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Record W3044818031 · doi:10.1002/ehf2.12846

Assessment of Diastolic Dysfunction: Comparison of Different Cardiovascular Magnetic Resonance Techniques

2020· article· en· W3044818031 on OpenAlexaff
Josephine Kermer, Julius Traber, Wolfgang Utz, Pierre Hennig, Marius Menza, Bernd Jung, Andreas Greiser, Philipp Barckow, Florian von Knobelsdorff‐Brenkenhoff, Agnieszka Töpper, Edyta Błaszczyk, Jeanette Schulz‐Menger

Bibliographic record

VenueESC Heart Failure · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsCircle Cardiovascular Imaging
FundersCharité – Universitätsmedizin Berlin
KeywordsMedicineCardiologyInternal medicineEjection fractionDiastoleHeart failureReceiver operating characteristicMagnetic resonance imagingNatriuretic peptideStroke volumeNuclear medicineBlood pressureRadiology

Abstract

fetched live from OpenAlex

AIMS: Heart failure with preserved ejection fraction is still a diagnostic and therapeutic challenge, and accurate non-invasive diagnosis of left ventricular (LV) diastolic dysfunction (DD) remains difficult. The current study aimed at identifying the most informative cardiovascular magnetic resonance (CMR) parameters for the assessment of LVDD. METHODS AND RESULTS: We prospectively included 50 patients and classified them into three groups: with DD (DD+, n = 15), without (DD-, n = 26), and uncertain (DD±, n = 9). Diagnosis of DD was based on echocardiographic E/E', invasive LV end-diastolic pressure, and N-terminal pro-brain natriuretic peptide. CMR was performed at 1.5 T to assess LV and left atrial (LA) morphology, LV diastolic strain rate (SR) by tissue tracking and tagging, myocardial peak velocities by tissue phase mapping, and transmitral inflow profile using phase contrast techniques. Statistics were performed only on definitive DD+ and DD- (total number 41). DD+ showed enlarged LA with LA end-diastolic volume/height performing best to identify DD+ with a cut-off value of ≥0.52 mL/cm (sensitivity = 0.71, specificity = 0.84, and area under the receiver operating characteristic curve = 0.75). DD+ showed significantly reduced radial (inferolateral E peak: DD-: -14.5 ± 6.5%/s vs. DD+: -10.9 ± 5.9%/s, P = 0.04; anterolateral A peak: DD-: -4.2 ± 1.6%/s vs. DD+: -3.1 ± 1.4%/s, P = 0.04) and circumferential (inferolateral A peak: DD-: 3.8 ± 1.2%/s vs. DD+: 2.8 ± 0.8%/s, P = 0.007; anterolateral A peak: DD-: 3.5 ± 1.2%/s vs. DD+: 2.5 ± 0.8%/s, P = 0.048) SR in the basal lateral wall assessed by tissue tracking. In the same segments, DD+ showed lower peak myocardial velocity by tissue phase mapping (inferolateral radial peak: DD-: -3.6 ± 0.7 ms vs. DD+: -2.8 ± 1.0 ms, P = 0.017; anterolateral longitudinal peak: DD-: -5.0 ± 1.8 ms vs. DD+: -3.4 ± 1.4 ms, P = 0.006). Tagging revealed reduced global longitudinal SR in DD+ (DD-: 45.8 ± 12.0%/s vs. DD+: 34.8 ± 9.2%/s, P = 0.022). Global circumferential and radial SR by tissue tracking and tagging, LV morphology, and transmitral flow did not differ between DD+ and DD-. CONCLUSIONS: Left atrial size and regional quantitative myocardial deformation applying CMR identified best patients with DD.

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 score0.456
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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

Citations17
Published2020
Admission routes1
Has abstractyes

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