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Record W1525446543 · doi:10.3171/ped-07/12/508

Detection of important venous collaterals by computed tomography venogram in multisutural synostosis

2007· article· en· W1525446543 on OpenAlexaff
Merdas Al-Otibi, Andrew Jea, Abhaya V. Kulkarni

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineCraniosynostosisRadiologyHydrocephalusDecompressionSyrinx (medicine)VenographyComputed tomographyShuntingIntracranial pressureShunt (medical)SurgeryMagnetic resonance imagingThrombosisSyringomyelia

Abstract

fetched live from OpenAlex

The authors describe the novel use of computed tomography (CT) venography in the preoperative evaluation of a child with Crouzon syndrome who was being considered for Chiari decompression. This 18-month-old girl presented with hydrocephalus (treated with a ventriculoperitoneal shunt) and persistent symptomatic Chiari malformation and associated syrinx. A CT venogram was obtained because of the well-described relationship between multisutural craniosynostosis and abnormal intracranial-to-extracranial venous drainage. The CT venogram showed widely dilated vertebral and paravertebral veins located in the paraspinous muscles of the craniocervical junction. Because of the risk of massive intraoperative blood loss and/or occlusion of important collateral draining veins leading to intracranial venous hypertension and intractably raised intracranial pressure, the planned posterior fossa decompression was not performed. Computed tomography venography is an easily obtained study that we recommend in the evaluation of children with multisutural craniosynostosis prior to cranial surgical interventions.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.006
GPT teacher head0.233
Teacher spread0.227 · 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 designObservational
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

Citations26
Published2007
Admission routes1
Has abstractyes

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