Early neurologic deterioration in intracerebral hemorrhage
Bibliographic record
Abstract
OBJECTIVE: To identify potential predictors of and factors associated with early neurologic deterioration (END) in primary intracerebral hemorrhage (ICH). METHODS: Two hundred sixty-six patients with spontaneous supratentorial ICH admitted within 12 hours of stroke onset were investigated in a multicenter, prospective study. Sixty-one clinical, biochemical, and neuroimaging variables were registered on admission, and 37 clinical and neuroimaging variables were registered at 48 hours. The volumes of the ICH and peripheral edema on admission and at 48 hours were measured on CT scan. Stroke severity and functional outcome were evaluated with the Canadian Stroke Scale (CSS) and modified Rankin Scale. END was diagnosed when the CSS score decreased > or =1 points between admission and 48 hours. With use of logistic regression analyses, baseline variables that predicted END and factors measured after the early acute phase and associated with END were investigated. RESULTS: END occurred in 61 (22.9%) patients. Body temperature of >37.5 degrees C (odds ratio [OR] 24.5; 95% CI 4.8 to 125), neutrophil count (by 1,000-unit increase; OR 2.1; 95% CI 1.6 to 2.6), and serum fibrinogen levels of >523 mg/dL (OR 5.6; 95% CI 1.9 to 16.2) on admission were independent predictors of END. Among the factors recorded at 48 hours, early ICH growth (OR 4.3; 95% CI 1.3 to 14.5), intraventricular bleeding (OR 2.6; 95% CI 1.4 to 5.0), and highest systolic blood pressure (by 10-unit increase; OR 1.17; 95% CI 1.02 to 1.32) were associated with END in multivariate analyses. CONCLUSIONS: Clinical and biologic markers of the inflammatory reaction on admission are predictors of subsequent END, whereas early ICH growth, intraventricular bleeding, and high systolic blood pressure within 48 hours are factors associated with END in patients with spontaneous ICH.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".