High-grade liver injuries with contrast extravasation managed initially with interventional radiology versus observation: A secondary analysis of a WTA multicenter study
Bibliographic record
Abstract
BACKGROUND: High-grade liver injuries with extravasation (HGLI + Extrav) are associated with morbidity/mortality. For low-grade injuries, an observation (OBS) first-strategy is beneficial over initial angiography (IR), however, it is unclear if OBS is safe for HGLI + Extrav. Therefore, we evaluated the management of HGLI + Extrav patients, hypothesizing IR patients will have decreased rates of operation and mortality. METHODS: HGLI + Extrav patients managed with initial OBS or IR were included. The primary outcome was need for operation. Secondary outcomes included liver-related complications (LRCs) and mortality. RESULTS: From 59 patients, 23 (39.0%) were managed with OBS and 36 (61.0%) with IR. 75% of IR patients underwent angioembolization, whereas 13% of OBS patients underwent any IR, all undergoing angioembolization. IR patients had an increased rate of operation (13.9% vs. 0%, p = 0.049), but no difference in LRCs (44.4% vs. 43.5%) or mortality (5.6% vs. 8.7%) versus OBS patients (both p > 0.05). CONCLUSION: Over 60% of patients were managed with IR initially. IR patients had an increased rate of operation yet similar rates of LRCs and mortality, suggesting initial OBS reasonable in appropriately selected HGLI + Extrav patients.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".