The prognosis prediction significance of Hounsfield unit value for stroke patients treated by intravenous thrombolysis
Bibliographic record
Abstract
BACKGROUND: Intravenous thrombolysis (IVT) is a rapid and effective treatment in the early stage of ischemic stroke patients and the purpose of this work is to explore the significance of Hounsfield unit (HU) value in Alberta Stroke Program Early CT Score (ASPECTS) for predicting the clinical prognosis of stroke patients with middle cerebral artery occlusion (MCAO) treated by IVT. METHODS: The 84 stroke patients with MCAO treated by IVT were divided into good prognosis group (48 cases) and poor prognosis group (36 cases). HU ratio and HU difference calculated from non-contrast computed tomography between groups were analyzed. RESULTS: The HU ratio of good prognosis group was higher than that in poor prognosis group and the HU difference of good prognosis group was lower than that in poor prognosis group (P < 0.05). The HU ratio and ASPECTS were negatively correlated with the infarct volume, and the HU difference was positively correlated with the infarct volume (P < 0.05). HU difference was an independent risk factor for prognosis of patients with MCAO treated by IVT. The area under the receiver operating characteristic curve of HU ratio and HU difference for prognosis was 0.743 and 0.833 respectively. CONCLUSION: The HU value changes are related to the clinical prognosis of stroke patients with MCAO treated by IVT, HU value may be a prognostic indicator for stroke patients with MCAO treated by IVT.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".