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Republished: Pipeline embolization device induced collateral channels in elective flow diversion treatment

2016· article· en· W3005702039 on OpenAlexaff
Yingming Amy Chen, Brian Drake, Albert Chiu, Thomas R. Marotta

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineEmbolizationAneurysmRadiologyAngiographyOcclusionCerebral angiographyThrombosisFusiform AneurysmEndovascular treatmentMiddle cerebral arterySurgeryCardiologyIschemia

Abstract

fetched live from OpenAlex

The pipeline embolization device (PED) is a well recognized treatment for intracranial aneurysms. However, uncertainty remains regarding its effects on flow alteration, which is particularly highlighted by persistently perfused aneurysmal remnants and non-regressing, non-perfused aneurysmal masses. Here we present a 68-year-old woman with an incidental giant fusiform right paraophthalmic aneurysm electively treated with a PED. After lowering her antiplatelet therapy to promote aneurysm thrombosis, she was found to have a progressively enlarging perfused aneurysmal remnant. Angiography revealed PED occlusion, but curiously the development of a peri-construct collateral channel which feeds the aneurysmal remnant, and gives rise to distal branches and contributes to middle cerebral artery flow. The large ‘thrombosed’ aneurysmal mass showed tiny internal vessels on cone beam CT angiography as well as florid enhancement on MRI, further confirming that apparently thrombosed remnants are biologically active and may be remodeled depending on flow demand.

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 score0.269
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.047
GPT teacher head0.292
Teacher spread0.245 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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