Endovascular balloon occlusion for catheter‐induced large artery perforation in the catheterization laboratory
Bibliographic record
Abstract
BACKGROUND: Vessel perforation is a complication that cannot be completely avoided in the setting of endovascular procedures. When a large noncompressible artery is disrupted, uncontrolled bleeding may lead to hemodynamic collapse. Endovascular occlusion may provide rapid control of hemorrhage and facilitate definitive therapy; yet, occlusion balloons are not commonly utilized in the cardiac catheterization laboratory. METHODS: We describe our experience with the use of dedicated occlusion balloons for the management of catheter-induced major bleeding events. Endovascular occlusion was utilized to control severe bleeding in five patients with perforation of the aorta, iliac, femoral, or pulmonary artery. RESULTS: Acute control of hemorrhage was achieved in all patients with hemodynamic stabilization in four of five cases. Endovascular balloon occlusion facilitated definitive therapy with surgical repair in two patients, covered stent deployment in one patient and transcatheter vessel occlusion in one patient. Care was withdrawn in one elderly patient with multiple comorbidities. All four patients who survived the procedure were discharged alive from the hospital. CONCLUSIONS: In most cases of severe catheter-induced bleeding, endovascular balloon occlusion provide a safe, rapid, and effective means of temporary bleeding control.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.001 |
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".