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Record W4283381447 · doi:10.1017/cjn.2022.240

P.158 Middle meningeal embolization for pediatric chronic subdural hematoma

2022· article· en· W4283381447 on OpenAlexaffvenue
A Ajisebutu

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldMedicine
TopicNeurosurgical Procedures and Complications
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsMedicineMiddle meningeal arteryEmbolizationSurgeryChronic subdural hematomaMiddle cerebral arteryRadiologyHematomaInternal medicine

Abstract

fetched live from OpenAlex

Background: Chronic subdural hematoma (CSDH), although common in the adult and geriatric populations, is a relatively rare condition in pediatric patients. Middle meningeal artery (MMA) embolization is a novel adjuvant endovascular procedure used to minimize the risk of recurrence of CSDH, and its use in pediatric populations is exceptionally rare. Methods: This is a case-report and review of the available literature. Results: A 14 year old male presented to the children hospital after an episode of dysarthria, word-finding aphasia and subtle right sided weakness. MRI revealed a CSDH left cerebral hemisphere with evidence of septations and an arachnoid cyst in the left middle cranial fossa. The patient underwent surgical drainage of the CSDH and subsequent MMA embolization. The patient made an excellent functional recovery with complete resolution of CSDH. Conclusions: Here we report our experience with MMA embolization as an adjuvant therapy for the treatment of a pediatric CSDH. We have found that MMA embolization provides a safe adjuvant therapy in the treatment of CSDH in the pediatric population, lending support to the limited literature of the utility of MMA in this age group. We propose that MMA embolization is safe and potentially efficatious in reducing risk of recurrence in pediatric complex, multi-loculated CSDHs

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.049
GPT teacher head0.286
Teacher spread0.237 · 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 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

Citations0
Published2022
Admission routes2
Has abstractyes

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