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Record W2897476095 · doi:10.1161/str.49.suppl_1.67

Abstract 67: RNA Expression Differentiates Large Artery And Cardioembolic Stroke: A Pilot Analysis From The BASE Trial

2018· article· en· W2897476095 on OpenAlexaff
Edward C. Jauch, Andrew D. Barreto, Joseph P. Broderick, Doug Char, Brett Cucchiara, William J. Hicks, Glen C. Jickling, Jeffrey G June, David S. Liebeskind, Joseph Miller, Judy Morgan, John O’Neill, Tim L. Schoonover, Frank R. Sharp, W. Frank Peacock, Ted Lowenkopf, David Huang

Bibliographic record

VenueStroke · 2018
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineStroke (engine)CardiologyInternal medicineAtrial fibrillationCoronary artery diseaseGold standard (test)

Abstract

fetched live from OpenAlex

Background: An accurate test to differentiate large artery stroke patients from those with cardioembolic stroke would be of significant utility. Using the Biomarkers of Acute Stroke Etiology (BASE) trial (NCT02014896) dataset, our purpose was to determine if blood gene expression signatures accurately differentiate large artery stroke patients from those with cardioembolic stroke. Methods: The BASE trial enrolled suspected stroke patients presenting to 10 hospitals within 8 hours of symptom onset. Gold standard diagnosis was per local neurologist adjudication blinded to RNA testing. The final gold standard diagnosis was determined by an adjudication committee blinded to RNA test results. Whole blood, obtained in PAX tubes, was frozen at -20C within 72 hours and analyzed at a core lab (Ischemia Care, LLC, Blue Ash, OH) using Affymetrix HTA micro arrays. Significantly differentially expressed genes (p<0.005) were identified by calculating an empirical Bayes moderated t-statistic contrasting expression in large artery and cardioembolic stroke patients. Differentially expressed genes were used as input to a multi-layer perceptron neural network to derive a 66-gene diagnostic signature. Results: Overall, 32 patients were enrolled, 8 (25%) with large artery stroke and 24 (75%) with cardioembolic stroke; 50% were male, and median (IQR) age was 68.6 (47,88). Median (IQR) time from symptoms to presentation was 102.5 (14, 450) minutes. Coexistent pathology at presentation was atrial fibrillation in 13 (41%), heart failure 7 (22%), prior stroke 7 (22%), and coronary artery disease 8 (25%). The resulting gene signature distinguished large artery stroke from cardioembolic stroke; C-statistic 0.99 (0.94-1.0, 95% CI), sensitivity 0.91 (0.56-1.0, 95% CI), at a fixed specificity of 0.95, as observed in 5-fold cross validation of the training data. Conclusion: RNA expression differentiates large artery stroke patients from those with cardioembolic stroke, and may have therapeutic and outcome implications.

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)0.006
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.256
Teacher spread0.240 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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