Use of the BioHole™ device for the creation of tunnel tracks for buttonhole cannulation of fistula for hemodialysis
Bibliographic record
Abstract
Buttonhole cannulation is a method of cannulation of native arteriovenous fistulae traditionally practiced by self-cannulators. At St Michael's Hospital, this method has been modified to allow its use in problematic fistulae by multiple cannulators. In a busy dialysis unit, the need for a few specific cannulators to establish the tunnel tracks in combination with the variable dialysis schedules creates logistical challenges. A new method of creating tunnel tracks with the use of the BioHole™ device was evaluated. Buttonhole tracks were created in 12 patients using a peg of polycarbonated material with a holder (BioHole™ kit). The peg was inserted into the path left by the hemodialysis sharp needle following the index cannulation. Four of the 12 patients had an alternate access. Buttonhole tracks were successfully created in all the patients, albeit in 2 patients, the initial attempt to establish buttonhole tracks was aborted due to complications and the procedure was rescheduled. Compared with the modified buttonhole technique, pain on cannulation following track creation was significantly less in the BioHole™ group (P < 0.001). Ease of cannulation was significantly improved in the BioHole™ group (P<0.05) when compared with that in thrice-weekly patients using the modified buttonhole technique. Hemostasis postdialysis did not differ between the study groups. The use of the BioHole™ device is effective in the creation of tunnel tracks for buttonhole cannulation, is associated with less pain, and simplifies the logistics of arranging patient and nurses' schedules.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".