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Record W4386191119 · doi:10.1101/2023.08.24.23294127

Reduced left ventricular function on cardiac MRI of SLE patients correlates with measures of disease activity and inflammation

2023· preprint· en· W4386191119 on OpenAlexaboutno aff
Audrey M. Hagiwara, Erica N. Montano, Gantseg Tumurkhuu, Moumita Bose, Marianne Bernardo, Daniel S. Berman, Galen Cook Wiens, Michael D. Nelson, Daniel J. Wallace, Janet Wei, Mariko Ishimori, C. Noel Bairey Merz, Caroline A. Jefferies

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Center for Research ResourcesDeutsches KrebsforschungszentrumNational Institute on AgingNational Heart, Lung, and Blood InstituteAdelson Family FoundationNational Institute of Allergy and Infectious DiseasesCedars-Sinai Medical Center
KeywordsInflammationCardiologyMedicineVentricular functionInternal medicineDiseaseCardiac function curveHeart failure

Abstract

fetched live from OpenAlex

Background: Women with SLE have an elevated risk of cardiovascular disease. Many women with SLE frequently report chest pain in the absence of obstructive coronary artery disease (CAD) due to coronary microvascular dysfunction (CMD), a form of ischemia with no obstructive CAD. Echocardiographic studies have shown that SLE patients have reduced left ventricular (LV) function, which may also correlate with higher SLE disease activity scores. As such, we used cardiac magnetic resonance imaging (cMRI) to investigate the relationship between SLE, related inflammatory biomarkers, and cardiac function in female SLE patients. Methods: We performed stress cMRI in women with SLE and chest pain with no obstructive CAD (n=13, all met ACR 1997 criteria,) and reference controls (n=22) using our published protocol. We evaluated LV function, tissue characterization (T1 mapping, ECV), and delayed enhancement, using CV142 software (Circle Cardiovascular Imaging Inc, Calgary, AB, Canada). Myocardial perfusion reserve index (MPRI) was calculated using our published protocol. SLEDAI and SLICC Damage Index (DI) were calculated per validated criteria. Serum samples were analyzed for inflammatory markers and autoantibodies. Wilcoxon rank-sum test was performed on clinical values with CMD and no CMD SLE subjects, and on cMRI values with all SLE subjects and controls. Correlation analysis was done on clinical values, and cMRI values on all SLE subjects. Results: Overall, 40% of SLE subjects had MPRI values < 1.84, consistent with CMD. Compared to controls, SLE subjects had significantly lower LVEF, and higher LVESVi and LVMi. Corresponding to this, radial, longitudinal, and circumferential strain were significantly lower in the SLE subjects. In correlation analysis of serum inflammatory biomarkers to cMRI values in the SLE subjects, SLICC DI was related to worse cardiac function (lower radial, circumferential and longitudinal strain) and higher T1 time. Additionally, fasting insulin and ESR were negatively correlated with LVMi. Fasting insulin also negatively correlated with ECV. CRP had a positive association with LVESV index and CI and a negative association with longitudinal strain. Conclusions: Among women with SLE with chest pain and no obstructive CAD, 40% have CMD. While evaluations of known inflammatory markers (such as CRP and ESR) predictably correlated with decreased cardiac function, our study found that decreased fasting insulin levels as a novel marker of diminished LV function. In addition, low insulin levels were observed to correlate with increased LVMi and ECV, suggesting a cardioprotective effect of insulin in SLE patients. We also noted that SLICC DI, an assessment of SLE damage, correlates with cardiac dysfunction in SLE. Our findings underline the potential of non-invasive cMRI as a tool for monitoring cardiovascular function in SLE, particularly in patients with high SLICC DI, ESR and CRP and low fasting insulin levels.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.243
Teacher spread0.225 · 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".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

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