Why the study?
Does low indexed psoas muscle area predict increased cardiac and all-cause mortality in patients undergoing TAVI?
Does low indexed psoas muscle area predict increased cardiac and all-cause mortality in patients undergoing TAVI?
Low indexed psoas muscle area on routine pre-procedural CT is an independent predictor of cardiac and all-cause mortality in women undergoing TAVI, and improves the predictive value of standard surgical risk scores.
Low iPMA may identify higher-risk women for TAVI; hypothesis-generating for frailty measures in risk models and requires validation.
OBJECTIVES: The aim of this study was to assess the predictive value of PMA measurement for mortality. BACKGROUND: Current surgical risk stratification have limited predictive value in the transcatheter aortic valve implantation (TAVI) population. In TAVI workup, a CT scan is routinely performed but body composition is not analyzed. Psoas muscle area (PMA) reflects a patient's global muscle mass and accordingly PMA might serve as a quantifiable frailty measure. METHODS: Multi-slice computed tomography scans (between 2010 and 2016) of 583 consecutive TAVI patients were reviewed. Patients were divided into equal sex-specific tertiles (low, mid, and high) according to an indexed PMA. Hazard ratios (HR) and their confidence intervals (CI) were determined for cardiac and all-cause mortality after TAVI. RESULTS: Low iPMA was associated with cardiac and all-cause mortality in females. One-year adjusted cardiac mortality HR in females for mid-iPMA and high-iPMA were 0.14 [95%CI, 0.05-0.45] and 0.40 [95%CI, 0.15-0.97], respectively. Similar effects were observed for 30-day and 2-years cardiac and all-cause mortality. In females, adding iPMA to surgical risk scores improved the predictive value for 1-year mortality. C-statistics changed from 0.63 [CI = 0.54-0.73] to 0.67 [CI: 0.58-0.75] for EuroSCORE II and from 0.67 [CI: 0.59-0.77] to 0.72 [CI: 0.63-0.80] for STS-PROM. CONCLUSIONS: Particularly in females, low iPMA is independently associated with an higher all-cause and cardiac mortality. Prospective studies should confirm whether PMA or other body composition parameters should be extracted automatically from CT-scans to include in clinical decision making and outcome prediction for TAVI.
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Mourik et al. (2018) studied this question.
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