Ultrasound Guidance in Femoral Artery Catheterization: A Systematic Review and a Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: During percutaneous cardiac procedures, the use of radial access is growing, but femoral access remains needed for large-bore, high-risk procedures. Methods are needed to make femoral access safer. In this systematic review and meta-analysis of randomized-controlled trials (RCTs), we assess whether ultrasound guidance is associated with a decreased risk of vascular complications during femoral artery catheterization. METHODS: Medline, Embase, and Cochrane Central were searched from inception to April 2018. RCTs assessing the use of ultrasound among adult patients undergoing a femoral artery catheterization were included. The primary outcome was vascular-access related complications. Secondary outcomes included major and minor vascular access bleeding, success rate, venipuncture, number of attempts, and successful placement into the common femoral artery. RESULTS: Five RCTs (n = 1553) met the inclusion criteria, with two trials using blinded outcome assessment. Ultrasound use was associated with a reduction in the rate of vascular-access related complications (1.9% vs 4.3%; odds ratio [OR], 0.44; 95% confidence interval [CI], 0.24-0.81; P<.01). This was primarily driven by a reduction in local hematomas; once hematomas were excluded, the association was no longer significant (0.6% vs 1.7%; OR, 0.39; 95% CI, 0.15-1.07; P=.07). There was no significant reduction in major bleeding (0.3% vs 1.3%; OR, 0.28; 95% CI, 0.07-0.1.16; P=.08) or minor bleeding (1.4% vs 2.8%; OR, 0.50; 95% CI, 0.24-1.05; P=.07). CONCLUSIONS: Ultrasound guidance during femoral artery catheterization is associated with a decreased risk of vascular complications, primarily driven by a reduction in local hematomas. Larger trials are needed to determine the effect of ultrasound on major bleeding and vascular complications (excluding hematomas).
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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 | 0.016 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".