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Record W4205184374 · doi:10.1017/cjn.2021.391

P.115 Vessel Wall Imaging of Unusual Childhood Strokes: a Pediatric Case Series

2021· article· en· W4205184374 on OpenAlexaffvenue
FF Albassam, Prakash Muthusami, Nomazulu Dlamini

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2021
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsToronto Public HealthSystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsMedicineRadiologyStroke (engine)Magnetic resonance imagingMagnetic resonance angiographyAngiography

Abstract

fetched live from OpenAlex

Background: MR-based vessel wall imaging (VWI) has gained influence in the clinical investigations, and management of pediatric strokes. Limitations still exist in interpreting it as a singular modality. Methods: We present 4 pediatric stroke cases with VWI enhancement. Results: Case 1. 4-year old boy with sickle cell anemia, who developed encephalopathy during a hemolytic crisis. MR-VWI revealed bilateral extracranial internal carotid enhanced narrowing, deemed a secondary vasculopathy, with resolution upon follow-up. Case 2. 16-year old male presented with left middle cerebral artery (MCA) infarction. VWI revealed left internal carotid terminus and proximal MCA enhancement. Conventional angiography showed abnormalities in mesentric and hepatic arteries. Stability sustained on anticoagulation and immunosuppressive therapy. Case 3. 10-year old girl, developed bilateral MCA infarctions with enhanced extracranial segments of both ICAs, and narrow PCAs, consistent with Moyamoya vasculopathy. Improved on combined immunosuppressive and anticoagulation therapy. Case 4. 13-year old boy had an episode of right facial weakness, with a normal neurological exam; with enhancement and narrowing in the left extracranial ICA, likely an intramural hematoma from dissection. He responded to dual anticoagulation therapy. Conclusions: In conclusion, these cases illustrate similarities in vessel wall imaging abnormalities under different clinical contexts, with practical utility in longitudinal follow-up and prognostication.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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