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Record W2023789643 · doi:10.1159/000086221

Clinical Epidemiology of Cardiovascular Disease in Chronic Kidney Disease

2005· review· en· W2023789643 on OpenAlexaff
Kiran Kaur Kundhal, Charmaine E. Lok

Bibliographic record

VenueNephron Clinical Practice · 2005
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineKidney diseaseEpidemiologyDiseaseIntensive care medicineNephrologyRisk factorRenal functionInternal medicineIncidence (geometry)

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is the most common cause of death in patients with chronic kidney disease (CKD) and end-stage renal disease (ESRD). The clinical epidemiology of CVD in CKD is challenging due to a prior lack of standardized definitions of CKD, inconsistent measures of renal function, and possible alternative effects of 'traditional' CVD risk factors in patients with CKD. These challenges add to the complexity of the role of renal impairment as the cause or the consequence of cardiovascular disease. The goal of this review is to summarize the current evidence on: (1) the incidence and prevalence of CVD in chronic renal insufficiency and in ESRD, (2) risk factors for CVD in CKD, (3) the outcomes of patients with renal failure with CVD, and (4) CKD as a risk factor for CVD. The epidemiological associations implicating the huge burden of CVD throughout all stages of CKD highlight the need to better understand and implement adequate screening, and diagnostic and treatment strategies.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.007
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.283
GPT teacher head0.546
Teacher spread0.263 · 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 designNot applicable
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

Citations76
Published2005
Admission routes1
Has abstractyes

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