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THE CLINICAL EPIDEMIOLOGY OF CARDIOVASCULAR DISEASES IN CHRONIC KIDNEY DISEASE: Is Chronic Kidney Disease a Cardiovascular Disease Risk Factor?

2003· review· en· W2154761934 on OpenAlexaff
Bruce F. Culleton, Brenda R. Hemmelgarn

Bibliographic record

VenueSeminars in Dialysis · 2003
Typereview
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineKidney diseaseRisk factorDiseaseRenal functionComorbidityDialysisEpidemiologyIntensive care medicineInternal medicinePopulationCohort studyEnvironmental health

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is prevalent in patients with chronic kidney disease (CKD) and may account for 50% of all deaths. The recent Dialysis Outcomes Quality Initiative (DOQI) publication on the evaluation, classification, and stratification of CKD states that a reduced glomerular filtration rate (GFR) identifies individuals at greater risk for CVD and death. This risk is the result of traditional and nontraditional CVD risk factors. However, the relative contribution of these risk factors in the CKD population remains uncertain. Recently interest in kidney disease (reduced GFR) as an independent nontraditional risk factor for CVD has come to the forefront. Studies examining this potential link have included community-based cohort studies, studies in patients with extensive comorbidity, and reports in kidney transplant recipients. Herein, results from these studies are reviewed. The difference between an independent CVD risk factor and a causal CVD risk factor is discussed, with particular emphasis on the temporal association between exposure (GFR) and outcome (CVD and CVD death).

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)0.007
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.859
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.029
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.357
Teacher spread0.309 · 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; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreReview

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

Citations43
Published2003
Admission routes1
Has abstractyes

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