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Record W2911535651 · doi:10.1161/str.50.suppl_1.tp77

Abstract TP77: Collateral- vs Perfusion-Based Selection Paradigm of Late Window (6-24 hours) Patients With Acute Ischemic Stroke a Comparative Study of Decision Making Using Multi-Phase CTA and CT Perfusion

2019· article· en· W2911535651 on OpenAlexaff
Mohammed Almekhlafi, Wolfgang G. Kunz, Ryan McTaggart, Mohammed A. Najm, Jai Shankar, Alexander V. Khaw, Enrico Fainardi, Marta Rubiera, Mahesh Jayaraman, Michael D. Hill, Andrew M. Demchuk, Mayank Goyal, Bijoy K. Menon

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsWestern UniversityUniversity of ManitobaUniversity of Calgary
Fundersnot available
KeywordsMedicinePerfusion scanningStroke (engine)PerfusionCollateral circulationLogistic regressionRadiologyReceiver operating characteristicNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

Purpose: To compare the performance of collateral- vs perfusion-based imaging paradigms in late window stroke patients. Methods: In the prospective international (PRove-IT) study, patients had baseline CT head, multi-phase CTA (mCTA) and CTP. Patients presenting 6-24 hours of onset were included. We retrospectively selected patients for EVT based on 1) Collaterals: ASPECTS ≥5, plus proximal intracranial occlusion, plus good mCTA collaterals; 2) Perfusion: using DEFUSE-3, or DAWN trial criteria. CTP was processed using RAPID software. The performance of each paradigm to predict outcomes was assessed using the area under the receiver operating characteristic curve (AUC) of logistic regression models adjusting for age, NIHSS, sex, onset to CT time, EVT treatment, and interaction of EVT and the imaging paradigm. Results: We included 83 patients; medians of age 71, NIHSS 12, ASPECTS 9, and onset/ last seen well to CT of 576 minutes. Occlusions were: ICA, M1, M2-MCA (81.9 %), distal (8.4%) and none (9.6%). 35 patients received EVT (all without IV tPA), 10 IV tPA, and 38 treated conservatively. TICI 2b-3 was achieved in 71.4% of EVT patients. mRS≤2 at 90 days was achieved in 47% (51.4% with EVT: 72% of TICI2b/3 patients). Table 1 shows 90-day mRS according to the imaging paradigm for the entire cohort. Among 10 patients who were EVT-eligible according to mCTA but not DEFUSE-3, 70% achieved mRS≤2. Among 31 who were EVT-eligible per mCTA but not DAWN, 61% achieved mRS≤2. For 5 patients who were EVT-eligible per DEFUSE-3 but not mCTA, 60% achieved mRS≤2. No patients were EVT-eligible per DAWN but not per mCTA. All paradigms had comparable AUCs for 90-day mRS≤2. In the EVT subgroup, mCTA had AUC of 0.80 vs 0.79 for DAWN, and 0.78 in DEFUSE-3 paradigms. Conclusion: The mCTA-defined collateral paradigm performs similarly well for EVT selection in the late time window. It also may include additional patients with possible benefit from ECT who would have been excluded by CTP-based imaging selection.

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 score0.001
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.020
GPT teacher head0.308
Teacher spread0.288 · 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
Published2019
Admission routes1
Has abstractyes

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