The Utility of Vascular Access Intervention via the Distal Radial Artery Approach in Hemodialysis Patients With Vascular Dysfunction
Bibliographic record
Abstract
BACKGROUND: Although case reports exist on vascular access intervention through the distal radial artery approach, there is a dearth of clinical studies reporting its safety and clinical outcomes. This study aimed to investigate the safety and long-term outcomes of vascular access intervention utilizing the distal radial artery approach. METHODS: Patients who underwent forearm arteriovenous fistula vascular access intervention at our hospital were divided into two groups: The distal radial artery approach (DRA group, N = 46) and the outflow vein approach (Vein group, N = 122). Patient characteristics, procedure results (procedure success rate, contrast medium dose, fluoroscopy dose), and one-year primary patency rates were compared between the two groups. FINDINGS: The procedure success rate was 100% in both groups. The DRA group demonstrated significantly lower contrast medium dose, fluoroscopy dose, and fluoroscopy time compared to the Vein group. No bleeding complications, arterial occlusion, or steal syndrome occurred in the DRA group. There was no significant difference in the one-year primary patency rate between the two groups. DISCUSSION: Vascular access intervention utilizing the distal radial artery approach offers benefits in reducing contrast medium and fluoroscopy dose compared to the outflow vein approach. Moreover, it demonstrates acceptable safety and patency rates.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".