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Record W2774382985 · doi:10.1161/str.48.suppl_1.tmp22

Abstract TMP22: Thrombus Volume as Predictor of Successful Recanalization in the Acute Stroke Patients With Thrombolytic Treatment

2017· article· en· W2774382985 on OpenAlexaff
Joonsang Yoo, Jang‐Hyun Baek, Dongbeom Song, Kyoungsub Kim, Young Dae Kim, Hyo Suk Nam, Ji Hoe Heo

Bibliographic record

VenueStroke · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineThrombusThrombolysisInterquartile rangeStroke (engine)RadiologyAngiographyCardiologyInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Introduction: The prediction of non-recanalization after IV thrombolysis (IVT) may be helpful to avoid unnecessary treatment and determine the strategy of recanalization treatment. Thrombus volume and density can be measured using software, which may provide accurate and reliable information on thrombus characteristics. Hypothesis: We hypothesized that the thrombus volume and/or density could predict non-recanalization after IVT. Methods: This was a post-hoc analysis of prospective cohort who underwent thin-section noncontrast CT (1 or 1.25 mm) and recanalization therapy. Among them, this study considered patients who received IVT due to anterior circulation stroke from Nov. 2006 to Dec. 2015. The volume and density of thrombus were measured semi-automatically using 3-dimensional software. Recanalization was assessed on CT angiography at the end of IVT or conventional angiography in cases further treated with intra-arterial treatment. Successful recanalization was defined as arterial occlusive lesion grade 2 or 3. Results: Among 345 patients considered, 218 with visible thrombus in the intracranial arteries were included for this study. Successful recanalization was achieved in 79 patients (36.2%). Thrombus volume was significantly larger in patients with non-recanalization than those with successful recanalization (median [interquartile range]: 117.8mm 3 [60.0 - 216.8 mm 3 ] vs. 56.9 mm 3 [31.1 - 105.0 mm 3 ]. p<0.001). In the multivariate analysis, thrombus volume was independently associated with non-recanalization (p<0.001). Recanalization failed in all cases with thrombus > 300 mm 3 , and in 41 of 44 cases (93.2%) with thrombus > 200 mm 3 . Thrombus density did not differ between the groups (non-recanalization vs. successful recanalization: 54.0 ± 9.1 vs. 52.6 ± 8.5, p=0.263). Conclusions: Thrombus volume was predictive of non-recanalization after IVT. Measurements of thrombus volume may be helpful to determine the strategy of recanalization treatment.

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)0.004
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.270
Teacher spread0.257 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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