Dialysis initiation in older persons across centres and over time in Australia and New Zealand
Bibliographic record
Abstract
AIM: With improved life expectancy over time, the burden of kidney failure resulting in kidney replacement therapy (KRT) in older persons is increasing. This study aimed to describe the age distribution at dialysis initiation in Australia and New Zealand (ANZ) across centres and over time. METHODS: Adults initiating dialysis as first KRT in ANZ from 1999 to 2018 reported to the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry were included. The primary outcomes were the age distribution and the proportion of older persons (75 years and older) initiating dialysis across centres and over time. Secondary outcomes were characterization of the older population compared with younger people and differences in dialysis modality and treatment trajectories between groups. RESULTS: Over the study period, 55 382 people initiated dialysis as first KRT, including 10 306 older persons, in 100 centres. Wide variation in age distribution across states/countries was noted, although the proportion of older persons at dialysis initiation did not significantly change over time (from 13% in 1999 to 19% in 2003, then remaining stable thereafter). Older persons were less likely to be treated with home therapies compared with younger people. Older persons were mostly Caucasians; had higher socioeconomic position, more cardiovascular comorbidities and higher eGFR at baseline; and resided in major cities. Higher proportions of older persons per centre were noted in privately funded facilities. CONCLUSION: Wide variations were noted in the proportions of older persons initiating dialysis across centres and states/country, which were associated with different case-mix across regions, particularly in terms of ethnicity, remoteness and socioeconomic advantage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".