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Record W4309748408 · doi:10.1161/strokeaha.122.040540

Hypoperfusion Intensity Ratio Is Correlated With the Risk of Parenchymal Hematoma After Endovascular Stroke Treatment

2022· article· en· W4309748408 on OpenAlexaboutno aff
Laurens Winkelmeier, Jeremy J. Heit, Gautam Adusumilli, Vincent Geest, Sören Christensen, Helge Kniep, Noel van Horn, Paul Steffen, Matthias Bechstein, Peter B. Sporns, Maarten G. Lansberg, Gregory W. Albers, Max Wintermark, Jens Fiehler, Tobias D. Faizy

Bibliographic record

VenueStroke · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineModified Rankin ScaleOdds ratioStroke (engine)HematomaPerfusion scanningPerfusionInternal medicineRetrospective cohort studyCardiologySurgeryIschemiaIschemic stroke

Abstract

fetched live from OpenAlex

Background: Parenchymal hematoma (PH) is a major complication after endovascular treatment (EVT) for ischemic stroke. The hypoperfusion intensity ratio (HIR) represents a perfusion parameter reflecting arterial collateralization and cerebral microperfusion in ischemic brain tissue. We hypothesized that HIR correlates with the risk of PH after EVT. Methods: Retrospective multicenter cohort study of patients with large vessel occlusion who underwent EVT between 2013 and 2021 at one of the 2 comprehensive stroke centers (University Medical Center Hamburg-Eppendorf, Germany and Stanford University School of Medicine, CA). HIR was automatically calculated on computed tomography perfusion studies as the ratio of brain volume with time-to-max (Tmax) delay >10 s over volume with Tmax >6 s. Reperfusion hemorrhages were assessed according to the Heidelberg Bleeding Classification. Primary outcome was PH occurrence (PH+) or absence (PH−) on follow-up imaging. Secondary outcome was good clinical outcome defined as a 90-day modified Rankin Scale score of 0 to 2. Results: A total of 624 patients met the inclusion criteria. We observed PH in 91 (14.6%) patients after EVT. PH+ patients had higher HIR on admission compared with PH− patients (median, 0.6 versus 0.4; P <0.001). In multivariable regression, higher admission blood glucose (adjusted odds ratio [aOR], 1.08 [95% CI, 1.04–1.13]; P <0.001), extensive baseline infarct defined as Alberta Stroke Program Early CT Score ≤5 (aOR, 2.48 [1.37–4.42]; P =0.002), and higher HIR (aOR, 1.22 [1.09–1.38]; P <0.001) were independent determinants of PH after EVT. Both higher HIR (aOR, 0.83 [0.75–0.92]; P <0.001) and PH on follow-up imaging (aOR, 0.39 [0.18–0.80]; P =0.013) were independently associated with lower odds of achieving good clinical outcome. Conclusions: Poorer (higher) HIR on admission perfusion imaging was strongly associated with PH occurrence after EVT. HIR as a surrogate for cerebral microperfusion might reflect tissue vulnerability for reperfusion hemorrhages. This automated and quickly available perfusion parameter might help to assess the need for intensive medical care after EVT.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.210
Teacher spread0.202 · 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

Citations44
Published2022
Admission routes1
Has abstractyes

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