Determinants and Prognostic Significance of Hematoma Sedimentation Levels in Acute Intracerebral Hemorrhage
Bibliographic record
Abstract
BACKGROUND: This study aimed at identifying the determinants and prognostic significance of a sedimentation level (fluid-blood level) in the hematoma among patients with acute intracerebral hemorrhage (ICH) who participated in the main Intensive Blood Pressure Reduction in Acute Cerebral Hemorrhage Trial (INTERACT2). METHODS: Post-hoc analysis of the INTERACT2 dataset, a randomized controlled trial of patients with acute ICH with elevated systolic blood pressure (SBP), randomly assigned to intensive (target SBP <140 mm Hg) or guideline-based (<180 mm Hg) BP management. Patients with a sedimentation level at baseline assessment on CT, and modified Rankin Scale score at 90-day, were included in these analyses. Factors associated with a sedimentation level and its significance in relation to 90-day clinical outcomes were assessed in univariable and multivariable logistic regression models. RESULTS: Of 2,065 participants, 19 (1%) had sedimentation level on baseline CT, which was independently associated with warfarin use (p = 0.006) and lobar ICH (p = 0.025). Sedimentation level was also associated with death or major disability at 90-day in both crude (84 vs. 53%; p = 0.014) and multivariable analyses adjusted for age, gender, Chinese region, warfarin use, baseline National Institutes of Health Stroke Scale score, onset to CT time, volume and location of ICH, intraventricular extension, and randomized intensive BP lowering (OR 3.94, 95% CI 1.01-15.37; p = 0.049). CONCLUSIONS: The presence of hematoma sedimentation level on baseline CT is associated with warfarin use and lobar location of ICH, and predicts a worse outcome. Although uncommon, sedimentation level is an easily detectable prognostic factor in acute 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".