Traumatic Intracranial Hematomas: Prognostic Value of Contrast Extravasation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Contrast extravasation within spontaneous intracranial hemorrhage is a well-described predictor of hematoma growth, poor clinical outcome, and mortality. The purpose of this study was to assess the prognostic value of contrast extravasation in acute traumatic intracranial hematomas. MATERIALS AND METHODS: In our institution, CTA (including PCCT) is the primary screening technique for cervical vascular injuries. Sixty consecutive patients with at least 1 acute intracranial hematoma (ICH, subdural hematoma, and/or epidural hematoma) meeting predefined size criteria, with CTA/PCCT performed within 24 hours of admission and follow-up CT within 72 hours of admission, were retrospectively evaluated for CE by 2 observers. The predictive value of CE for a composite outcome (hematoma expansion, need for hematoma evacuation, in-hospital mortality) was evaluated on a per-patient basis. Interobserver agreement for CE and the association between baseline variables and outcome were also examined. Different patterns of extravasation were evaluated on a per-lesion basis, with outcomes including hematoma expansion and evacuation. RESULTS: CE was present in 30 (50%) patients with almost perfect interobserver agreement (κ=0.87; 95% CI, 0.74-0.99). The per-patient multivariate analysis showed independent association of midline shift (P=.020), Glasgow Coma Scale score≤8 (P=.024), and CE (P=.017), with poor outcome and demonstrated a trend toward poor outcome prediction for age 65 years or older (P=.050). In the per-lesion analysis, only extravasation identified on CTA (active and contained extravasation) was associated with hematoma expansion and evacuation. CONCLUSIONS: Contrast extravasation within intracranial hematomas predicts poor in-hospital outcome in the setting of acute traumatic intracranial injuries.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".