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Record W7005000695

PERITONEAL DIALYSIS TIME ON THERAPY AND REGIONAL DIFFERENCES IN DEATH, TRANSFER TO HEMODIALYSIS AND KIDNEY TRANSPLANTATION: RESULTS FROM THE PDOPPS

2021· other· en· W7005000695 on OpenAlexaboutno aff

Bibliographic record

VenueKeele Research Repository (Keele University) · 2021
Typeother
Languageen
FieldMaterials Science
TopicPhytochemistry and Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationHemodialysisPeritoneal dialysisDialysisKidney diseaseProportional hazards model
DOInot available

Abstract

fetched live from OpenAlex

Background and Aims Comparing and interpreting regional differences in peritoneal dialysis (PD) time on therapy needs to consider differences in the rates of permanent transfer to hemodialysis (HDT), death or kidney transplantation. Here we describe these outcomes among countries in the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS), as well as reasons for PD discontinuation. Method PDOPPS is a prospective cohort study of randomly selected patients across national samples of PD facilities from Australia/New Zealand (A/NZ), Canada, Japan, Thailand, the UK, and the US. Fine and Gray models were used on a population of 7115 patients, of varying PD vintages at study entry [median (IQR) vintage = 0.82 yrs (0.21, 2.03)], to analyse the cumulative incidence from PD start of transplantation, HDT, or death (on PD or within 7 days of transfer to HD). This allows for the determination of the % of patients remaining on PD at each PD vintage referred to as Time on Therapy (ToT). Models were left truncated to account for PD vintage at time of study enrollment. HDT was defined as no return from HD therapy within 12 weeks of transferring to HD. Cox models were used to calculate hazard ratios (HR) for death accounting for facility clustering and adjusted for patient age, sex, US black race, heart disease, diabetes, psychiatric disorder, prior HD experience, urine volume, and transplant waitlist referral. Results Mean patient age ranged from 56 yrs in Thailand to 64 yrs in Japan (Figure). Overall, 1261 patients transferred to HD, 76 patients transferred to HD/PD hybrid therapy, 900 patients died and 506 were transplanted during follow-up. By 3 years, the % of patients remaining on PD ranged from 25% in UK, 34-40% in A/NZ, Canada and US, to 47% in Thailand, and 54% in Japan (Figure). The much lower % of patients on PD at 3 yrs in the UK vs Japan was largely due to the high % of patients transplanted in the UK vs Japan: % transplanted ranged from 2% in Japan and Thailand to 32% in the UK at 3 yrs. When defining a ‘poor outcome’ as either death or HDT: (1) the % of patients still on PD or having been transplanted were quite similar across all 6 countries, and (2) death was a much larger proportion of this ‘poor outcome’ in Thailand vs other countries. Similar risks of HDT were seen across all countries except Thailand which displayed much lower risks of HDT. This finding changed little with covariate adjustment (not shown). Infection, reported as primary HDT cause, varied from 30% (Canada) to 66% (Thailand) of cases, and insufficient solute or water clearance as primary HDT cause ranged from 6% (Thailand) to 44% (Japan) of cases (not shown). In Cox models, the adjusted HR of death, compared to the US, was higher in Thailand [1.55 (1.17-2.06)], lower in Canada [0.75 (0.61-0.92)], A/NZ [0.60 (0.47-0.78)], and Japan [0.36 (0.27-0.48)], and close to 1 in UK [0.98 (0.75-1.28)]. Conclusion Time on PD therapy differed considerably across countries. This was mainly due to large country differences in proportion transplanted, so that transplantation has a greater impact on country variability in ToT than HDT and death. Risk of death varied greatly across countries, particularly when accounting for case-mix. With the exception of Thailand, differences between countries in risk of HDT were modest. Marked differences in recorded reasons for HDT merit additional study.

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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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.064
GPT teacher head0.265
Teacher spread0.201 · 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 designBench or experimental
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

Citations0
Published2021
Admission routes1
Has abstractyes

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