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Record W4406609513 · doi:10.3174/ajnr.a8659

Location-Specific Net Water Uptake and Malignant Cerebral Edema in Acute Anterior Circulation Occlusion Ischemic Stroke

2025· article· en· W4406609513 on OpenAlexaboutno aff
Li Huang, Xi Shen, Chang Sheng Zhou, Hui Pang, L Chen, Cheng Shao, Guangming Lu

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2025
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineCerebral edemaOcclusionStroke (engine)IschemiaIschemic strokeEdemaCerebral circulationAnesthesiaCardiologyInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT BACKGROUND AND PURPOSE: Early identification of malignant cerebral edema (MCE) in patients with acute ischemic stroke is crucial for timely interventions. We aimed to identify regions critically associated with MCE using the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) to evaluate the association between location-specific-net water uptake (NWU) and MCE. MATERIALS AND METHODS: This multicentre, retrospective cohort study included patients with acute ischemic stroke following large anterior circulation occlusion. The ASPECTS was determined by RAPID ASPECTS software. ASPECTS-NWU and Region-NWU were calculated automatically by comparing the Hounsfield units values in the ischemic and contralateral regions. Critical ASPECTS MCE regions and Region-NWU were evaluated by multivariate logistic regression and the areas under the receiver operating characteristic curves (AUCs). RESULTS: The study included 513 patients. Multivariate analysis showed that the ASPECTS insula (OR=2.49; 95% CI, 1.44–4.31) and M5 (OR=1.59; 95% CI, 1.11–3.41) regions were significantly associated with MCE. After adjustment, only the insula (OR=2.34; 95% CI, 1.23–4.45) was independently associated with MCE. Univariable ROC analysis found AUCs for Insula-NWU (AUC, 0.70; 95% CI, 0.65– 0.76)and ASPECTS-NWU (AUC, 0.64; 95% CI, 0.58-0.70) .The Insula-NWU had better diagnostic power than ASPECTS-NWU (DeLong test; P=0.01). A multivariate regression model that combined the NIHSS, ASPECTS, insula involvement, and Insula-NWU had good discriminatory power (AUC=0.80; 95% CI, 0.74–0.86) and better diagnostic power than Insula-NWU (DeLong test; P<0.01). CONCLUSIONS: Brief statement directed to the stated purpose or hypothesis; no references should be cited.The insula region is critical for MCE, and Insula-NWU has better prediction efficacy than ASPECTS-NWU. This method does not rely on advanced imaging, facilitating rapid assessment in emergencies. ABBREVIATIONS: ASPECTS = the Alberta Stroke Program Early Computed Tomography Score; AUC= the areas under the receiver operating characteristic curve; CT=computed tomography; CTP=CT perfusion; HU = hounsfield unit; MCE = malignant cerebral edema; NCCT=non-contrast Computed Tomography; NWU = net water uptake; ROC = receiver operating characteristic curve.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.008
GPT teacher head0.252
Teacher spread0.243 · 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 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

Citations2
Published2025
Admission routes1
Has abstractyes

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