Bibliographic record
Abstract
Background: This study examines whether abnormal blood hemoglobin concentration (bHB) is associated with worse clinical outcomes and poorer prognosis after acute ischemic stroke. Methods: We included data from the Registry of the Canadian Stroke Network on consecutive patients with ischemic stroke who were admitted between July/2003 and March/2008. Patients were divided into groups as follows: low bHB, normal bHB, and high bHB. Primary outcome measures were the frequency of moderate/severe strokes on admission (Canadian Neurological Scale: <8), greater degree of disability at discharge (modified Rankin score: 3-6), and 30-day and 90-day mortality. Results: Higher bHB than the superior normal limit is associated with greater degree of impairment (OR=1.45, 95%CI: 1.06-1.95, p=0.0195) and disability (OR=1.49, 95%CI: 1.03-2.15, p=0.0331), and higher 30-day mortality (HR=1.98, 95%CI: 1.44-2.74, p<0.0001) after adjustment for major potential confounders. The Kaplan-Meier curves indicate that abnormal bHB is associated with higher mortality after acute ischemic stroke (p<0.0001). Lower bHB than the inferior normal limit is associated with longer stay in the acute stroke care center (OR=1.11, 95%CI: 1.02-1.22, p=0.017). Conclusions: Polycythemia on the initial admission is associated with poorer prognosis regarding the degree of impairment and disability, and 30-day mortality after an acute ischemic stroke. Anemia on admission is associated with longer stay in the acute stroke center.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.303 | 0.147 |
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".