International Comparisons of Native Arteriovenous Fistula Patency and Time to Becoming Catheter-Free: Findings From the Dialysis Outcomes and Practice Patterns Study (DOPPS)
Bibliographic record
Abstract
RATIONALE & OBJECTIVE: Optimizing vascular access use is crucial for long-term hemodialysis patient care. Because vascular access use varies internationally, we examined international differences in arteriovenous fistula (AVF) patency and time to becoming catheter-free for patients receiving a new AVF. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 2,191 AVFs newly created in 2,040 hemodialysis patients in 2009 to 2015 at 466 randomly selected facilities in the Dialysis Outcomes and Practice Patterns Study (DOPPS) from the United States, Japan, and EUR/ANZ (Belgium, France, Germany, Italy, Spain, Sweden, United Kingdom, Australia, and New Zealand). PREDICTORS: Demographics, comorbid conditions, dialysis vintage, body mass index, AVF location, and country/region. OUTCOMES: Primary/cumulative AVF patency (from creation), primary/cumulative functional patency (from first use), catheter dependence duration, and mortality. ANALYTICAL APPROACH: Outcomes estimated using Cox regression. RESULTS: Across regions, mean patient age ranged from 61 to 66 years, with male preponderance ranging from 55% to 66%, median dialysis vintage of 0.3 to 3.2 years, with 84%, 54%, and 32% of AVFs created in the forearm in Japan, EUR/ANZ, and United States, respectively. Japan displayed superior primary and cumulative patencies due to higher successful AVF use, whereas cumulative functional patency was similar across regions. AVF patency associations with age and other patient characteristics were weak or varied considerably between regions. Catheter-dependence following AVF creation was much longer in EUR/ANZ and US patients, with nearly 70% remaining catheter dependent 8 months after AVF creation when AVFs were not successfully used. Not using an arteriovenous access within 6 months of AVF creation was related to 53% higher mortality in the subsequent 6 months. LIMITATIONS: Residual confounding. CONCLUSIONS: Our findings highlight the need to reevaluate practices for optimizing long-term access planning and achievable AVF outcomes, especially AVF maturation. New AVFs that are not successfully used are associated with long-term catheter exposure and elevated mortality risk. These findings highlight the importance of selecting the best access type for each patient and developing effective clinical pathways for when AVFs fail to mature successfully.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".