Handheld ultrasound‐guided cannulation of difficult hemodialysis arteriovenous access: A randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: Cannulation of complex arteriovenous fistula (AVF) or graft (AVG) frequently poses challenges to renal nursing practice. Ultrasound (US) guidance on visualizing central and peripheral venous access has been widely adopted in nephrology, reducing vascular intervention complications. Renal nurses could acquire this point-of-care technique to increase the successful cannulation rate while facilitating confidence build-up during practice. We aim to evaluate the use of handheld US on difficult AVF/AVG cannulation in a hospital-based dialysis unit. METHODS: We conducted a single-center randomized controlled trial from January 2021 to January 2022. Ten renal nurses were trained by an interventional nephrologist before patient recruitment and had completed a pre- and posttraining questionnaire on their confidence level. Fifty hemodialysis patients with complex AVF were randomized to US-guided or conventional cannulation. The total time spent on cannulation and patients' pain scores were also collected. FINDINGS: Renal nurses increased their confidence level after training (pretraining score 26.6 ± 6.9 vs. posttraining score 36.4 ± 3.0; p = 0.014). There was a higher success rate (only one cannulation attempt required) for US-guided (96%) versus conventional (72.0%) cannulation (p = 0.049). US-guided cannulation had a lower pain score than the conventional method (1.48 ± 0.73 vs. 2.13 ± 0.95, p = 0.012). The pre-cannulation assessment time and time spent on cannulation were comparable between the two groups. DISCUSSION: Our study showed that US-guided cannulation increased renal nurses' confidence level in difficult cannulation and improved success rate. Larger scale studies are required to further assess the applications of handheld US in AVF cannulation, particularly in different clinical settings (e.g., chronic dialysis centers).
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".