Ultrasound guidance for vascular access in patients undergoing coronary angiography via the transradial approach.
Bibliographic record
Abstract
BACKGROUND: We assessed the value of routine real-time ultrasound (RTUS) guidance to improve transradial access (TRA) for cardiac catheterization. METHODS: A prospective, single-center descriptive observational study of patients presenting for cardiac catheterization via the transradial approach. The first phase of the study enrolled 100 consecutive patients who underwent TRA without the assistance of RTUS followed by 100 consecutive patients who underwent TRA using RTUS guidance. The primary outcome measure was time between needle attempts for arterial access and sheath insertion. RESULTS: There were no statistically significant differences in any outcome measures. Median time between commencing needle attempts for arterial access to sheath insertion was 82.5 seconds (interquartile range [IQR], 64-161.5 seconds) with no RTUS guidance vs 84 seconds (IQR, 52.75-122.5 seconds) with RTUS; P=.19. Median number of needle passes through the skin required was 1 (IQR, 1-3) with no RTUS guidance vs 2 (IQR, 1-3) with RTUS; P=.25. Median number of arterial punctures was 1 (IQR, 1-1) with no RTUS guidance vs 1 (IQR, 1-1) with RTUS; P=.21. CONCLUSION: Routine RTUS guidance to assist in TRA does not significantly improve parameters of successful vascular access among high-volume radial operators. However, RTUS guidance should still be considered in selected cases and among less experienced radial practitioners.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".