Skip to main navigation Skip to search Skip to main content

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

  • Vassilios S. Vassiliou
  • , Menelaos Pavlou
  • , Tamir Malley
  • , Brian P. Halliday
  • , Vasiliki Tsampasian
  • , Claire E. Raphael
  • , Gary Tse
  • , Miguel Silva Vieira
  • , Dominique Auger
  • , Russell Everett
  • , Calvin Chin
  • , Francisco Alpendurada
  • , John Pepper
  • , Dudley J. Pennell
  • , David E. Newby
  • , Andrew Jabbour
  • , Marc R. Dweck
  • , Sanjay K. Prasad
    • University of East Anglia

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)

    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.
    Original languageEnglish
    JournalScientific Reports
    DOIs
    Publication statusPublished - 12 Oct 2021

    Keywords

    • Cardiology
    • Interventional cardiology
    • Risk factors

    Fingerprint

    Dive into the research topics of 'A novel cardiovascular magnetic resonance risk score for predicting mortality following surgical aortic valve replacement'. Together they form a unique fingerprint.

    Cite this