Dialysis modality utilization patterns and mortality in older persons initiating dialysis in Australia and New Zealand
Bibliographic record
Abstract
AIM: The benefits of dialysis in the older population remain highly debated, particularly for certain dialysis modalities. This study aimed to explore the dialysis modality utilization patterns between in-centre haemodialysis (ICHD), peritoneal dialysis (PD) and home haemodialysis (HHD) and their association with outcomes in older persons. METHODS: Older persons (≥75 years) initiating dialysis in Australia and New Zealand from 1999 to 2018 reported to the Australia and New Zealand Dialysis and Transplant (ANZDATA) registry were included. The main aim of the study was to characterize dialysis modality utilization patterns and describe individual characteristics of each pattern. Relationships between identified patterns and survival, causes of death and withdrawal were examined as secondary analyses, where the pattern was considered as the exposure. RESULTS: A total of 10 306 older persons initiated dialysis over the study period. Of these, 6776 (66%) and 1535 (15%) were exclusively treated by ICHD and PD, respectively, while 136 (1%) ever received HHD during their dialysis treatment course. The remainder received both ICHD and PD: 906 (9%) started dialysis on ICHD and 953 (9%) on PD. Different individual characteristics were seen across dialysis modality utilization patterns. Median survival time was 3.0 (95%CI 2.9-3.1) years. Differences in survival were seen across groups and varied depending on the time period following dialysis initiation. Dialysis withdrawal was an important cause of death and varied according to individual characteristics and utilization patterns. CONCLUSION: This study showed that dialysis modality utilization patterns in older persons are associated with mortality, independent of individual characteristics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".