Safety and effectiveness of vascular closure devices in interventional radiological procedures
Bibliographic record
Abstract
Background Although it is well known that vascular closure devices (VCD) are commonly used in therapeutic interventional radiological procedures, standard use in diagnostic procedures is not as well studied. Purpose The aim of this study was to determine the real-world safety and effectiveness of the VCD in both diagnostic and therapeutic interventional radiological procedures. Materials and methods A retrospective, single center study included all patients where VCDs were used for either a diagnostic or therapeutic interventional procedure. Various demographic and clinical risk factors were recorded and examined for any significant association with successful deployment and complications. Results A total of 2072 patients were included. VCDs were successfully deployed in 95.2% of the patients with 4.8% of perioperative complications, which included minor oozing from the puncture site, small hematoma less than or equal to 5 cm, large hematoma greater than 5 cm, pain, and loss of vascular access. Therapeutic (vascular interventional radiology (VIR) and neuro-interventional radiology (NIR)) procedures (OR 3.03, 95% CI 1.51–6.09, p = 0.002), use of Angioseal (OR 5.26, 95% CI 3.13–8.33), p < 0.001), and no use of antiplatelet medications (OR 0.47, 95% CI 0.22–0.97, p = 0.041) were independently associated with successful deployment of VCDs when controlled for other risk factors. Smoking (OR 3.50, 95% CI 2.00–6.05, p = <0.001), use of antiplatelet (OR 2.01, 95% CI 1.04–3.87, p = 0.037) and use of heparin (OR 1.78, 95% CI 1.10–2.86, p = 0.018) were independently associated with higher complication rates. Conclusion VCD's were successfully deployed in 95.2% of the patients with 4.8% of perioperative minor complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".