Postcontrast CT Extravasation Is Associated With Hematoma Expansion in CTA Spot Negative Patients
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The purpose of this study was to assess the effect of postcontrast CT (PCCT) leakage (PCL) on hematoma growth in CTA spot negative patients. METHODS: A retrospective study of 61 patients presenting within 6 hours of primary ICH onset imaged with CT angiography (CTA) and PCCT. Presence of CTA spot sign and PCL were documented. PCL was defined as the presence of contrast extravasation on the PCCT study at a location remote from the CTA spot sign if present. Hematoma expansion was defined as >6 mL or 30% hematoma enlargement. Patients were dichotomized by CTA spot sign presence and PCL and compared for baseline demographic data, hematoma size, and growth using the unpaired t test and Mann-Whitney test for continuous and categorical data, respectively. A probability value <0.05 was considered significant. RESULTS: PCL was present in 11/61 patients (18%), occurring in 5 without a spot sign (45%). Spot negative PCL patients demonstrated larger absolute (P=0.02) and percentage hematoma growth (P=0.02) compared to those without PCL. The mean volume and percent increase was 6.7 mL and 26%, respectively. Inclusion of PCL together with CTA spot sign as risk factor for hematoma expansion increased sensitivity from 0.78 (95% CI; 0.52 to 0.94) to 0.94 (95% CI; 0.72 to 1.00) and NPV from 0.90 (95% CI; 0.76 to 0.97) to 0.97 (95% CI; 0.85 to 1.00). CONCLUSIONS: Inclusion of PCCT in the investigation of ICH patients allows detection of PCL which, together with the CTA spot sign, increases sensitivity and negative predictive value for predicting hematoma expansion. This finding should be validated in larger studies.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".