Early hematoma retraction in intracerebral hemorrhage is uncommon and does not predict outcome
Bibliographic record
Abstract
BACKGROUND: Clot retraction in intracerebral hemorrhage (ICH) has been described and postulated to be related to effective hemostasis and perihematoma edema (PHE) formation. The incidence and quantitative extent of hematoma retraction (HR) is unknown. Our aim was to determine the incidence of HR between baseline and time of admission. We also tested the hypothesis that patients with HR had higher PHE volume and good prognosis. METHODS: This was a retrospective single-centre study in which serial planimetric volume measurements of the total hematoma volume (parenchymal (IPH) and intraventricular (IVH)) and PHE were performed in ICH patients with baseline non-contrast computed tomography (CT) completed within 6 hours of onset and follow-up CT 24 (±12) hours from symptom onset. HR was defined as a decrease in volume of >3ml or >15%, and hematoma expansion (HE) as an increase of >6ml or >30%. All other patients were categorized as stable hematoma (HS). Good outcome was defined as modified Rankin Scale (mRS) 0-2 at 90 days. RESULTS: A total of 136 patients (mean age = 69.3±13.39 years, 58.1% male) were included. Median (interquartile range) baseline total hematoma volume was 14.96 (7.80, 31.88) ml. HR >3ml and >15% occurred in 6 (4.4%) and 8 (5.9%) patients, respectively. Neither definition of HR was associated with follow-up PHE (p>0.297) or good outcome (p>0.249). IVH was the only independent predictor of HR (p<0.0241). CONCLUSIONS: Early HR is rare and associated with IVH, but not with PHE or clinical outcome. There was no relationship between HR, PHE, and patient prognosis. Therefore, HR is unlikely to be a useful endpoint in clinical ICH studies.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".