International Comparison of Home Dialysis Uptake: A Multi-Registry Analysis from the INTEGRATED Research Group
Bibliographic record
Abstract
Background: Despite advantages, home dialysis remains underutilized globally, with significant international variability. This study aims to analyse the pattern and uptake of home dialysis within the first year of dialysis across populations in different countries with similar access to kidney replacement therapy (KRT). Methods: This retrospective observational study utilized data from multiple national registries: ANZDATA (Australia-New Zealand), CORR (Canada), REIN (France), and UKRR (UK). We included adults over 18 starting dialysis between 1 January 2008 and 31 December 2018. The primary outcome was home dialysis initiation within the first year, visualized using cumulative incidences. Adjusted associations between patient characteristics and home dialysis initiation were analysed using clustered Cox regressions. Results: The study included 30 370 patients from ANZDATA, 50 682 from CORR, 103 962 from REIN, and 72 397 from UKRR. Home dialysis uptake at 12 months ranged from 41% (ANZDATA) to 13% (REIN). Transplant rates at 12 months varied from 1.1% (New Zealand) to 3.6% (UK), while 1-year mortality ranged from 5.5% (New Zealand) to 14% (France and Canada). Median age at dialysis initiation ranged from 59 years (New Zealand) to 71 years (France). Increased age was associated with a lower probability of home dialysis. Conclusions: This study highlights international differences in use of home dialysis within the first year of KRT. Patterns of conversion from facility haemodialysis to home dialysis were also different, underscoring the potential importance of healthcare systems and cultural factors within countries.
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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 | 0.014 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".