Who should be referred for a fistula? A survey of nephrologists
Bibliographic record
Abstract
BACKGROUND: There is marked variation in the use of the arteriovenous fistula (AVF) across programmes, regions and countries not explained by differences in patient demographics or comorbidities. The lack of clear criteria of who should or should not get a fistula may contribute to this, as well as barriers to creating AVFs. METHODS: We conducted a survey of Canadian and American nephrologists to assess the patient variables considered to determine the timing and type of access requested. Perceived barriers and absolute contraindications to access were also collected. RESULTS: An immediate referral for a fistula was more highly preferred when patients are <65 years old, have minimal comorbidities or have no history of failed accesses. In older patients, and in those with increased comorbidities or a previously failed fistula, US nephrologists selected arteriovenous grafts as an alternative to the fistula, while Canadian nephrologists selected primarily catheters. Referral for vascular mapping was more common in the USA than in Canada. Gender did not influence the timing or the type of access. Perceived barriers to establishing a mature fistula included patient refusal for creation (77%) or cannulation (58%), delay in decision regarding dialysis modality (71%), wait time for surgical creation (55%) and high failure-to-mature rate (52%). We found that 27% of Canadian and 43% of American nephrologists indicated no absolute contraindications for permanent vascular access. CONCLUSIONS: This study demonstrated marked variability in timing and criteria used to select patients for referral for a vascular access between nephrologists practicing within Canada and the USA. Establishing minimal eligibility criteria for fistulae is an important area of future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".