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Record W2622125475 · doi:10.1161/str.47.suppl_1.tp44

Abstract TP44: Low Cerebral Blood Flow (CBF) at Baseline Best Predicts Parenchymal Hematoma (PH) Post Revascularization Therapy

2016· article· en· W2622125475 on OpenAlexaff
Connor Batchelor, Connor C. McDougall, Patrick Wee, Mari E. Boesen, Emmad Qazi, Mohamed Najm, Enrico Fainardi, Tolu Sajobi, Christopher D. d’Esterre, Ting Y. Lee, Richard I. Aviv, Andrew M. Demchuk, Mayank Goyal, Bijoy K. Menon

Bibliographic record

VenueStroke · 2016
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsCalgary Laboratory ServicesSunnybrook Health Science CentreUniversity of Calgary
Fundersnot available
KeywordsMedicineCerebral blood flowCerebral blood volumeNuclear medicineHematomaRevascularizationCardiologyIntracerebral hemorrhagePerfusion scanningPerfusionAnesthesiaInternal medicineSurgerySubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Introduction: In patients with acute ischemic stroke (AIS), parenchymal hematoma (PH) after revascularization therapy can lead to clinical deterioration and is often unpredictable. We sought to examine the association between admission CT perfusion (CTP) parameters (cerebral blood volume (CBV), cerebral blood flow (CBF), and Tmax) and PH in a case-controlled sample of patients receiving intravenous tPA ± endovascular treatment when using an industry standard CTP algorithm. Hypothesis: We hypothesize that CTP derived parameters (CBV, CBF, and Tmax) can predict PH in AIS. Methods: PH was classified according to ECASS II criteria. Two-phase (150s) and single-phase (66s) CTP acquisitions were performed within 12hrs of ictus. CTP 4D(GE Healthcare) delay-insensitive software was used to calculate CBF, CBV, and Tmax maps. Ipsilateral hemisphere gray and white matter (GM, WM) were flooded to determine volumes (mm3) for 3 lesion types: 1) patient-specific very low CBV (vlCBV) thresholds derived from the lower 10th, 5th and 2.5th percentiles of the contralateral hemisphere, 2) very low CBF threshold of ≤7ml/(min·100g), and 3) very high Tmax threshold of ≥16s. To correct for varying scan coverage, ratio of threshold output volume by ipsilateral hemisphere volume within slices that contained lesions was obtained. Receiver operating characteristic (ROC) analysis was used to compare models to determine which CTP parameter best predicted PH. Results: 34 AIS patients (18 PH, 16 no hemorrhage) were included. Very low CBF threshold of ≤7ml/(min·100g) best predicted the occurrence of PH post revascularization therapy (p < 0.001; comparison of c-statistic). CBV and Tmax parameters were not discriminative of PH. (See Figure 1 for comparison of c- statistics). Conclusion: When using a delay insensitive industry standard CTP paradigm, very low CBF≤7ml/(min·100g) has the ability in predicting PH post revascularization therapy.

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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