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Record W2804489712 · doi:10.1093/ndt/gfy104.fp483

FP483PATIENT-REPORTED DISADVANTAGES OF PERITONEAL DIALYSIS: RESULTS FROM THE PERITONEAL DIALYSIS OUTCOMES AND PRACTICE PATTERNS STUDY (PDOPPS)

2018· article· en· W2804489712 on OpenAlexaffabout
Nidhi Sukul, Junhui Zhao, Douglas S. Fuller, Angelo Karaboyas, Brian Bieber, James A. Sloand, Lalita Subramanian, David W. Johnson, Matthew J. Oliver, Kriang Tungsanga, Tadashi Tomo, Rachael L. Morton, Hal Morgenstern, Bruce Robinson, Jeffrey Perl

Bibliographic record

VenueNephrology Dialysis Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSt. Michael's HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePeritoneal dialysisIntensive care medicineDialysisInternal medicineUrology

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: Home-based peritoneal dialysis (PD) offers several advantages and disadvantages. We sought to better understand patient-reported disadvantages of PD and their relation with clinical outcomes. METHODS: Using the PDOPPS (2014-17), a prospective cohort study of PD treatment and outcomes in Australia, Canada, Japan, New Zealand, Thailand, the United Kingdom, and the United States, we asked patients to rate 17 aspects of their PD treatment experienced as a disadvantage, advantage, or neither. A patient-level disadvantage score (DS) was calculated as the proportion of aspects rated as a disadvantage. We examined the adjusted associations of both the individual reported disadvantages and the overall DS with health-related quality of life, depressive symptoms, transfer to HD, and all-cause mortality. RESULTS: Of the 2705 patients with complete data on the 17 aspects, the most commonly cited disadvantages were feeling full with fluid in the abdomen (42%) and storage space taken up by PD supplies (32%). Among the 8 most commonly cited disadvantages, none were associated with increased mortality, transfer to HD, or the composite outcome of mortality or transfer to HD, with the exception of space taken up by PD supplies, which was associated with increased risk of transfer to HD and the composite outcome (adjusted hazard ratios [95% CI]: 1.23 [1.03, 1.48] and 1.19 [1.01, 1.39], respectively). The DS was strongly associated with poorer quality-of-life scores and more depressive symptoms (Figure 1A). Patients with a DS of >30% had a higher rate of transfer to HD, but a weakly positive association with mortality (Figure 1B), compared to the reference DS of 0%. CONCLUSIONS: Increasing patient-reported disadvantages of PD are associated with poor quality of life and increased depressive symptoms, possibly due in part to reverse causation, and longitudinally with an increased risk of transfer to HD. Solution storage was the second most common reported disadvantage and was associated with an increased risk of transfer to HD. Taken together, strategies to reduce patient reported disadvantages of PD should include addressing PD solution storage, which may improve the PD patient experience, and potentially reduce the risk of transfer to HD.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.019
GPT teacher head0.307
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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