Usefulness of Psoas Muscle Area and Volume and Frailty Scoring to Predict Outcomes After Transcatheter Aortic Valve Implantation.

Am J Cardiol

Second Department of Cardiology, Jagiellonian University Medical College, Krakow, Poland; Second Department of Cardiology and Cardiovascular Interventions, University Hospital, Krakow, Poland; Department of Interventional Cardiology, Institute of Cardiology, Jagiellonian University Medical College, Krakow, Poland.

Published: July 2018

Numerous scales were implemented for frailty assessment. However, limited evidence and recommendations for frailty tools for everyday clinical practice in patients who underwent transcatheter aortic valve implantation (TAVI) exist. Thus, we aimed to determine the long-term predictive value of different frailty scores and objective assessment of sarcopenia by imaging techniques in patients after TAVI. Frailty indexes according to Valve Academic Research Consortium-2 (VARC-2) recommendations, as well as other available scales of frailty, were assessed at baseline. Sarcopenia was evaluated with psoas muscle area (PSA) and psoas muscle volume (PSV) using computed tomography (CT) scans. The primary end point was 12-month all-cause mortality. We enrolled 153 patients who underwent TAVI with analyzable CT scans and complete frailty data. The median of PSA normalized for body surface area was 2,581.1 (2,214.9 to 2,654.9) mm/m, and the median of normalized PSV was 338.8 (288.1-365.6) cc/m. At 12 months, all-cause mortality and new-onset atrial fibrillation were highest in the lowest tertile of normalized PSA. In the receiver operating characteristic analysis, all the tested frailty indexes, as well as PSA and PSV, were good predictors of 12-month all-cause mortality after TAVI with the highest area under the curve value for PSA and PSV normalized for body surface area. In conclusion, normalized PSA and PSV values are strong predictors of long-term mortality after TAVI. CT evaluation of psoas muscles could be incorporated to preprocedural comprehensive clinical models used for prediction of outcomes in patients scheduled for TAVI.

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http://dx.doi.org/10.1016/j.amjcard.2018.03.020DOI Listing

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