Ischemia in Intracerebral Hemorrhage Is Associated With Leukoaraiosis and Hematoma Volume, Not Blood Pressure Reduction
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Diffusion-weighted imaging (DWI) lesions have been identified both inside and outside the perihematoma region. We tested the hypotheses that larger hematoma volumes and blood pressure reduction are associated with DWI lesions. METHODS: Hematoma and perihematoma edema volumes were measured using planimetric techniques in 117 intracerebral hemorrhage (ICH) patients who underwent DWI. Perihematoma and remote DWI lesion volumes were measured using apparent diffusion coefficient thresholds for moderate (<730×10(-6) mm/s) and severe (<550×10(-6) mm/s) ischemia. Acute blood pressure change over the first 24 hours was calculated. RESULTS: The median (interquartile range) time to magnetic resonance imaging was 2 (1-5) days. Median hematoma volume was 9.8 (2.6-23.0) mL, and median perihematoma edema volume was 7.0 (2.9-18.6) mL. A small portion of the perihematoma region contained tissue below the thresholds for moderate (8.0 [2.9-14.5]%) and severe ischemia (1.1 [0.3-3.5]%). Ischemic perihematoma tissue volumes were correlated with hematoma volumes (R=0.52, P<0.001), but not maximal systolic blood pressure drop at 24 hours (R=-0.09, P=0.38). Remote DWI lesions were found in 17 (14.5%) patients (mean volume=0.44±0.3 mL). Patients with remote DWI lesions had higher rates of antiplatelet use (P=0.01), prior ICH (P=0.03), lobar ICH (0.04), and larger leukoaraiosis volumes (P=0.02). Maximal systolic blood pressure drop at 24 hours was similar in patients with (-20.5 [-55, -10] mm Hg) and without remote DWI lesions (-27 [-46, -13] mm Hg, P=0.96). CONCLUSIONS: Small DWI lesions within and outside the perihematoma region are common in primary ICH. Perihematoma DWI lesions were independently associated with larger hematoma volumes. Remote DWI lesions may be an epiphenomenon associated with the underlying microvascular pathogenesis. These data do not support a hemodynamic mechanism of ischemic injury after primary 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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".