Evaluating the Prognosis of Ischemic Stroke Using Low-Dose Multimodal Computed Tomography Parameters in Hyperacute Phase
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate the potential value of low-dose multimodal computed tomography (CT) in predicting prognosis of acute ischemic stroke (AIS) within 6 hours. METHODS: The admission "one-stop-shop" multimodal CT examination, including noncontrast CT (NCCT), low-dose CT perfusion, and CT angiography (CTA), was performed in patients with symptoms of stroke within 6 hours. Noncontrast CT, CTA source image (CTA-SI), cerebral blood flow (CBF), cerebral blood volume (CBV), time to peak (TTP), and mean transit time (MTT) maps were studied using Alberta Stroke Program Early CT Score (ASPECTS). The regional leptomeningeal collateral (rLMC) score (0-20) was dichotomized into 2 groups: good (11-20) and poor (0-10) rLMC. Poor functional outcomes were defined by a modified Rankin scale score of 3 to 6. RESULTS: One hundred forty-four patients were ultimately selected; 43.8% of them showed poor functional outcomes. They had lower ASPECTSs on NCCT, CTA-SI, CBV, CBF, TTP, and MTT, and poor rLMC was more frequently associated with poor functional outcomes (all P < 0.001). In the multivariate analysis for AIS patients with conservative treatment, CTA-SI-ASPECTS 6 or less (odds ratio [OR], 5.9; 95% confidence interval [95% CI], 1.9-18.4; P = 0.002) and poor collaterals (OR, 5.0; 95% CI, 1.3-15.4; P = 0.017), CBV-ASPECTS 6 or less (OR, 8.0; 95% CI, 2.7-24.0; P < 0.001), CBF-ASPECTS 4 or less (OR, 8.0; 95% CI, 2.0-31.5; P = 0.003), MTT-ASPECTS≤3 (OR, 5.8; 95% CI, 1.8-18.1; P = 0.003), TTP-ASPECTS 4 or less (OR, 5.0; 95% CI, 1.6-15.1; P = 0.005), and NCCT-ASPECTS 8 or less (OR, 5.9; 95% CI, 1.7-20.4; P = 0.005) were significantly associated with poor functional outcome. In the multivariate analysis for AIS patients with thrombolysis, CTA-SI-ASPECTS 6 or less (OR, 27.5; 95% CI, 2.9-262.3; P = 0.004), poor collaterals (OR, 28.0; 95% CI, 2.8-283.0; P < 0.028), and CBV-ASPECTS 6 or less (OR, 18.0; 95% CI, 3.0-107.7; P = 0.002) were associated with poor functional outcomes. Furthermore, the area under the curve (AUC) of the combination of CTA-SI-ASPECTS 6 or less, poor collaterals, and CBV-ASPECTS 6 or less (AUC, 0.87) was greater than that for any single parameter alone: CTA-SI-ASPECTS 6 or less (AUC, 0.80; P < 0.001), poor collaterals (AUC, 0.76; P < 0.001), and CBV-ASPECTS 6 or less (AUC, 0.81; P = 0.002). CONCLUSIONS: The combination of CTA-SI-ASPECTS, collaterals, and CBV-ASPECTS may improve predictive power compared with a single parameter alone.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it