[Molecular markers are associated with early computed tomography ischemic changes].
Bibliographic record
Abstract
INTRODUCTION: During brain ischemia, neurotoxicity, neuroinflammation and blood-brain barrier (BBB) disruption mechanisms are involved, leading to necrosis, edema and hemorrhagic transformation. Cranial computed tomography (CT) is the most widely used method in the diagnosis of acute stroke, and its early performance may help in the selection of patients for certain treatments. Our objective is to identify molecular markers of neuroexcitotoxicity, neuroinflammation and BBB disruption in the acute phase of stroke that might be associated with early ischemic CT signs. METHODS: 311 patients with ischemic stroke within the first 24 h from symptoms onset were prospectively included. We established tres groups based on the time between symptom onset and hospital arrival: < or = 6 h, between 6 and 12 h and >12 h. Cranial CT was performed at admission to evaluate early ischemic signs according to the Alberta Stroke Program Early CT Score (ASPECTS). Blood samples were taken at admission for the determination of molecular markers of neuroexcitotoxicity (glutamate), neuroinflammation (interleukin [IL]-6) and BBB disruption (metalloproteinase [MMP]-9). RESULTS: Patients with ASPECTS score < or =7 showed a worse early and late prognosis. Glutamate >134.4 microM (OR: 9.7; CI 95%: 4.2-22.5; p<0.001), IL-6>15.5 pg/mL (OR: 4.4; CI 95%: 2.1-9.4; p<0.001) and MMP-9 > 87.2 ng/mL (OR: 18.4; CI 95%: 7.2-47.1; p<0.001) were associated with ASPECTS score < or =7. In the logistic regression model, only glutamate >134.4 microM/l in the first 6 h (OR: 13.2; CI95%: 5.4-31.3; p<0.001), IL-6>15.5 pg/mL from 6 to 12 h (OR: 10.5; CI 95 %: 4.1-26.7; p<0.001) and MMP-9 >87.2 ng/ml after 12 h (OR: 24.2; CI 95%: 4.8- 50.2; p < 0.001) were independently associated with ASPECTS score < or = 7. CONCLUSIONS: The ASPECTS score may be considered as a surrogate marker of early neurological deterioration and final infarct volume, and associated with molecular markers of neuroexcitotoxicity, neuroinflammation and BBB disruption.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".