Anaemia on Admission is Associated with More Severe Intracerebral Haemorrhage and Worse Outcomes
Bibliographic record
Abstract
BACKGROUND: Lower haemoglobin levels may impair cerebral oxygen delivery and threaten tissue viability in the setting of acute brain injury. Few studies have examined the association between haemoglobin levels and outcomes after spontaneous intracerebral haemorrhage. AIMS: We evaluated whether anaemia on admission was associated with greater intracerebral haemorrhage severity and worse outcome. METHODS: Consecutive patients with spontaneous intracerebral haemorrhage were analyzed from the Registry of the Canadian Stroke Network. Admission haemoglobin was related to stroke severity (using the Canadian Neurological Scale), modified Rankin score at discharge, and one-year mortality. Adjustment was made for potential confounders including age, gender, medical history, warfarin use, glucose, creatinine, blood pressure, and intraventricular haemorrhage. RESULTS: Two thousand four hundred six patients with intracerebral haemorrhage were studied of whom 23% had anaemia (haemoglobin <120 g/l) on admission, including 4% with haemoglobin <100 g/l. Patients with anaemia were more likely to have severe neurological deficits at presentation [haemoglobin ≤ 100 g/l, adjusted odds ratio 4.04 (95% confidence interval 2.39, 6.84); haemoglobin 101-120 g/l, adjusted odds ratio 1.93 (95% confidence interval 1.43, 2.59), both P < 0.0001]. In nonanticoagulated patients, severe anaemia was also associated with poor outcome (modified Rankin score 4-6) at discharge [haemoglobin ≤ 100 g/l, adjusted odds ratio 2.42 (95% confidence interval 1.07-5.47), P = 0.034] and increased mortality at one-year [haemoglobin ≤ 100 g/l, adjusted hazard ratio 1.73 (95% confidence interval 1.22-2.45), P = 0.002]. CONCLUSIONS: Anaemia on admission is associated with greater intracerebral haemorrhage severity and worse outcomes. The utility of transfusion remains unclear in this setting.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".