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Record W2739204573 · doi:10.1097/pec.0000000000001236

A Rare Pediatric Case of Posttraumatic Pseudoaneurysm

2017· review· en· W2739204573 on OpenAlexaff
Ada Gu, April Kam

Bibliographic record

VenuePediatric Emergency Care · 2017
Typereview
Languageen
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsMcMaster Children's Hospital
Fundersnot available
KeywordsMedicinePseudoaneurysmAsymptomaticRadiologySurgeryEmergency departmentPulsatile flowWristPhysical examinationAneurysmCardiology

Abstract

fetched live from OpenAlex

Posttraumatic pseudoaneurysms are extremely rare in pediatric populations. In many cases, pseudoaneurysms may be confused with abscesses, epidermoid cysts, arteriovenous fistula, foreign objects, and ganglion cysts, as well as tumors. They are associated with distinguishing findings of "pulsatile mass, a palpable thrill, and an audible to-and-fro murmur" (1), which can be confirmed by various imaging techniques. In this report, we describe the case of a 4-year-old boy who presented to the pediatric emergency department 3 weeks after falling and subsequently getting cut by glass. Upon clinical examination, the patient presented with pulsatile, swollen mass in the left wrist. A Doppler ultrasound of the left wrist demonstrated that the area of clinical concern in the left wrist showed a pseudoaneurysm, and prominent arterial blood flow was seen within the pseudoaneurysm. Because pseudoaneurysms, particularly posttraumatic pseudoaneurysms, are extremely rare in the pediatric population, it may be easy to miss these cases during clinical examination. Misdiagnosis of the pseudoaneurysm can cause delayed treatment, a longer recovery period, and complications such as infection, rupture, and hemorrhage. It is important for physicians to consider this entity when evaluating patients with symptoms of asymptomatic bulges to painful pulsatile masses after trauma.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.106
GPT teacher head0.408
Teacher spread0.301 · 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
GenreReview

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 routes1
Has abstractyes

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