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Record W4246943000 · doi:10.14740/jmc2901w

The Challenge of Blunt Abdominal Trauma in Children: Report of a Case and Review of Management

2017· article· en· W4246943000 on OpenAlexvenueaboutno aff
Ana Minaya‐Bravo, Hector Aguado-Lopez

Bibliographic record

VenueJournal of Medical Cases · 2017
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBluntAbdominal traumaGrading (engineering)SurgeryBlunt traumaGeneral surgeryIntensive care medicine

Abstract

fetched live from OpenAlex

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

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.292

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.368
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2017
Admission routes2
Has abstractyes

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