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Record W4306254522 · doi:10.1093/eurheartj/ehac544.251

Ethnicity-specific myocardial remodelling in hypertensive heart disease by multi-parametric cardiovascular magnetic resonance

2022· article· en· W4306254522 on OpenAlexaboutno aff
Aqeel T Mohamed, Georgios Georgiopoulos, Luca Faconti, Clint Asher, Samuel Vennin, Ryan McNally, S Vasileios, Khaled Alfakih, P Lamata, Louise Keehn, Phil Chowienczyk, Pier Giorgio Masci

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineMagnetic resonance imagingHeart failureHypertensive heart diseaseBlood pressureRadiology

Abstract

fetched live from OpenAlex

Abstract Background Patients with systemic hypertension (HTN) of African ancestry (Afr-a) are at greater risk of incident heart failure (HF), hospitalisation and death than those of European ancestry (Eu-a). This has been related to higher prevalence of HTN-related target organ damage, including high level of circulating cardiac troponins, which is not fully explained by blood pressure level. Thus, one may speculate that Afr-a hypertensives have a higher tendency to develop myocardial damage in response to arterial afterload. However, myocardial composition differences between Afr-a and Eu-a hypertensives remain speculative. Purpose To investigate ethnic-specific differences in myocardial tissue composition in Eu-a and Afr-a hypertensives by multi-parametric cardiovascular magnetic resonance (CMR). Methods This cross-sectional study included 63 Afr-a and 47 Eu-a hypertensive patients. All patients underwent multi-parametric CMR (1.5-Tesla Aera, Siemens-Healthcare, Erlangen-Germany). Left (LV) and right ventricular (RV) volumes, mass and function, atrial dimensions, and myocardial tissue characterisation (including T1- and T2-mapping) were measured using a standardised imaging protocol, and post-processing recommendations from international scientific societies. Analysis was completed using a commercially available cardiac-software (CVI-42, Calgary-Canada). Central pulse-wave-velocity (PWV) between the ascending and proximal descending thoracic aorta was measured by high-temporal, resolution 2D phase-contrast velocity-encoded parasagittal cine images, using in-house MATLAB software. Results Although Afr-a were 5 years older than Eu-a hypertensives, cardiovascular risk factors, anthropometric, body composition and haemodynamic measures were similar between the two groups (Figure 1). Segmental PWV was greater in Afr-a than Eu-a patients (8.16±2.71 vs 6.97±2.82 m/s, P=0.044), underlying higher aortic stiffness in Afr-a hypertensives. Afr-a hypertensives also had greater LV mass and LV-mass/end-diastolic volume ratio than Eu-a (Figure 2), whilst no difference was observed in LV systolic/diastolic function. Native T1 relaxation time and synthetic extracellular volume were also similar between the two ethnicities, though T2 relaxation time was significantly higher in Afr-a hypertensives. Late gadolinium enhancement (LGE), a well-established metric of replacement fibrosis (scarring), was more prevalent in Afr-a than Eu-a hypertensives (14% vs 4%, P=0.001). In patients with LGE, the extent of LGE was higher in Afr-a than Eu-a hypertensives (Figure 2). Conclusion Afr-a hypertensives have higher arterial afterload, LV mass and remodelling than Eu-a, despite comparable mean blood pressure, body-mass-index, and body composition. These changes in LV structure and geometry were associated with higher T2 relaxation time, likely reflecting low-grade inflammation, as well as higher prevalence and extent of replacement myocardial fibrosis. Funding Acknowledgement Type of funding sources: None.

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)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.045
GPT teacher head0.270
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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