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Record W3007711717 · doi:10.1111/ene.14181

Hypoperfusion intensity ratio correlates with angiographic collaterals in acute ischaemic stroke with M1 occlusion

2020· article· en· W3007711717 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineNeuroradiologyPerfusionDigital subtraction angiographyPerfusion scanningMagnetic resonance imagingStroke (engine)OcclusionNuclear medicineRadiologyAngiographyInterventional radiologyInternal medicineMagnetic resonance angiographyCardiologyConfidence intervalNeurology

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Among patients with an acute ischaemic stroke secondary to large-vessel occlusion, the hypoperfusion intensity ratio (HIR) [time to maximum (TMax) > 10 volume/TMax > 6 volume] is a strong predictor of infarct growth. We studied the correlation between HIR and collaterals assessed with digital subtraction angiography (DSA) before thrombectomy. METHODS: Between January 2014 and March 2018, consecutive patients with an acute ischaemic stroke and an M1 middle cerebral artery (MCA) occlusion who underwent perfusion imaging and endovascular treatment at our center were screened. Ischaemic core (mL), HIR and perfusion mismatch (TMax > 6 s minus core volume) were assessed through magnetic resonance imaging or computed tomography perfusion. Collaterals were assessed on pre-intervention DSA using the American Society of Interventional and Therapeutic Neuroradiology/Society of Interventional Radiology (ASITN/SIR) scale. Baseline clinical and perfusion characteristics were compared between patients with good (ASITN/SIR score 3-4) and those with poor (ASITN/SIR score 0-2) DSA collaterals. Correlation between HIR and ASITN/SIR scores was evaluated using Pearson's correlation. Receiver operating characteristic analysis was performed to determine the optimal HIR threshold for the prediction of good DSA collaterals. RESULTS: A total of 98 patients were included; 49% (48/98) had good DSA collaterals and these patients had significantly smaller hypoperfusion volumes (TMax > 6 s, 89 vs. 125 mL; P = 0.007) and perfusion mismatch volumes (72 vs. 89 mL; P = 0.016). HIR was significantly correlated with DSA collaterals (-0.327; 95% confidence interval, -0.494 to -0.138; P = 0.01). An HIR cut-off of <0.4 best predicted good DSA collaterals with an odds ratio of 4.3 (95% confidence interval, 1.8-10.1) (sensitivity, 0.792; specificity, 0.560; area under curve, 0.708). CONCLUSION: The HIR is a robust indicator of angiographic collaterals and might be used as a surrogate of collateral assessment in patients undergoing magnetic resonance imaging. HIR <0.4 best predicted good DSA collaterals.

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.

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 score0.242
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.012
GPT teacher head0.212
Teacher spread0.200 · 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