Abstract 18523: Simultaneous Consideration of Imaging and Blood Markers for Prediction of Hemorrhagic Transformation in Acute Ischemic Stroke
Bibliographic record
Abstract
Introduction: Prediction of hemorrhagic transformation (HT) may be helpful for the treatment decision in patients with acute ischemic stroke. Lower scores of Alberta Stroke program early CT score (ASPECTS), or high levels of plasma MMP-9 have been suggested to predict hemorrhage after thrombolytic treatment. Hypothesis: Combined measurements of baseline MMP-9 levels and ASPECTS can be surrogate markers of HT in acute ischemic stroke patients. Methods: Enrolled for this study were patients with acute cerebral infarction in the carotid artery territory who visited within 6 hours after symptom onset. Among them, those whose blood samples could be obtained before the thrombolytic treatment or before administration of any antithrombotic agent, and whose initial non-contrast CT of the brain was available were included. The baseline CT scans were scored by consensus approach of two neurologists. Plasma MMP-9 levels were measured by enzyme-linked immunosorbent assays. Severity of neurologic deficits was assessed ...
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".