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Poor correlation between coronary artery calcification and obstructive coronary artery disease in an end‐stage renal disease patient

2008· article· en· W2063023281 on OpenAlexvenueno aff
Lili Tong, Rajnish Mehrotra, David M. Shavelle, Matthew J. Budoff, Sharon G. Adler

Bibliographic record

VenueHemodialysis International · 2008
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsnot available
FundersNational Center for Research Resources
KeywordsMedicineCardiologyInternal medicineCoronary artery diseaseHemodialysisAsymptomaticKidney diseaseDialysisCalcificationEnd stage renal diseaseCoronary arteriesDiabetes mellitusPopulationCoronary Calcium ScoreArteryRadiologyCalcinosis

Abstract

fetched live from OpenAlex

Vascular calcification is highly prevalent and often severe in patients with chronic kidney disease. Arterial calcification in patients with chronic kidney disease can result from the deposition of mineral along the intimal layer of arteries in conjunction with atheromatous plaques or from calcium deposition in the medial wall of arteries, also known as Monckeberg's sclerosis. Whether coronary artery calcium scores as measured by electron beam computed tomography correlate with occlusive atherosclerotic disease in the dialysis population is uncertain. Here we report a case of an asymptomatic patient with diabetes mellitus and end-stage renal disease undergoing maintenance hemodialysis, who was found to have extremely elevated coronary artery calcium scores on electron beam computed tomography, but varied degrees of atherosclerotic plaque in her coronary arteries on coronary angiography. This suggests that in addition to the calcification anticipated in a remodeled intima, a proportion of the calcification is also likely to be in the arterial media. Thus, this case demonstrates that even an extremely high coronary calcium score may not be a satisfactory surrogate marker for obstructive atherosclerosis in elderly diabetic dialysis 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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.013
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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.

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".

Quick stats

Citations23
Published2008
Admission routes1
Has abstractyes

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