Factors predicting failure of <scp>AV</scp> “fistula first” policy in the elderly
Bibliographic record
Abstract
An arteriovenous fistula (AVF) is the preferential hemodialysis (HD) access. The goal of this study was to identify factors associated with pre-dialysis AVF failure in an elderly HD population. We used United States Renal Data System + Medicare claims data to identify patients ≥ 67 years old who had an AVF as their initial vascular access placed pre-dialysis. Failure of the AVF to be used for initial HD, was used as the outcome. Logistic regression model was used to identify factors associated with AVF failure. The study cohort consisted of 20,360 subjects (76.2 ± 6.02 year old, 58.5% men). Forty-eight percent of patients initiated dialysis using an AVF, while 52% used a catheter or an AVG. The following variables found to be associated with AVF failure when an AVF was created at least 4 months pre-HD initiation: older age (odds ratio [OR] 1.01; 95% confidence interval [CI] 1.00-1.02), female gender (OR 1.69; 95% CI 1.55-1.83), black race (OR 1.41; 95% CI 1.26-1.58), history of diabetes (OR 1.22; 95% CI 1.06-1.39), cardiac failure (OR 1.26; 95% CI 1.15-1.37), and shorter duration of pre-end-stage renal disease (ESRD) nephrology care (OR for a nephrology care of less than 6 months prior to ESRD of 1.22 compared with a pre-ESRD nephrology follow up of more than 12 months; 95% CI 1.07-1.38). OR for AVF failure for the entire cohort showed similar findings. In an elderly HD population, there is an association of older age, female gender, black race, diabetes, cardiac failure and shorter pre-ESRD nephrology care with predialysis AVF failure.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".