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Record W4224313872 · doi:10.7759/cureus.24449

Predictors of Radiographic and Symptomatic Hemorrhagic Conversion Following Endovascular Thrombectomy for Acute Ischemic Stroke Due to Large Vessel Occlusion

2022· article· en· W4224313872 on OpenAlexaboutno aff
Kainaat Javed, Andre E. Boyke, Ishan Naidu, Jessica Ryvlin, Rose Fluss, Adisson Fortunel, Joseph Dardick, Devikarani Kadaba, David Altschul, Neil Haranhalli

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsMedicineStroke (engine)Odds ratioConfidence intervalLogistic regressionRetrospective cohort studyOcclusionSurgeryInternal medicine

Abstract

fetched live from OpenAlex

Background Endovascular therapy is known to achieve a high rate of recanalization in patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) and is currently the standard of care. Hemorrhagic conversion is a severe complication that may occur following AIS in patients undergoing endovascular thrombectomy (EVT). There is a scarcity of data on the risk factors related to HV in post-EVT patients, especially those who develop symptomatic hemorrhagic conversion. The main objective of our study is to identify independent predictors of radiographic and symptomatic hemorrhagic conversion in our diverse patient population with multiple baseline comorbidities that presented with AIS and were treated with EVT as per the most updated guidelines and practices. Methodology This is a retrospective chart review in which we enrolled adult patients treated with EVT for AIS at a comprehensive stroke center in the Bronx, NY, over a four-year period. Bivariate analyses followed by multiple logistic regression modeling were performed to determine the independent predictors of all and symptomatic hemorrhagic conversion. Results A total of 326 patients who underwent EVT for AIS were enrolled. Of these, 74 (22.7%) had an HC, while 252 (77.3%) did not. In total, 25 out of the 74 (33.7%) patients were symptomatic. In the logistic regression model, a history of prior ischemic stroke (odds ratio (OR) = 2.197; 95% confidence interval (CI) = 1.062-4.545; p-value = 0.034), Alberta Stroke Program Early CT Score (ASPECTS) of <6 (OR = 2.207; 95% CI = 1.477-7.194; p-value = 0.019), and Thrombolysis in Cerebral Infarction (TICI) 2B-3 recanalization (OR = 2.551; 95% CI = 1.998-6.520; p-value=0.045) were found to be independent predictors of all types of hemorrhagic conversion. The only independent predictor of symptomatic hemorrhagic conversion on multiple logistic regression modeling was an elevated international normalized ratio (INR) (OR = 11.051; 95% CI = 1.866-65.440; p-value = 0.008). Conclusions History of prior ischemic stroke, low ASPECTS score, and TICI 2B-3 recanalization are independent predictors of hemorrhagic conversion while an elevated INR is the only independent predictor of symptomatic hemorrhagic conversion in post-thrombectomy patients.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.007
GPT teacher head0.244
Teacher spread0.238 · 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 designNot applicable
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

Citations6
Published2022
Admission routes1
Has abstractyes

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