Comparison between Surgical and Endovascular Hemodialysis Arteriovenous Fistula Interventions and Associated Costs
Bibliographic record
Abstract
PURPOSE: To compare: (i) rate of arteriovenous fistula (AVF) interventions in both incident and prevalent end-stage kidney disease patients; (ii) their associated costs; and (iii) intervention-free survival between patients with surgical hemodialysis arteriovenous fistula (SAVF) versus those with an endovascularly created fistula (endoAVF). MATERIALS AND METHODS: Data from the United States Renal Data System (USRDS) were abstracted to determine the rate of AVF interventions performed in the first year and associated costs (based on Medicare payment rates) for SAVFs created from 2011 to 2013 in the incident and prevalent patient cohorts. Comparative data for endoAVF were obtained from the Novel Endovascular Access Trial (NEAT). Event rates, intervention-free survival, and costs were compared between endoAVF and SAVF cohorts after 1:1 propensity score (PS) matching. RESULTS: In the matched incident patients, the event rate was 0.74 per patient-year (PY) for endoAVF versus 7.22/PY for SAVF (P < .0001), with a difference in expenditures of $16,494. Similarly, in matched prevalent patients the event rate was 0.46/PY for endoAVF vs 4.10/PY for SAVF (P < .0001), resulting in a cost difference of $13,389. Time-to-event analysis showed that at 1 year, 70% of endoAVF patients experienced freedom from intervention versus only 18% of SAVF patients for incident patients; these numbers were 62% and 18% for endoAVF and SAVF prevalent patients, respectively (P < .0001 for both). CONCLUSIONS: Both incident and prevalent patients with endoAVF required fewer interventions and had lower costs within the first year compared with matched patients with SAVF.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".