Multiple Single Cannulaton Technique for Puncturing Arteriovenous Fistulas: Randomized Comparison With Rope Ladder Technique Cannulation
Bibliographic record
Abstract
OBJECTIVE: This study aims to evaluate the impact of multiple single cannulation technique (MuST) on complications associated with arteriovenous fistulas (AV fistulas) in hemodialysis patients. METHODS: Patients who initiated hemodialysis using AV fistulas at our hospital between August 2023 and December 2023 were selected using convenience sampling. Participants were randomly assigned to either the control group or the experimental group using a random number table, with odd-numbered patients placed in the control group and even-numbered patients in the experimental group. The experimental group received MuST, while the control group received the rope ladder cannulation technique. After 12 months of follow-up, we assessed the incidence of aneurysms, thrombosis, infiltration, and stenosis, along with the cannulation success rate. Pain levels were evaluated using the Visual Analogue Scale (VAS) for pain, and cannulation difficulty was rated using Likert's five-point scale. RESULTS: The experimental group exhibited significantly lower incidences of aneurysms (3.44% vs. 15.3%), thrombus (1.72% vs. 13.6%), and stenosis (1.72% vs. 11.7%) compared to the control group (p < 0.05). The cannulation success rate was also significantly higher in the experimental group (99.5% vs. 99.0%) (p < 0.05). Moreover, the experimental group reported significantly lower cannulation difficulty scores (1.41 ± 0.54 vs. 2.24 ± 1.04) and pain scores (1.82 ± 0.93 vs. 3.29 ± 0.77) (p < 0.05). However, the incidence of infiltration was significantly higher in the experimental group (19.0% vs. 6.78%). CONCLUSIONS: MuST was associated with reduced pain and higher success rate of cannulation, and fewer complications compared to the standard rope ladder method. However, it was linked with a higher rate of infiltration. These findings suggest that MuST may be a promising alternative and warrants further investigation and broader clinical adoption.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".