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Record W2424158710 · doi:10.1017/cjn.2016.185

P.081 Penetrating brain injury, recent case series of a single institution and literature review

2016· article· en· W2424158710 on OpenAlexvenueno aff
Pascal Lavergne, Myreille D’Astous, Hélène T. Khuong

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2016
Typearticle
Languageen
FieldMedicine
TopicTraumatic Ocular and Foreign Body Injuries
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBluntRadiological weaponTraumatic brain injuryDecompressive craniectomyPresentation (obstetrics)CranioplastySurgeryPolytraumaSkull

Abstract

fetched live from OpenAlex

Background: Penetrating brain injury is a rare entity. Furthermore, clinical presentation can be highly variable and management difficult, especially when the foreign body is retain in the skull Methods: We present a serie of three recent cases of penetrating brain injury that happened at our institutionm including clinical and radiological data. We discuss management of those challenging cases and present a brief review of the literature. Results: Our cases (3) encompassed different mechanisms: bilateral nail gun injury, knife and aircraft propeller. All patients were male, with a median age of 37 years old. Work-up was negative for intracranial vascular injury. All patients were treated with initial craniectomy (bilateral in one case) and a course of antibiotics. Cranioplasty was later performed. All patients survived and evolved in favorable fashion. Conclusions: Penetrating brain injury is a rare injury, requiring individualized surgical and medical management. A few recommendations may be found in the literature but are often based on literature from blunt traumatic brain injury or war-related injuries.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.289
Teacher spread0.251 · 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.

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

Citations0
Published2016
Admission routes1
Has abstractyes

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