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Record W2609747156 · doi:10.1161/strokeaha.117.016616

Use of Noncontrast Computed Tomography and Computed Tomographic Perfusion in Predicting Intracerebral Hemorrhage After Intravenous Alteplase Therapy

2017· article· en· W2609747156 on OpenAlexafffund
Connor Batchelor, Pooneh Pordeli, Christopher D. d’Esterre, Mohamed Najm, Fahad Al-Ajlan, Mari E. Boesen, Connor C. McDougall, Lisa Hur, Enrico Fainardi, Jai Shankar, Marta Rubiera, Alexander V. Khaw, Michael D. Hill, Andrew M. Demchuk, Tolulope T. Sajobi, Mayank Goyal, Ting‐Yim Lee, Richard I. Aviv, Bijoy K. Menon

Bibliographic record

VenueStroke · 2017
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of CalgaryHealth Sciences CentreDalhousie UniversityUniversity of TorontoLawson Health Research InstituteSunnybrook Health Science CentreWestern University
FundersCanadian Institutes of Health Research
KeywordsMedicineIntracerebral hemorrhageCerebral blood flowQuantitative computed tomographyPerfusion scanningStroke (engine)Confidence intervalRadiologyBlood volumeNuclear medicinePerfusionSurgeryInternal medicineGlasgow Coma Scale

Abstract

fetched live from OpenAlex

Background and Purpose— Intracerebral hemorrhage is a feared complication of intravenous alteplase therapy in patients with acute ischemic stroke. We explore the use of multimodal computed tomography in predicting this complication. Methods— All patients were administered intravenous alteplase with/without intra-arterial therapy. An age- and sex-matched case–control design with classic and conditional logistic regression techniques was chosen for analyses. Outcome was parenchymal hemorrhage on 24- to 48-hour imaging. Exposure variables were imaging (noncontrast computed tomography hypoattenuation degree, relative volume of very low cerebral blood volume, relative volume of cerebral blood flow ≤7 mL/min·per 100 g, relative volume of T max ≥16 s with all volumes standardized to z axis coverage, mean permeability surface area product values within T max ≥8 s volume, and mean permeability surface area product values within ipsilesional hemisphere) and clinical variables (NIHSS [National Institutes of Health Stroke Scale], onset to imaging time, baseline systolic blood pressure, blood glucose, serum creatinine, treatment type, and reperfusion status). Results— One-hundred eighteen subjects (22 patients with parenchymal hemorrhage versus 96 without, median baseline NIHSS score of 15) were included in the final analysis. In multivariable regression, noncontrast computed tomography hypoattenuation grade ( P <0.006) and computerized tomography perfusion white matter relative volume of very low cerebral blood volume ( P =0.04) were the only significant variables associated with parenchymal hemorrhage on follow-up imaging (area under the curve, 0.73; 95% confidence interval, 0.63–0.83). Interrater reliability for noncontrast computed tomography hypoattenuation grade was moderate (κ=0.6). Conclusions— Baseline hypoattenuation on noncontrast computed tomography and very low cerebral blood volume on computerized tomography perfusion are associated with development of parenchymal hemorrhage in patients with acute ischemic stroke receiving intravenous alteplase.

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)0.008
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 score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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

Citations24
Published2017
Admission routes2
Has abstractyes

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