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Record W2945700545 · doi:10.1016/j.tcr.2019.100206

Motor vehicle collision with seatbelt sign and traumatic abdominal wall hernia should raise suspicion for hollow viscus injury

2019· article· en· W2945700545 on OpenAlexaff
Michael A. D’Elia, R. Ian Grant, Nicole Kolozsvari, Maher Matar

Bibliographic record

VenueTrauma Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicAbdominal Trauma and Injuries
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineMotor vehicle crashSurgeryHerniaComputed tomographyRadiologySign (mathematics)Poison controlInjury preventionMedical emergency

Abstract

fetched live from OpenAlex

Diagnosing hollow viscus injury following motor vehicle collision (MVC) requires a high index of suspicion. Here we present two cases of high velocity MVC, with 3-point restrained occupants, who presented with a seatbelt sign and associated acute traumatic flank herniation. Both patients underwent a computer tomography (CT) scan which did not identify any hollow viscus injuries. Significant injuries were ultimately identified in the operating room (OR). The presence of a seatbelt sign and underlying acute traumatic hernia should prompt a heightened level of suspicion for intra-abdominal injury, particularly hollow viscus. A heightened level of suspision and a lower threshold for operative exploration is suggested to avoid the morbidity and mortality associated with a delayed diagnosis of hollow viscus injury.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.027
GPT teacher head0.300
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2019
Admission routes1
Has abstractyes

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