Our results suggest that QMLT alone with our current protocol may not accurately identify patients with low muscle mass.

The loss of muscle mass is a defining characteristic of malnutrition, and there is ongoing interest in the assessment of lean tissue at the bedside. Globally, bioimpedance techniques have been widely appreciated for their noninvasiveness, safety, ease of use, portability, and relatively low cost compared with other clinically available methods. In this brief update, we review the 3 primary types of commercially available bioimpedance devices (single- and multiple-frequency and spectroscopy) and differentiate the underlying theory and current applications of each. We also address limitations and potential opportunities for using these devices at the bedside for clinical assessment. Mixed reports in the validation literature for all bioimpedance approaches have raised questions about absolute accuracy to estimate whole body composition in clinical populations, particularly those with abnormal fluid status and/or body geometry in whom underlying method assumptions may be violated. Careful selection of equations can improve whole body estimates by single- and multiple-frequency techniques; however, not all devices will allow for this approach. Research is increasing on the use of bioimpedance variables including phase angle and impedance ratio as potential markers of nutrition status and/or clinical outcomes; consensus on reference cut-points for interpreting these markers has yet to be established. Novel developments in the bioimpedance spectroscopy approach are allowing for improved fluid management in individuals receiving dialysis; these developments have implications for the clinical management of other conditions associated with fluid overload and may also provide enhanced whole body estimates of lean tissue through new modeling procedures.

Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.

BACKGROUND:Skeletal muscle mass decreases in end-stage heart failure and is predictive of clinical outcomes in several disease states. Skeletal muscle attenuation and quantity as quantified on preoperative chest computed tomographic scans may be predictive of mortality after continuous flow (CF) left ventricular assist device (LVAD) implantation. METHODS AND RESULTS:A single-center continuous flow-LVAD database (n=354) was used to identify patients with chest computed tomographies performed in the 3 months before LVAD implantation (n=143). Among patients with computed tomography data available, unilateral pectoralis muscle mass indexed to body surface area and attenuation (approximated by mean Hounsfield units [PHU m ]) were measured in each patient with a high intrarater and inter-rater reliability (intraclass correlation coefficients 0.98 and 0.97, respectively). Multivariate Cox regression analyses were performed, censoring at cardiac transplantation, to assess the impact of preoperative pectoralis muscle index and pectoralis muscle mean Hounsfield unit on survival after LVAD implantation. Each unit increase in pectoralis muscle index was associated with a 27% reduction in the hazard of death after LVAD (adjusted hazard ratio, 0.73; 95% confidence interval, 0.58-0.92; P=0.007). Each 5-U increase in pectoralis muscle mean Hounsfield unit was associated with a 22% reduction in the hazard of death after LVAD (adjusted hazard ratio, 0.78; 95% confidence interval, 0.68-0.89; P<0.0001). Pectoralis muscle index and pectoralis muscle mean Hounsfield unit outperformed other traditional measures in the data set, including the HeartMate II risk score. CONCLUSIONS:Pectoralis muscle size and attenuation were powerful predictors of outcomes after LVAD implantation in this data set. This one time, repeatable, internal assessment of patient substrate added valuable prognostic information that was not available on standard preoperative testing.

The Academy/ASPEN Consensus and the PG-SGA were in good agreement. It is unclear whether PA and IR can be used as surrogate markers of nutrition status or muscle loss.