Prospective Analysis of Arteriovenous Fistula Performance in the Context of Competing Risks
Bibliographic record
Abstract
Key Points Among 257 newly created arteriovenous fistulas, primary nonfunction occurred in 49%, and only 55% were ultimately used for dialysis. Loss of arteriovenous fistula patency was lower when competing risks were accounted for compared with conventional Kaplan–Meier analysis. We present icon-array plots that summarize our data and may be used a decision aid for patients in the future. Background Many patients with newly created arteriovenous fistulas (AVFs) may die before the AVF is needed for hemodialysis. However, formal competing risks (CRs) frameworks are rarely used to report AVF patency, which may lead to biased estimates. We sought to identify the proportion of newly created AVF experiencing primary nonfunction and describe long-term patency using a CR framework. Methods We conducted a prospective observational study in 257 adults with newly created AVF in Alberta, Canada. The primary outcome was primary nonfunction. Secondary outcomes included loss of primary patency, loss of assisted primary patency, and loss of secondary functional patency. Results were presented using icon-array plots to form the basis for future decision aids. Results Participants were 63.0% male, with mean age 62.3 years and median follow-up 18.5 months (range, 0.02–180 months). Of 257 participants, 50 could not be assessed for function or primary nonfunction, usually because of death. Of the remaining 207, 102 (49.3%) had primary nonfunction, and function was ultimately established for 142 (68.6%). Thus, only 142 of the 257 participants (55.3%) ultimately used the AVF for hemodialysis. High rates of CRs led to biased results from Kaplan–Meier analyses of lost patency. When accounting for CRs, loss of primary patency among AVFs with established function was 36.6%, 65.5%, and 66.2%, at 1, 3, and 5 years, respectively. Conclusions Only 55% of fistulas were ultimately used for hemodialysis when accounting for CRs and primary nonfunction. These results and the icon-array plots may inform discussions surrounding vascular access options for patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".