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Record W2564945383 · doi:10.1093/ndt/gfw171.15

SP444INTERNATIONAL VARIATIONS IN THE EXPERIENCE OF PATIENTS ON PERITONEAL DIALYSIS (PD) IN THE PERITONEAL DIALYSIS OUTCOMES AND PRACTICE PATTERNS STUDY (PDOPPS)

2016· article· en· W2564945383 on OpenAlexaffabout
Fredric O. Finkelstein, Junhui Zhao, Brian Bieber, Sarbjit V. Jassal, Hal Morgenstern, Kenji Tsuchida, Edwina A. Brown, David W. Johnson, Francesca Tentori

Bibliographic record

VenueNephrology Dialysis Transplantation · 2016
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicinePeritoneal dialysisDialysisHemodialysisIntensive care medicineInternal medicineUrology

Abstract

fetched live from OpenAlex

Introduction and Aims: Increasing attention is being focused on the experience of dialysis patients, both as a central component of the patients well-being and as predictor of other clinical outcomes. As in the hemodialysis population, it is likely that patient-reported outcomes (PRO) in PD patients vary across countries. We present comparisons of PRO measures across countries among participants in PDOPPS, which is the largest international study of PD patients to date. Methods: The PDOPPS is a prospective cohort study underway in the US, Canada, Japan, Australia, and the UK in collaboration with the International Society for Peritoneal Dialysis (ISPD) . Here we present cross-sectional analyses based on data collected to date at patient enrollment in the first 3 countries. PRO measures include the physical (PCS) and mental (MCS) component summary scores of the SF-12 survey, functional status measured in the Kidney Disease Quality of Life questionnaire, and the Center for Epidemiologic Studies Depression (CES-D) scale. Across countries differences in means PCS, MCS, and CES-D scores and prevalence of CES-D ≥ 10 (indicative of possible depression) and functional status were estimated using linear regressionwere compared and modified Poisson regression, with progressive adjustment (model 1: age, sex, race; model 2: vintage, diabetes, coronary heart disease, congestive heart failure, other cardiovascular disease, serum albumin, phosphorus and hemoglobin).

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)0.001
metaresearch head score (Gemma)0.003
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.299
Teacher spread0.283 · 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".

Quick stats

Citations0
Published2016
Admission routes2
Has abstractyes

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