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Record W3001511372 · doi:10.1177/0896860819895356

International comparison of peritoneal dialysis prescriptions from the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS)

2020· article· en· W3001511372 on OpenAlexaffabout
Angela Yee‐Moon Wang, Junhui Zhao, Brian Bieber, Talerngsak Kanjanabuch, Martin Wilkie, Mark R. Marshall, Hideki Kawanishi, Jeffrey Perl, Simon Davies

Bibliographic record

VenuePeritoneal Dialysis International · 2020
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersKidney Research UK
KeywordsMedicinePeritoneal dialysisMedical prescriptionIcodextrinDialysis adequacyDialysisContinuous ambulatory peritoneal dialysisKt/VUrologyInternal medicineIntensive care medicinePharmacology

Abstract

fetched live from OpenAlex

BACKGROUND: = 4657) from Australia/New Zealand (A/NZ), Canada, Japan, Thailand, United Kingdom (UK), and United States (US). RESULTS: CAPD was more commonly used in Thailand and Japan, while APD predominated over CAPD in A/NZ, Canada, the US, and the UK. Total prescribed PD volume normalized to the surface area was the highest in Thailand and the lowest in Japan (for both APD and CAPD) and the UK (for CAPD). PD patients from Thailand had the lowest residual urine volume and residual renal urea clearance, yet achieved the highest dialysis urea clearance. Japanese patients had the lowest dialysis urea clearances for both APD and CAPD. Despite having similar urine volumes to patients in A/NZ, Canada, Japan, and the UK, US CAPD and APD patients used 2.5% and 3.86% glucose PD solutions more frequently, whereas fewer than 25% of these patients used icodextrin. Over half of the patients in A/NZ, Canada, the UK, and Japan used icodextrin, whereas it was hardly used in Thailand. Japan and Thailand were more likely to use 1.5% glucose solutions for their PD prescription. CONCLUSIONS: There are considerable international variations in PD modality use and prescription patterns that translate into important differences in achieved dialysis clearances. Ongoing recruitment of additional PDOPPS participants and accrual of follow-up time will allow us to test the associations between specific PD prescription regimens and clinical and patient-reported outcomes.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.350
Teacher spread0.304 · 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.

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

Citations47
Published2020
Admission routes2
Has abstractyes

Explore more

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