Ultrasound guidance versus anatomical landmark approach for femoral artery access in coronary angiography: A randomized controlled trial and a meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: The objective was to assess the effect of ultrasound (US)-guidance compared to the anatomical landmark (AL) approach in patients requiring femoral artery (FA) access for coronary angiography/percutaneous coronary interventions (PCI). BACKGROUND: US-guidance has been proposed as a strategy to optimize FA access, potentially leading to decreased vascular complications. METHODS: Patients requiring FA access for coronary angiography/PCI were randomized to the US-guided or AL approaches. The primary endpoint was a composite of immediate procedural vascular outcomes, and access-site outcomes at day one. Results were subsequently pooled in a study-level meta-analysis of randomized trials comparing US-guided FA access to another strategy. RESULTS: A total of 129 patients were randomized (64 US-guided group; 65 AL group). The primary endpoint occurred in 30 patients (47%) with US, and in 39 patients (62%) with AL (P = 0.09). Four additional studies met the inclusion criteria and were included in the meta-analysis (1553 patients). Following data pooling, bleeding events (OR = 0.41; 95%CI 0.20-0.83; P = 0.01), venipunctures (OR = 0.18; 95%CI: 0.11-0.29; P < 0.0001), and multiple puncture attempts (OR = 0.24; 95%CI: 0.19-0.31; P < 0.0001) were significantly improved with US-guidance, but not successful common FA cannulation (OR = 0.84; 95%CI: 0.60-1.17; P = 0.29). CONCLUSION: Our study did not show significant benefits for the use of US to guide arterial femoral access compared to the anatomical landmark approach, but pooled analysis of five randomized trials showed decreased rates of bleeding events and venipunctures, and improved first-pass success. The clinical impact of these findings is uncertain, and do not warrant a systematic use of US-guidance in this clinical setting.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".