Likelihood of Starting Dialysis after Incident Fistula Creation
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Guidelines promote early fistula creation to avoid central venous catheter use. This practice may lead to fistula creations in patients who never receive dialysis. The objective of this study was to estimate the risk of fistula nonuse with long-term follow-up. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Administrative health data identified 1929 predialysis adults who had their first fistula creation between April of 2002 and March of 2006. Patients were followed for a minimum of 2 years or until they began dialysis, received a kidney transplant, or died. RESULTS: The median follow-up times in patients who started dialysis, died without receiving dialysis, and remained in predialysis were 6.1, 11.5, and 38.7 months, respectively. Eighty-one percent of patients initiated dialysis; 9% of patients died without receiving dialysis, and 10% of patients remained predialysis. Forty percent of patients had their first fistula creation 3-12 months before initiating dialysis (the recommended window). Thirty percent were created within 90 days of starting dialysis; 30% were created more than 1 year before starting dialysis, and 10% were created more than 2 years before starting dialysis. Older patients, females, and patients with less comorbidity were not as likely to initiate dialysis after incident fistula creation. CONCLUSIONS: Most patients who underwent fistula creation before starting dialysis eventually received dialysis with extended follow-up, but the risk was significantly modified by age, sex, and comorbidity. Many patients had fistula creations earlier or later than recommended.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".