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Record W2553228974 · doi:10.1161/strokeaha.116.014794

Dissociation of Early and Delayed Cerebral Infarction After Aneurysmal Subarachnoid Hemorrhage

2016· article· en· W2553228974 on OpenAlexaff
Oliver G. S. Ayling, George M. Ibrahim, Naif M. Alotaibi, Peter Gooderham, R. Loch Macdonald

Bibliographic record

VenueStroke · 2016
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsUniversity of British ColumbiaSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSubarachnoid hemorrhageCerebral infarctionAnesthesiaCardiologyIschemia

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Cerebral infarction after aneurysmal subarachnoid hemorrhage is a significant cause of substantial morbidity and mortality. Because early and delayed cerebral infarction after aneurysmal subarachnoid hemorrhage may be mediated by different processes, we evaluated whether aneurysm-securing methods contributed to infarcts and whether long-term outcomes differ between early and delayed infarcts. METHODS: A post hoc analysis of the CONSCIOUS-1 study (Clazosentan to Overcome Neurological Ischemia and Infarction Occurring After Subarachnoid Hemorrhage) was performed. Using multivariate logistic regression analysis and propensity matching, independent clinical risk factors associated with infarctions were identified, and the contribution of cerebral infarcts to long-term outcomes was evaluated. RESULTS: Within the cohort of 413 subjects, early infarcts were present in 76 subjects (18%), whereas delayed infarcts occurred in 79 subjects (19%), and 36 subjects (9%) had new infarctions that were present on both early and delayed imaging. Propensity score matching revealed a significantly higher proportion of early infarcts after clipping (odds ratio, 4.62; 95% confidence interval, 1.99-11.57; P=0.00012). Multivariate logistic regressions identified clipping as an independent risk factor for early cerebral infarction (odds ratio, 0.26; 95% confidence interval, 0.15-0.48; P<0.001), and angiographic vasospasm was an independent risk factor for delayed cerebral infarction (odds ratio, 1.79; 95% confidence interval, 1.03-3.13; P=0.039). Early infarcts were a significant independent risk factor for poor long-term outcomes at 3 months (odds ratio, 2.34; 95% confidence interval, 1.18-4.67; P=0.015). CONCLUSIONS: Clipping is an independent risk factor for the development of early cerebral infarcts, whereas delayed cerebral infarcts are associated with angiographic vasospasm. Early cerebral infarcts are stronger predictors of worse outcome than delayed infarction. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00111085.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.201
Threshold uncertainty score0.214

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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 teacher head, 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

Citations62
Published2016
Admission routes1
Has abstractyes

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