Representativeness of the PDOPPS cohort compared to the Australian PD population
Bibliographic record
Abstract
BACKGROUND: The Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS) is an international, prospective study following persons treated by peritoneal dialysis (PD) to identify modifiable practices associated with improvements in PD technique and person survival. The aim of this study was to assess the representativeness of the Australian cohort included in PDOPPS compared to the complete Australian PD population, as reported to the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry. METHODS: Adults with at least one PD treatment reported to ANZDATA Registry during the census period of PDOPPS Phase I (November 2014 to April 2018) were compared to the Australian PDOPPS cohort. The primary outcomes were the representativeness of centres and persons. Secondary outcomes explored the association of person characteristics with consent to study participation. RESULTS: After data linkage, 511 PDOPPS participants were compared to 5616 Australians treated with PD. Within centres eligible for PDOPPS, selected centres were similar to other Australian centres. The PDOPPS participants' cohort tended to include older persons, more males, a higher proportion of Caucasians and more persons with higher socioeconomic advantage compared to the Australian PD population. Differences in distribution across sex and ethnicities between the PDOPPS cohort and the overall PD population were in part due to the selection and consent processes, during which females and non-Caucasians were more likely to not consent to PDOPPS participation. CONCLUSION: Sampling methods used in PDOPPS allowed for good national representativeness of the included centres. However, representativeness of the unweighted PDOPPS sample was suboptimal in regard to some participant characteristics.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".