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THE CLINICAL EPIDEMIOLOGY OF CARDIOVASCULAR DISEASES IN CHRONIC KIDNEY DISEASE: Management of Heart Failure and Coronary Artery Disease in Patients with Chronic Kidney Disease

2003· review· en· W1919666989 on OpenAlexaff
S. Murphy

Bibliographic record

VenueSeminars in Dialysis · 2003
Typereview
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMedicineCardiologyCoronary artery diseaseInternal medicineKidney diseasePopulationHeart failureRevascularizationDiseaseIntensive care medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Cardiovascular disease (CVD) is a major contributor to the mortality and morbidity of patients who suffer from chronic kidney disease (CKD). Heart failure and ischemic heart disease (IHD) are both highly prevalent in this population. The diagnosis of myocardial dysfunction is usually based on echocardiography. As in the general population, systolic dysfunction is treated with a combination of diuretics, renin-angiotensin system blockade, and beta-receptor antagonists. Diastolic dysfunction is best managed by eliminating the cause. Non-invasive tests for coronary artery disease (CAD) may be less reliable in patients with renal disease compared with nonuremic patients. Medical therapy of IHD in this population is generally similar to that for other patient groups, but surgical revascularization appears to carry a higher risk of complications with poorer clinical outcomes. The choice of revascularization procedure (coronary artery bypass grafting versus percutaneous transluminal angioplasty) should be based on the specific coronary anatomy of a given patient as well as a consideration of other comorbid factors.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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 teacher head, not a consensus.

Study designObservational
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

Citations12
Published2003
Admission routes1
Has abstractyes

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