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Record W2290644163 · doi:10.1161/str.43.suppl_1.a2549

Abstract 2549: Favorable Vascular Profile Is An Independent Predictor Of Outcome: A Post Hoc Analysis Of The Sentis Trial

2012· article· en· W2290644163 on OpenAlexaff
Peter D. Schellinger, Martin Köhrmann, Songling Liu, William P. Dillon, Raul G. Nogueira, Ashfaq Shuaib, David S. Liebeskind

Bibliographic record

VenueStroke · 2012
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsUniversity of AlbertaDillon Consulting
Fundersnot available
KeywordsMedicinePost-hoc analysisStroke (engine)Internal medicineCardiologyCircle of WillisCerebral perfusion pressureUnivariate analysisBlood pressureRandomized controlled trialAtrial fibrillationPerfusion scanningMultivariate analysisPerfusion

Abstract

fetched live from OpenAlex

Background: The Safety and Efficacy of NeuroFlo TM Technology in Acute Ischemic Stroke (SENTIS) trial was the first randomized interventional stroke study for hemodynamic augmentation by partial aortic occlusion to improve neurological outcome versus standard medical management. We hypothesized that a favourable vascular profile (FVP) defined as anatomical intactness of the Circle of Willis (CoW, including visualization of the communicators) combined with a stable cerebral perfusion pressure (CPP) is a prerequisite for collateral recruitment and maintenance. We performed post hoc analyses to identify whether a favorable vascular profile (FVP) is associated with independent outcome. Methods: We identified all patients from the primary dataset (n=515 patients) with available intracranial vascular imaging (MRA, CTA, or conventional angiography) at baseline. Two independent readers evaluated the vascular imaging blind to clinical and treatment data. CPP compromise was assumed in critical hypotension defined as mean arterial blood pressure (MAP) drop below 65mmHg. FVP was scored, when CoW was intact and MAP >65mmHg at all timepoints within the first 12h of the NeuroFlo procedure. We performed univariate and multivariate analyses to identify predictors of independent outcome (mRS 0-2) at 90 days. Results: 192/515 SENTIS subjects had available baseline vascular imaging (91 treated / 101 controls). Baseline characteristics did not differ between groups (age, weight, infarct side, NIHSS, race, time from symptom onset, vital parameters, cardiovascular risk factors including atrial fibrillation (AF), medical history). Overall, FVP was seen in 89.6% of patients with a trend in favor of treated patients (94.5% vs 85.2%, p=0.0562). Nevertheless, presence of FVP predicted independent outcome in univariate (OR=7.46, 1.68-33.18, p=0.0082) and multiple logistic regression analyses after adjustment for all variables (OR=10.22, 1.78-58.57, p=0.0091). Aside from FVP, only baseline NIHSS (OR=0.74, 95% CI 0.67-0.82, p<0.0001) and presence of atrial fibrillation (OR=0.48, 95% CI 0.21-1.12, p=0.0909) entered the predictive model. There was no interaction with randomization to treatment or control. Conclusion: 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.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.277
Teacher spread0.258 · 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
Published2012
Admission routes1
Has abstractyes

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