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Record W2109442539 · doi:10.1161/strokeaha.113.001050

Optimizing Prediction Scores for Poor Outcome After Intra-Arterial Therapy in Anterior Circulation Acute Ischemic Stroke

2013· article· en· W2109442539 on OpenAlexaboutno aff
Amrou Sarraj, Karen C. Albright, Andrew D. Barreto, Amelia K. Boehme, Clark Sitton, Jeanie Choi, Steven L Lutzker, Chung-Huan J. Sun, Wafi Bibars, Claude Nguyen, Osman Mir, Farhaan Vahidy, Tzu-Ching Wu, George Α. Lopez, Nicole R. Gonzales, Randall C. Edgell, Sheryl Martin‐Schild, Hen Hallevi, Peng Roc Chen, Mark J. Dannenbaum, Jeffrey L. Saver, David S. Liebeskind, Raul G. Nogueira, Rishi Gupta, James C. Grotta, Sean I. Savitz

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Center for Research ResourcesNational Institute of Neurological Disorders and StrokeAgency for Healthcare Research and Quality
KeywordsMedicineThrombolysisModified Rankin ScaleConfidence intervalOdds ratioMiddle cerebral arteryStroke (engine)Internal medicineLogistic regressionCardiologyCerebral infarctionInternal carotid arterySurgeryIschemiaIschemic strokeMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Intra-arterial therapy (IAT) promotes recanalization of large artery occlusions in acute ischemic stroke. Despite high recanalization rates, poor clinical outcomes are common. We attempted to optimize a score that combines clinical and imaging variables to more accurately predict poor outcome after IAT in anterior circulation occlusions. METHODS: Patients with acute ischemic stroke undergoing IAT at University of Texas (UT) Houston for large artery occlusions (middle cerebral artery or internal carotid artery) were reviewed. Independent predictors of poor outcome (modified Rankin Scale, 4-6) were studied. External validation was performed on IAT-treated patients at Emory University. RESULTS: A total of 163 patients were identified at UT Houston. Independent predictors of poor outcome (P≤0.2) were identified as score variables using sensitivity analysis and logistic regression. Houston Intra-Arterial Therapy 2 (HIAT2) score ranges 0 to 10: age (≤59=0, 60-79=2, ≥80 years=4), glucose (<150=0, ≥150=1), National Institute Health Stroke Scale (≤10=0, 11-20=1, ≥21=2), the Alberta Stroke Program Early CT Score (8-10=0, ≤7=3). Patients with HIAT2≥5 were more likely to have poor outcomes at discharge (odds ratio, 6.43; 95% confidence interval, 2.75-15.02; P<0.001). After adjusting for reperfusion (Thrombolysis in Cerebral Infarction score≥2b) and time from symptom onset to recanalization, HIAT2≥5 remained an independent predictor of poor outcome (odds ratio, 5.88; 95% confidence interval, 1.96-17.64; P=0.02). Results from the cohort of Emory (198 patients) were consistent; patients with HIAT2 score≥5 had 6× greater odds of poor outcome at discharge and at 90 days. HIAT2 outperformed other previously published predictive scores. CONCLUSIONS: The HIAT2 score, which combines clinical and imaging variables, performed better than all previous scores in predicting poor outcome after IAT for anterior circulation large artery occlusions.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.268
Teacher spread0.253 · 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

Citations111
Published2013
Admission routes1
Has abstractyes

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