Clinical and molecular correlates of the ASPECTS in the acute phase of stroke
Bibliographic record
Abstract
BACKGROUND: The Alberta Stroke Program Early CT Score (ASPECTS) scale was developed for monitoring early ischemic changes on CT, being associated with clinical outcomes. The ASPECTS can also associate with peripheral biomarkers that reflect the pathophysiological response of the brain to the ischemic stroke. OBJECTIVE: To investigate the association between peripheral biomarkers with the Alberta Stroke Program Early CT Score (ASPECTS) in individuals after ischemic stroke. METHODS: Patients over 18 years old with acute ischemic stroke were enrolled in this study. No patient was eligible for thrombolysis. The patients were submitted to non-contrast CT in the first 24 hours of admission, being the Alberta Stroke Program Early CT Score and clinical and molecular evaluations applied on the same day. The National Institutes of Health Stroke Scale (NIHSS), modified Rankin scale and the Mini-Mental State Examination for clinical evaluation were also applied to all subjects. Plasma levels of BDNF, VCAM-1, VEGF, IL-1β, sTNFRs and adiponectin were determined by ELISA. RESULTS: Worse neurological impairment (NIHSS), cognitive (MEEM) and functional (Rankin) performance was observed in the group with changes in the NCTT. Patients with NCTT changes also exhibited higher levels of IL-1β and adiponectin. In the linear multivariate regression, an adjusted R coefficient of 0.515 was found, indicating adiponectin and NIHSS as independent predictors of ASPECTS. CONCLUSION: Plasma levels of adiponectin are associated with the ASPECTS scores.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".