Knight, Daniel S;
Karia, Nina;
Cole, Alice R;
Maclean, Rory H;
Brown, James T;
Masi, Ambra;
Patel, Rishi K;
... Muthurangu, Vivek; + view all
(2022)
Distinct cardiovascular phenotypes are associated with prognosis in systemic sclerosis: a cardiovascular magnetic resonance study.
European Heart Journal - Cardiovascular Imaging
, Article jeac120. 10.1093/ehjci/jeac120.
Preview |
Text
Denton_jeac120.pdf Download (1MB) | Preview |
Abstract
AIMS: Cardiovascular involvement in systemic sclerosis (SSc) is heterogeneous and ill-defined. This study aimed to: (i) discover cardiac phenotypes in SSc by cardiovascular magnetic resonance (CMR); (ii) provide a CMR-based algorithm for phenotypic classification; and (iii) examine for associations between phenotypes and mortality. METHODS AND RESULTS: A retrospective, single-centre, observational study of 260 SSc patients who underwent clinically indicated CMR including native myocardial T1 and T2 mapping from 2016 to 2019 was performed. Agglomerative hierarchical clustering using only CMR variables revealed five clusters of SSc patients with shared CMR characteristics: dilated right hearts with right ventricular failure (RVF); biventricular failure dilatation and dysfunction (BVF); and normal function with average cavity (NF-AC), normal function with small cavity (NF-SC), and normal function with large cavity (NF-LC) sizes. Phenotypes did not co-segregate with clinical or antibody classifications. A CMR-based decision tree for phenotype classification was created. Sixty-three (24%) patients died during a median follow-up period of 3.4 years. After adjustment for age and presence of pulmonary hypertension (PH), independent CMR predictors of all-cause mortality were native T1 (P < 0.001) and right ventricular ejection fraction (RVEF) (P = 0.0032). NF-SC and NF-AC groups had more favourable prognoses (P≤0.036) than the other three groups which had no differences in prognoses between them (P > 0.14). Hazard ratios (HR) were statistically significant for RVF (HR = 8.9, P < 0.001), BVF (HR = 5.2, P = 0.006), and NF-LC (HR = 4.9, P = 0.002) groups. The NF-LC group remained significantly predictive of mortality after adjusting for RVEF, native T1, and PH diagnosis (P = 0.0046). CONCLUSION: We identified five CMR-defined cardiac SSc phenotypes that did not co-segregate with clinical data and had distinct outcomes, offering opportunities for a more precision-medicine based management approach.
Type: | Article |
---|---|
Title: | Distinct cardiovascular phenotypes are associated with prognosis in systemic sclerosis: a cardiovascular magnetic resonance study |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1093/ehjci/jeac120 |
Publisher version: | https://doi.org/10.1093/ehjci/jeac120 |
Language: | English |
Additional information: | © The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
Keywords: | T1 mapping, cardiovascular magnetic resonance, cluster analysis, prognosis, pulmonary hypertension, systemic sclerosis |
UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Inflammation UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10151312 |
Archive Staff Only
View Item |