Trends in Arteriovenous Fistula Use at Dialysis Initiation After Automated <scp>eGFR</scp> Reporting
Bibliographic record
Abstract
The purpose of this study was to examine trends in the presence of an arteriovenous fistula (AVF) at dialysis initiation before and after eGFR reporting. All incident dialysis patients from four Canadian provinces that implemented province-wide, automated laboratory reporting of eGFR with known vascular access at dialysis initiation were included in the study (N = 25,201) from 2001 to 2010. The primary outcome was the change in proportion of patients with an AVF at dialysis initiation using an interrupted time series and adjusted multilevel logistic regression models. AVF usage at dialysis initiation decreased gradually over the study period from 19.0% to 14.6%. After implementation of automated eGFR reporting, there was attenuation in the decline in AVF usage in models adjusted for case-mix, facility, and the downward trajectory in AVF use over time. The adjusted odds ratio for initiating dialysis with an AVF 1 year post-eGFR reporting compared to pre-eGFR reporting was more pronounced in older patients (age tertile >73; OR: 1.40; 95% CI: 1.04-1.90). Laboratory-based eGFR reporting was associated with a possible attenuation in the decline of AVF at dialysis initiation and this was more pronounced in older patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".