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Record W2804993590 · doi:10.1093/ndt/gfy104.sp532

SP532THE ASSOCIATION OF FUNCTIONAL STATUS WITH MORTALITY AND DIALYSIS MODALITY CHANGE: RESULTS FROM THE PERITONEAL DIALYSIS OUTCOMES AND PRACTICE PATTERNS STUDY (PDOPPS)

2018· article· en· W2804993590 on OpenAlexaffabout
Karthik Tennankore, Junhui Zhao, Angelo Karaboyas, Brian Bieber, Bruce Robinson, Hal Morgenstern, Sarbjit V. Jassal, Fredric O. Finkelstein, Talerngsak Kanjanabuch, Areewan Cheawchanwattana, Ronald L. Pisoni, James A. Sloand, Jeffrey Perl

Bibliographic record

VenueNephrology Dialysis Transplantation · 2018
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsSt. Michael's HospitalUniversity Health NetworkDalhousie University
Fundersnot available
KeywordsMedicinePeritoneal dialysisDialysisIntensive care medicineModality (human–computer interaction)HemodialysisInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: Functional impairment is associated with a higher mortality risk among hemodialysis (HD) patients. We examined the prevalence of functional impairment in peritoneal dialysis (PD) patients, its variation by country, and its association with mortality and permanent transfer to HD. METHODS: We analyzed prevalent PD patients from the 7 initial countries in the PDOPPS (2014-17), a prospective cohort study of PD treatment and outcomes in Australia, Canada, Japan, New Zealand, Thailand, the United Kingdom (UK), and the United States (US). Functional status (FS) was assessed by self-reports of 8 instrumental and 5 basic activities of daily living based on the Lawton-Brody and the Katz questionnaires. Summary FS scores ranging from 1.25 (most dependent) to 13 (independent) were based on the patient’s ability to perform each activity with or without assistance. Logistic regression was used to compare the prevalence odds of FS score <11 vs ≥11 among countries, and Cox regression was used to estimate the hazard ratio (HR) for the effect of FS score on 3 outcomes: all-cause mortality, transfer to HD (censoring at death), and the composite of both; all analyses adjusted for several factors (Figure). RESULTS: Of the 2,585 patients with complete data on FS, the distribution of scores was 48% with 13, 32% 11-<13, 14% 8-<11, and 6% <8. Patients with a FS score <11 were older and had more comorbidities than those with FS 11+. Compared with the US, the adjusted odds ratio (95% CI) for a FS score <11 was 4.2 (2.4, 7.5) in Thailand, 1.9 (1.1, 3.3) in the UK, and close to 1 in the other 4 countries. There was a strong monotonic association between FS score and mortality (HR [95% CI] for FS score <8 vs. 13 = 3.7 [2.3, 6.0], FS score 8-<11 vs. 13 = 3.0 [2.1, 4.2]), but no association between FS score and transfer to HD (Figure). CONCLUSIONS: A greater prevalence of functional impairment among PD patients in Thailand and the UK may reflect differences in the case-mix of patients treated with PD. The association between greater functional impairment and increased mortality is similar to that observed in HD patients. Permanent transfer to HD does not seem to depend on functional status. This raises the possibility that impaired FS should not preclude the use of PD, i.e., that concerns of a heightened risk of technique failure leading to a permanent transfer to HD may be unfounded.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
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 head0.038
GPT teacher head0.305
Teacher spread0.268 · 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
Published2018
Admission routes2
Has abstractyes

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