Variability and Trends over Time and Across Centers in Hemodialysis Weekly Duration in Australia and New Zealand
Bibliographic record
Abstract
Background: Hemodialysis treatment prescription varies widely around the world. This study explored patient- and center-level characteristics associated with weekly haemodialysis hours. Methods: Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry data was analyzed. Characteristics associated with weekly duration were evaluated using mixed-effects linear regression models with patient- and center-level covariates as fixed effects, and dialysis center and state as random effects using the 2017 prevalent in-centre hemodialysis (ICHD) and home hemodialysis (HHD) cohorts. Evaluation of patterns of weekly duration over time analyzed the 2000 to 2017 incident ICHD and HHD cohorts. Results: Overall, 12,494 ICHD and 1,493 HHD prevalent patients in 2017 were included. Median weekly treatment duration was 13.5 (interquartile range (IQR) 12-15) hours for ICHD and 16 (IQR 15-20) hours for HHD. Male sex, younger age, higher body mass index, arteriovenous fistula/graft use, Aboriginal and Torres Strait Islander ethnicity and longer dialysis vintage were associated with longer weekly duration for both ICHD and HHD. No center characteristics were associated with weekly duration. Variability in duration across centers was very limited in ICHD compared to HHD, with variation in HHD being associated with state. Duration did not vary significantly over time for ICHD, whereas longer weekly HHD treatments were reported between 2006 and 2012 compared to before and after this period. Conclusions: This study in the Australian and New Zealand hemodialysis population showed that weekly treatment duration was primarily associated with patient characteristics. No center effect was demonstrated. Practice patterns seemed to differ across states/countries, with more variability in HHD than in ICHD. Funding: Government Support - Non-U.S.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".