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Inadequate Treatment of Cardiovascular Disease and Cardiovascular Disease Risk Factors in Dialysis Patients: A Commentary

2004· editorial· en· W1839838842 on OpenAlexaff
Bruce F. Culleton, Brenda R. Hemmelgarn

Bibliographic record

VenueSeminars in Dialysis · 2004
Typeeditorial
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDiseaseIntensive care medicineDialysisEnd stage renal diseasePopulationIntervention (counseling)Internal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in patients with end-stage renal disease (ESRD). Despite its significant impact on health outcomes, which would imply a need for aggressive intervention, both CVD and CVD risk factors are inadequately treated in this patient population. The reasons for this inadequate treatment are unclear. This article reviews the contribution of traditional risk factors to the burden of CVD in ESRD patients, outlines the evidence regarding undertreatment of CVD and traditional CVD risk factors, and identifies potential factors that may be responsible for inadequate cardiovascular care in ESRD patients.

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)0.007
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.023
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0040.005
Open science0.0040.001
Research integrity0.0230.032
Insufficient payload (model declined to judge)0.0050.004

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 head0.007
GPT teacher head0.230
Teacher spread0.222 · 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
GenreEditorial

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

Citations14
Published2004
Admission routes1
Has abstractyes

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