The Challenge of Blunt Abdominal Trauma in Children: Report of a Case and Review of Management
Bibliographic record
Abstract
Blunt abdominal trauma is the most frequent cause of abdominal injuries in children. The term solid organ injury (SOI) is referred to liver, spleen and kidney. Splenic injuries are the most common. The management of SOI has been motive of discussion for years and has undergone a radical shift in the last decades. Currently, non-operative management is the gold standard of care when circumstances are favorable. In 1977, non-operative management was supported by surgeons in Toronto. Later, the American Pediatric Surgical Association (APSA) pointed that management should be based on imaging findings and CT grading of the American Association for the Surgery of Trauma. However, this caused long stays and unnecessary follow-up imaging. Soon, APSA guidelines were questioned and raised controversy. Finally, hemodynamic status was defined as the main key for taking decisions and ATOMAC guidelines gained support. However, facing a blunt trauma in children is always a challenge. Hemodynamic stability is not easy to define and heart rate and blood pulse are poor markers for stability. This complicates the management of blunt trauma in children. As consequence, it is important that these children are treated in pediatric centers. We report a case of a 15-year-old male who suffered from a blunt abdominal trauma with splenic and renal injuries treated by adult surgeons when playing football. We review the current recommendations for blunt abdominal trauma in children and the differences with adult management. J Med Cases. 2017;8(11):340-346 doi: https://doi.org/10.14740/jmc2901w
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| 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".