Optimal Vascular Access Choice for Patients on Hemodialysis
Bibliographic record
Abstract
Which vascular access to use is considered one of the most important questions in the care of patients on hemodialysis (HD). An arteriovenous fistula (AVF) is often considered the gold standard for delivering HD due to better patient survival, higher quality of life, and fewer complications. However, AVFs have some limitations: they require surgery, it takes approximately three months to know whether the surgery was successful, and a majority of these surgeries end in failure. Conversely, another common vascular access, the central venous catheter, can be inserted via a simple procedure and used immediately after placement. In this research, we address the question of whether and when to perform AVF surgery on incident and established HD patients, with the aim of finding individualized policies that maximize a patient’s probability of survival and remaining quality-adjusted life expectancy. Using a continuous-time dynamic programming model and under certain data-driven assumptions, we establish structural properties of the optimal policy for each objective. We provide further insights for policy makers through our numerical experiments.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".