Bibliographic record
Abstract
UNLABELLED: The aim of this study was to determine which variables should be the predictors for clinical outcome at discharge and sixth month after acute ischemic stroke. METHODS: Two hundred and sixty-six consecutive patients, each with an acute ischemic cerebrovascular disease, were evaluated within 24 h of symptom onset. We divided our patients into two groups; 1 - Independent (Rankin scale RS < or = 2) and, 2 - Dependent (RS>3) and death. Baseline characteristics, clinical variables, risk factors, infarct subtypes and radiologic parameters were analyzed. RESULTS: Canadian Neurological Scale (CNS) on admission <6.5 [odds ratio (OR) 22] and posterior circulation infarction (OR 4.2) were associated with a poor outcome at discharge from hospital whereas only a CNS score <6.5 (OR 14) was associated with a poor outcome at 6 months. CONCLUSIONS: Severity of neurologic deficit is the most important indicator for clinical outcome in acute ischemic stroke both at short-term and at sixth month, whereas posterior circulation infarction also predicts a poor outcome at discharge.
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 | 0.000 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".