tailored management approach considering their delicate physiology. Early initiation of high-flow oxygen, judicious ventilatory support for acute respiratory distress, and proactive fluid management are essential, while pain control and hemodynamic monitoring remain critical throughout the recovery process. Here, we report a challenging case of a 6-year-old male child presenting to the Pediatric Emergency Department with acute moderate-to-severe respiratory distress that was successfully treated with extracorporeal membrane oxygenation. The child was brought to our emergency department with only history of mild head trauma that occurred 2 h before presenting to the hospital. After triaging as Canadian Triage and Acuity Scale (CTAS) II, the child was managed in line with acute respiratory distress via ATLS abroach. We ruled out head, cervical spine, and other evidence of invasive chest as well as gross abdominal injuries, by ATLS abroach and adjuncts such as point-of-care ultrasound and chest and abdomen X-rays and PAN CT. Although the initial venous blood gas analyses were suggestive of mixed respiratory an metabolic acidosis, the CXR and the chest CT revealed that the child had significant lung parenchymal injury in the form of bilateral fluffy pulmonary infiltrates. This case indicates that even an uncertain history and absence of physical finding, chest blunt trauma causing lung injury, leading to severe manifestations and sometimes fatal complications such as pulmonary contusion, hemorrhage, and ARDS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".