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Record W1997136823 · doi:10.1161/strokeaha.111.000709

Favorable Vascular Profile is an Independent Predictor of Outcome

2013· article· en· W1997136823 on OpenAlexaff
Peter D. Schellinger, Martin Köhrmann, Songling Liu, W.P. Dillon, Raul G. Nogueira, Ashfaq Shuaib, David S. Liebeskind

Bibliographic record

VenueStroke · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Alberta
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineOdds ratioConfidence intervalModified Rankin ScaleInternal medicineStroke (engine)Logistic regressionCardiologyUnivariate analysisRandomized controlled trialSurgeryMultivariate analysisIschemiaIschemic stroke

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: We hypothesized that a favorable vascular profile (FVP) defined as anatomic intactness of the Circle of Willis combined with a stable cerebral perfusion pressure (mean arterial blood pressure>65 mm Hg) is a prerequisite for collateral recruitment and maintenance and may improve outcome. We performed post hoc analyses of a subset of the Safety and Efficacy of NeuroFlo Technology in Ischemic Stroke (SENTIS) trial data set to identify whether FVP is associated with independent outcome. METHODS: SENTIS was a randomized, controlled device trial comparing hemodynamic augmentation with the NeuroFlo device to best medical treatment. We identified all patients from the primary dataset (n=515 patients) with available intracranial vascular imaging at baseline. Vascular imaging data were read blind to clinical and treatment data. We performed univariate and multivariate analyses to identify predictors of independent outcome (modified Rankin Scale 0-2) at 90 days. RESULTS: A total of 192/515 SENTIS subjects had available baseline vascular imaging (91 treated/101 controls). Baseline characteristics did not differ between groups. Overall, FVP was seen in 89.6% of patients and predicted independent outcome in univariate (odds ratio, 7.46; 95% confidence interval, 1.68-33.18; P=0.0082) and multiple logistic regression analyses (odds ratio, 10.22; 95% confidence interval, 1.78-58.57; P=0.0091). Aside from FVP, only baseline National Institutes of Health Stroke Scales (NIHSS; odds ratio, 0.74; 95% confidence interval, 0.67-0.82, P<0.0001) entered the predictive model. There was no interaction with randomization to treatment or control. CONCLUSIONS: FVP and baseline NIHSS independently predicted outcome in this subset of the SENTIS population. FVP is a novel parameter to predict outcome of acute stroke patients and further studies will establish its potential role for selection of optimal candidates for hemodynamic augmentation. Clinical Trial Registration Information- URL: http://www.clinicaltrials.gov. Unique identifier: NCT00119717.

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)0.005
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.262
Teacher spread0.243 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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