Perihematoma Cerebral Blood Flow is Unaffected by Statin Use in Acute Intracerebral Hemorrhage Patients
Bibliographic record
Abstract
Statin therapy has been associated with improved cerebral blood flow (CBF) and decreased perihematoma edema in animal models of intracerebral hemorrhage (ICH). We aimed to assess the relationship between statin use and cerebral hemodynamics in ICH patients. A post hoc analysis of 73 ICH patients enrolled in the Intracerebral Hemorrhage Acutely Decreasing Arterial Pressure Trial (ICH ADAPT). Patients presenting <24 hours from ICH onset were randomized to a systolic blood pressure target <150 or <180 mm Hg with computed tomography perfusion imaging 2 hours after randomization. Cerebral blood flow maps were calculated. Hematoma and edema volumes were measured planimetrically. Regression models were used to assess the relationship between statin use, perihematoma edema and cerebral hemodynamics. Fourteen patients (19%) were taking statins at the time of ICH. Statin-treated patients had similar median (IQR Q25 to 75) hematoma volumes (21.1 (9.5 to 38.3) mL versus 14.5 (5.6 to 27.7) mL, P=0.25), but larger median (IQR Q25 to 75) perihematoma edema volumes (2.9 (1.7 to 9.0) mL versus 2.2 (0.8 to 3.5) mL, P=0.02) compared with nontreated patients. Perihematoma and ipsilateral hemispheric CBF were similar in both groups. A multivariate linear regression model revealed that statin use and hematoma volumes were independent predictors of acute edema volumes. Statin use does not affect CBF in ICH patients. Statin use, along with hematoma volume, are independently associated with increased perihematoma edema volume.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".