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Record W2616692176 · doi:10.1055/s-0037-1603454

Lingual Artery Pseudoaneurysm after Severe Facial Trauma

2017· article· en· W2616692176 on OpenAlexaff
Leyre Margallo, Estibaliz Ortiz de Zárate, María Guadalupe Franco, María García-Iruretagoyena, Rosa Cherro, Luis Barbier Herrero, Josu Mendiola, Thomas Constantinescu

Bibliographic record

VenueCraniomaxillofacial Trauma & Reconstruction · 2017
Typearticle
Languageen
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsHumber River Regional Hospital
Fundersnot available
KeywordsMedicinePseudoaneurysmSurgeryFacial traumaAirwayAngiographyComplicationOsteosynthesis

Abstract

fetched live from OpenAlex

The mortality associated with high-energy trauma has several time peaks and variable prognosis. In the particular case of isolated head and neck trauma, management initially includes stabilizing the patient, especially the airway and circulation, and then proceeding to treat injured structures with debridement and often fracture fixation and coverage. We present a case of a male patient who suffered a severe facial trauma at his workplace. He underwent an initial uneventful emergency surgery for control of bleeding and mandibular osteosynthesis. At 2 weeks postoperatively, a second emergency surgery was required to treat a previously undiagnosed lingual pseudoaneurysm that ruptured spontaneously, with massive oral bleeding. The case highlights the clinical significance and timing of pseudoaneurysm formation, and the surveillance and high index of suspicion required for potentially life-threatening bleeding at later time peaks. Diagnostic and therapeutic angiography effectively treated the late complication. Multidisciplinary management options are reviewed, emphasizing the need for rapid decision making and collaboration to improve outcomes in such significant surgical trauma patients.

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)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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