Predictors of good prognosis in total anterior circulation infarction within 6 h after onset under conventional therapy
Bibliographic record
Abstract
OBJECTIVE: We investigated the predictors of good prognosis in total anterior circulation infarction (TACI), under conventional therapy. METHODS: We enrolled 166 patients with first-ever ischemic stroke within 6 h after onset with symptoms of TACI. Sixty-three patients (38.0%) with good outcome [G group, the modified Rankin Disability Scale (mRS) after 3 months < or =3] and 103 patients (62.0%) with bad outcome (B group, mRS >3) were compared. RESULTS: On univariate analysis, G group patients were significantly younger, had lower score in the National Institutes of Health Stroke Scale (NIHSS) of total and consciousness sub-score, had lower rate of clinical deterioration. On cranial CT at entry, three early CT signs [hyperdense middle cerebral artery (MCA) sign, hypodensity of >1/3 MCA and brain swelling] were significantly more frequent in the B group. On the second CT at 24-48 h, infarct area as assessed by the Alberta Stroke Programme Early CT Score (ASPECTS) was significantly smaller in the G group. Multivariate analysis with logistic regression revealed age <7 0 years, NIHSS < or =15, no clinical deterioration, and only no brain swelling in early CT signs, and ASPECTS > or =7 as independent predictors of good prognosis. CONCLUSIONS: Some clinical variables are useful in predicting outcome in TACI within the early period after stroke onset.
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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 | 0.000 | 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 | 0.000 |
| 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".