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Record W4283800538 · doi:10.54029/2022kmj

ASPECTS as a clinical outcome marker for MCA infarction treated with thrombolytic therapy: Non-contrast CT versus CTA source images

2022· article· en· W4283800538 on OpenAlexaboutno aff
Fatma Ger Akarsu, Ezgi SEZER ERYILDIZ, Özlem AYKAÇ, Zehra Uysal Kocabaş, Atilla Özcan Özdemi̇r

Bibliographic record

VenueNeurology Asia · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineModified Rankin ScaleComputed tomography angiographyAngiographyMiddle cerebral arteryRadiologyStroke (engine)Computed tomographyOcclusionInternal medicineIschemic strokeIschemia

Abstract

fetched live from OpenAlex

Background & Objective: Computed tomography angiography (CTA) in acute stroke has been widely used to demonstrate arterial occlusion. Alberta Stroke Program Early CT Score (ASPECTS) is used to detect early ischemic signs in non-contrast computed tomography (NCCT) in the middle cerebral artery region. We hypothesized that computed tomography angiography source image (CTA-SI) is superior to NCCT in predicting final infarct volume, 24 hour National Institutes of Health Stroke Scale (NIHSS) score and 90-day clinical outcome. Methods: Patients who had an acute ischemic stroke due to middle cerebral artery (MCA) occlusion and treated with tissue plasminogen activator (tPA) were retrospectively evaluated. ASPECTS was evaluated by two experienced stroke neurologists in acute NCCT, CTA-SI, and follow up imaging. The final ASPECTS was compared with the mean baseline ASPECTS of NCCT and CTA-SI. The relation of both scores with 24-hour NIHSS and clinical outcome was compared. The Modified Rankin Scale (mRS) was utilized to evaluate the 90-day outcomes. mRS score of 0-2 was considered a “good outcome”. Results: Fifty-three patients were evaluated. We observed a significant relation among CTA-SI ASPECTS and after treatment 24hr ASPECTS (y= -3.9 + 1.4 x; 95% CI, -7.6 to -0.2) (y= -26.04 + 3.5 x; CI, -41 to -10). The median baseline 24-hr NHISS was 6 (0 - 22). We found a better correlation between CTA-SI ASPECTS and 24-hr NHISS (y= 363.06 + -37.03 x; CI, -148 to 864) than between NCCT ASPECTS and 24h NHISS (y=529.80 + -62.55 x; CI, 180 - 829). Median 90 days mRS score was 2 (0 - 6). According to Deming regression analysis, the CTA-SI ASPECTS (y= 76.10 + -7.69 x; 95% CI, -36 to 188) was more consistent with the 90 day mRS compared to NCCT ASPECTS (y=149.86 + -17.67 x; 95% CI, 23 - 267) CTA-SI was superior in predicting 24hr NIHSS and day 90 mRS compared to NCCT ASPECTS. Conclusion: Prediction of CTA-SI ASPECTs is better than NCCT ASPECTs at 24hr NIHSS, 3-month mRS and final infarct size in acute ischemic stroke patients treated with tPA.

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 score0.096
Threshold uncertainty score0.861

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 science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.319
Teacher spread0.292 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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