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Record W3213895268 · doi:10.1177/08968608211056242

Representativeness of the PDOPPS cohort compared to the Australian PD population

2021· article· en· W3213895268 on OpenAlexaff
Isabelle Éthier, Neil Boudville, Stephen P. McDonald, Fiona G. Brown, Peter G. Kerr, Rowan G. Walker, Stephen Geoffroy Holt, Sunil V. Badve, Yeoungjee Cho, Carmel M. Hawley, Laura Robison, Donna Reidlinger, Elasma Milanzi, Brian Bieber, Keith McCullough, David W. Johnson

Bibliographic record

VenuePeritoneal Dialysis International · 2021
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Health and Medical Research Council
KeywordsRepresentativeness heuristicMedicineCohortPopulationDemographyPeritoneal dialysisBiobankConcordanceSocioeconomic statusRecord linkageCohort studyInformed consentFamily medicineSurgeryInternal medicineEnvironmental healthPathologyPsychology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.024
GPT teacher head0.325
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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