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Record W4311874303 · doi:10.1186/s12883-022-03022-4

Quantitative indices for an intracranial aneurysm and subarachnoid hemorrhage in early childhood: a case report

2022· article· en· W4311874303 on OpenAlexaboutno aff
Kenichi Tetsuhara, Noriyuki Kaku, Koichi Arimura, Yasunari Sakai, Shouichi Ohga

Bibliographic record

VenueBMC Neurology · 2022
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsSubarachnoid hemorrhageMedicineNeurosurgeryNeurologyNeurochemistryAneurysmRadiologySurgeryPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Intracranial aneurysms (ICA) rarely occur in children under 3 years of age. Little is known for neuroimaging parameters that predict survival and clinical outcomes of patients with ICA in early childhood. CASE PRESENTATION: A 2-year-old girl showed intracranial hemorrhage due to a rupture of aneurysm at the middle cerebral artery. Quantitative measurements of ischemic damages on the head computed tomography (CT) marked an extremely low score of 2 points with modified Alberta Stroke Program Early CT Score (mASPECTS). She died 15 days after admission. In publications from 2021 to 2022, we found 21 children who were under 3 years of age at onset of ICA. None of them died, but two of three patients who had mASPECTS scores 0-8 showed developmental delay and/or epilepsy as neurological complications. CONCLUSION: Early CT findings are applicable for predicting survival and neurological outcomes of young children with intracranial hemorrhage.

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)0.003
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.289
Teacher spread0.263 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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