Neuroimaging and clinical outcomes of oral anticoagulant–associated intracerebral hemorrhage
Bibliographic record
Abstract
Objective Whether intracerebral hemorrhage (ICH) associated with non–vitamin K antagonist oral anticoagulants (NOAC‐ICH) has a better outcome compared to ICH associated with vitamin K antagonists (VKA‐ICH) is uncertain. Methods We performed a systematic review and individual patient data meta‐analysis of cohort studies comparing clinical and radiological outcomes between NOAC‐ICH and VKA‐ICH patients. The primary outcome measure was 30‐day all‐cause mortality. All outcomes were assessed in multivariate regression analyses adjusted for age, sex, ICH location, and intraventricular hemorrhage extension. Results We included 7 eligible studies comprising 219 NOAC‐ICH and 831 VKA‐ICH patients (mean age = 77 years, 52.5% females). The 30‐day mortality was similar between NOAC‐ICH and VKA‐ICH (24.3% vs 26.5%; hazard ratio = 0.94, 95% confidence interval [CI] = 0.67–1.31). However, in multivariate analyses adjusting for potential confounders, NOAC‐ICH was associated with lower admission National Institutes of Health Stroke Scale (NIHSS) score (linear regression coefficient = −2.83, 95% CI = −5.28 to −0.38), lower likelihood of severe stroke (NIHSS > 10 points) on admission (odds ratio [OR] = 0.50, 95% CI = 0.30–0.84), and smaller baseline hematoma volume (linear regression coefficient = −0.24, 95% CI = −0.47 to −0.16). The two groups did not differ in the likelihood of baseline hematoma volume < 30cm3 (OR = 1.14, 95% CI = 0.81–1.62), hematoma expansion (OR = 0.97, 95% CI = 0.63–1.48), in‐hospital mortality (OR = 0.73, 95% CI = 0.49–1.11), functional status at discharge (common OR = 0.78, 95% CI = 0.57–1.07), or functional status at 3 months (common OR = 1.03, 95% CI = 0.75–1.43). Interpretation Although functional outcome at discharge, 1 month, or 3 months was comparable after NOAC‐ICH and VKA‐ICH, patients with NOAC‐ICH had smaller baseline hematoma volumes and less severe acute stroke syndromes. Ann Neurol 2018;84:702–712
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".