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Record W2949667798 · doi:10.1093/ndt/gfz096.fc061

FC061DIETARY PATTERNS AND MORTALITY IN ADULTS ON HEMODIALYSIS

2019· article· en· W2949667798 on OpenAlexaff
Valeria Saglimbene, Germaine Wong, Marinella Ruospo, Suetonia C. Palmer, Patrizia Natale, Vanessa García-Larsen, Juan Jesús Carrero, Peter Stenvinkel, Letizia Gargano, Marcello Tonelli, Amparo Bernat, Delia Timofte, Mariëtta Török, Anna Bednarek-Skublewska, Jua Duława, Paul Stroumza, Charlotta Wollheim, Jörgen Hegbrant, Jonathan C. Craig, Giovanni FM Strippoli

Bibliographic record

VenueNephrology Dialysis Transplantation · 2019
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineHemodialysisIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Clinical practice guidelines on dietary intake in patients treated with haemodialysis focus on restricting individual nutrients to avoid electrolyte complications. Evidence for whole dietary patterns and their association with clinical outcomes is of very low certainty due to sparse existing data. We aimed to evaluate the association of data driven dietary patterns with cardiovascular and all-cause mortality among adults treated with hemodialysis. METHODS: In the DIET-HD multinational cohort study, dietary composition of over 200 foods was ascertained using the GA2LEN food frequency questionnaire in 8110 adults treated with haemodialysis. In this analysis, dietary patterns were identified using principal components analysis. Participants received a score for each identified pattern with higher scores indicating closer resemblance of their diet to the identified pattern. The association of dietary pattern scores (as quartiles) with all-cause and cardiovascular mortality was estimated using Cox regression analyses, clustered by country and adjusted for comorbidity, demographic and life style characteristics. Estimates are presented as adjusted hazard ratios (aHR) with 95% confidence intervals (CI), using the lowest quartile score as the reference category. RESULTS: During a median follow up of 2.7 years (18,666 person-years), there were 2087 deaths (958 cardiovascular). Two dietary patterns, “fruit and vegetables-based” and “Western”, were identified by principal components analysis. The main food components of each dietary patient is shown in Figure 1. There was no evidence of an association of increasing concordance with the fruit and vegetable dietary pattern and cardiovascular mortality (aHR 0.94 (CI, 0.76-1.15), 0.83 (0.66-1.06) and 0.91 (0.69-1.21) for ascending score quartiles) or all-cause mortality (0.95 (0.83-1.09), 0.84 (0.71-0.99) and 0.87 (0.72-1.05)). Similarly there was no evidence of an association between a Western dietary pattern in ascending quartiles of dietary concordance and cardiovascular mortality (aHR 1.01 1.10 (0.90-1.35), 1.11 (0.87-1.41) and 1.09 (0.80-1.49) or all-cause mortality (1.01 (0.88-1.16), 1.00 (0.85-1.18) and 1.14 (0.93-1.41)). CONCLUSIONS: There appears to be little or no association between consumption of a fruit and vegetable-based or a Western diet with cardiovascular and all-cause mortality in patients on hemodialysis.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0030.000

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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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
Published2019
Admission routes1
Has abstractyes

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