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Record W1600778249 · doi:10.1186/1532-429x-17-s1-p116

Myocardial oxygenation is impaired in advanced chronic kidney disease and renal transplant patients

2015· article· en· W1600778249 on OpenAlexaff
S. Parnham, Jonathan Gleadle, Darryl P. Leong, Suchi Grover, Rebecca Perry, Craig Bradbrook, Richard Woodman, Carmine G. De Pasquale, Joseph B. Selvanayagam

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2015
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsPopulation Health Research Institute
FundersFlinders University
KeywordsMedicineCardiologyInternal medicineKidney diseaseCoronary artery diseaseAngiologyAsymptomaticMyocardial infarctionLeft ventricular hypertrophyOxygenationPopulationBlood pressure

Abstract

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Coronary artery disease (CAD) and left ventricular hypertrophy are prevalent in the chronic kidney disease (CKD) and renal transplant population. Advances in cardiovascular magnetic resonance (CMR) with the blood oxygen level-dependent (BOLD) technique provides unprecedented capability to assess myocardial oxygenation as a measure of ischaemia. We hypothesised that myocardial oxygenation would be reduced in advanced CKD and renal transplant patients and may provide a novel strategy for assessing myocardial ischaemia. We prospectively studied 20 advanced CKD subjects (8 dialysis group with median eGFR 9.5 (range 5-37) ml/min and 12 CKD group with median eGFR 14 (range 8-18) ml/min), 8 renal transplant (RT) recipients with median eGFR 74.5 (range 57-114) ml/min and 7 hypertensive (HT) controls with median eGFR 107 (range 57-144) ml/min. All patients were asymptomatic for CAD and none had prior history of CAD. All groups had cine and BOLD CMR at 3T, and RT and HT groups also had late gadolinium CMR to assess infarction/replacement fibrosis. CKD group additionally underwent 2D echocardiography strain to assess fibrosis. Myocardial oxygenation was measured at rest and under stress with adenosine (140 µg/kg/min) using BOLD Signal Intensity (SI). Analyses were performed using linear mixed models. A total of 1074 myocardial segments of the advanced CKD group [522 myocardial segments of dialysis group and 552 myocardial segments of CKD group], 456 myocardial segments of RT and 324 myocardial segments of HT controls were analysed and compared using linear mixed modeling. Mean interventricular septal thickness and left ventricular mass indexed to body surface area was similar between the groups (LV septum advanced CKD 1.2 ± 0.3 cm vs RT 1.2 ± 0.2 cm vs HT 1.1 ± 0.3 cm, p>NS; LV mass index advanced CKD 76 ± 22 g/m2vs RT 67 ± 9 g/m2 vs HT 63 ± 9 g/m2, p>NS). None of the advanced CKD group had impaired global longitudinal strain (GLS) (mean GLS -18.39) and none of the RT/HT groups had late gadolinium hyperenhancement. The mean BOLD SI change was lower in advanced CKD and RT groups compared to HT controls (-0.75 ± 8.82 versus 15.86 ± 9.56, p<0.0001 and 6.57 ± 6.99 versus 15.86 ± 9.56, p=0.033, respectively). The global myocardial BOLD SI change was also lower in the advanced CKD subjects compared to RT recipients (p=0.045). In the advanced CKD and RT groups, the BOLD SI Change was associated with eGFR (β= 0.1, 95%CI= 0.03 to 0.17, p<0.01). Our study suggests myocardial oxygenation is impaired in advanced chronic kidney disease patients and renal transplant recipients, and unlikely to be related to LVH or myocardial scarring. The impaired myocardial oxygenation may be associated with declining renal function. Non-contrast BOLD CMR is a promising tool to detect myocardial ischaemia in advanced chronic kidney disease population.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.246
Teacher spread0.235 · 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 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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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