A novel cardiovascular magnetic resonance risk score for predicting mortality following surgical aortic valve replacement

Vassiliou, Vassilios, Pavlou, Menelaos, Malley, Tamir, Halliday, Brian P., Tsampasian, Vasiliki, Raphael, Claire E., Tse, Gary, Vieira, Miguel Silva, Auger, Dominique, Everett, Russell J., Chin, Calvin W. L., Alpendurada, Francisco, Pepper, John R., Pennell, Dudley J., Newby, David, Jabbour, Andrew, Dweck, Marc R. and Prasad, Sanjay K. (2021) A novel cardiovascular magnetic resonance risk score for predicting mortality following surgical aortic valve replacement. Scientific Reports, 11. ISSN 2045-2322

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Abstract

The increasing prevalence of patients with aortic stenosis worldwide highlights a clinical need for improved and accurate prediction of clinical outcomes following surgery. We investigated patient demographic and cardiovascular magnetic resonance (CMR) characteristics to formulate a dedicated risk score estimating long-term survival following surgery. We recruited consecutive patients undergoing CMR with gadolinium administration prior to surgical aortic valve replacement from 2003 to 2016 in two UK centres. The outcome was overall mortality. A total of 250 patients were included (68 ± 12 years, male 185 (60%), with pre-operative mean aortic valve area 0.93 ± 0.32cm2, LVEF 62 ± 17%) and followed for 6.0 ± 3.3 years. Sixty-one deaths occurred, with 10-year mortality of 23.6%. Multivariable analysis showed that increasing age (HR 1.04, P = 0.005), use of antiplatelet therapy (HR 0.54, P = 0.027), presence of infarction or midwall late gadolinium enhancement (HR 1.52 and HR 2.14 respectively, combined P = 0.12), higher indexed left ventricular stroke volume (HR 0.98, P = 0.043) and higher left atrial ejection fraction (HR 0.98, P = 0.083) associated with mortality and developed a risk score with good discrimination. This is the first dedicated risk prediction score for patients with aortic stenosis undergoing surgical aortic valve replacement providing an individualised estimate for overall mortality. This model can help clinicians individualising medical and surgical care. Trial Registration ClinicalTrials.gov Identifier: NCT00930735 and ClinicalTrials.gov Identifier: NCT01755936.

Item Type: Article
Additional Information: Funding Information: This work was supported by the NIHR Biomedical Research Unit, Royal Brompton and Harefield Hospitals and Imperial College London, London, United Kingdom, and the Rosetrees Charity Trust, London (VSV, SKP), the British Heart Foundation (BH FS/15/29/31492; CER FS/14/13/30619; RE DEN CH/09/002; MRD FS/14/78/31020); DEN was also supported by a Wellcome Trust Senior Investigator Award (WT103782AIA).
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
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Depositing User: LivePure Connector
Date Deposited: 15 Oct 2021 01:13
Last Modified: 03 Dec 2021 01:42
URI: https://ueaeprints.uea.ac.uk/id/eprint/81717
DOI: 10.1038/s41598-021-99788-7

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