Adam J. Kuchnia

Bioimpedance at the Bedside Current Applications, Limitations, and Opportunities

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.

Validation of Bedside Ultrasound of Muscle Layer Thickness of the Quadriceps in the Critically Ill Patient (VALIDUM Study): A Prospective Multicenter Study.

Background: In critically ill patients, muscle atrophy is associated with long-term disability and mortality. Bedside ultrasound may quantify muscle mass, but it has not been validated in the intensive care unit (ICU). Here, we compared ultrasound-based quadriceps muscle layer thickness (QMLT) with precise quantifications of computed tomography (CT)–based muscle cross-sectional area (CSA). Methods: Patients ≥18 years old with abdominal CT scans performed for clinical reasons were recruited from 9 ICUs for an ultrasound assessment of the quadriceps. CT scans of the third lumbar vertebra, performed <24 hours before or <72 hours after ICU admission, were analyzed for CSA. Low muscularity was defined as 170 cm2 for men and 110 cm2 for women. The ultrasound probe was maximally compressed against the skin and QMLT was measured on 2 sites of each quadriceps <72 hours of the CT scan. Results: Mean CT-derived muscle CSA was 109 ± 25 cm2 for women and 168 ± 37 cm2 for men, where 58% of patients exhibited low muscularity; only 2.7% patients were underweight according to body mass index. QMLT was positively correlated with CT CSA (r = 0.45, P < .001). Based on logistic regression to predict low muscularity, QMLT independently generated a concordance index (c) of 0.67 (P < .002), which increased to 0.77 (P < .001) when age, sex, body mass index, Charlson Comorbidity Index, and admission type (surgical vs medical) were added. Conclusions: Our results suggest that QMLT alone with our current protocol may not accurately identify patients with low muscle mass.

Evaluation of Bioelectrical Impedance Analysis in Critically Ill Patients Results of a Multicenter Prospective Study

Background: In critically ill patients, muscle loss is associated with adverse outcomes. Raw bioelectrical impedance analysis (BIA) parameters (eg, phase angle [PA] and impedance ratio [IR]) have received attention as potential markers of muscularity, nutrition status, and clinical outcomes. Our objective was to test whether PA and IR could be used to assess low muscularity and predict clinical outcomes. Methods: Patients (≥18 years) having an abdominal computed tomography (CT) scan and admitted to intensive care underwent multifrequency BIA within 72 hours of scan. CT scans were landmarked at the third lumbar vertebra and analyzed for skeletal muscle cross-sectional area (CSA). CSA ⩽170 cm2 for males and ⩽110 cm2 for females defined low muscularity. The relationship between PA (and IR) and CT muscle CSA was evaluated using multivariate regression and included adjustments for age, sex, body mass index, Charlson Comorbidity Index, and admission type. PA and IR were also evaluated for predicting discharge status using dual-energy x-ray absorptiometry–derived cut-points for low fat-free mass index. Results: Of 171 potentially eligible patients, 71 had BIA and CT scans within 72 hours. Area under the receiver operating characteristic (c-index) curve to predict CT-defined low muscularity was 0.67 (P ⩽ .05) for both PA and IR. With covariates added to logistic regression models, PA and IR c-indexes were 0.78 and 0.76 (P < .05), respectively. Low PA and high IR predicted time to live ICU discharge. Conclusion: 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.

The Use of Technology for Estimating Body Composition: Strengths and Weaknesses of Common Modalities in a Clinical Setting

Assessment of body composition, both at single time points and longitudinally, is particularly important in clinical nutrition practice. It provides a means for the clinician to characterize nutrition status at a single time point, aiding in the identification and diagnosis of malnutrition, and to monitor changes over time by providing real-time information on the adequacy of nutrition interventions. Objective body composition measurement tools are available clinically but are often underused in nutrition care, particularly in the United States. This is, in part, due to a number of factors concerning their use in a clinical context: cost and accessibility of equipment, as well as interpretability of the results. This article focuses on the factors influencing interpretation of results in a clinical setting. Body composition assessment, regardless of the method, is inherently limited by its indirect nature. Therefore, an understanding of the strengths and limitations of any method is essential for meaningful interpretation of its results. This review provides an overview of body composition technologies available clinically (computed tomography, dual-energy x-ray absorptiometry, bioimpedance, ultrasound) and discusses the strengths and limitations of each device.

The Use of Technology for Estimating Body Composition

Assessment of body composition, both at single time points and longitudinally, is particularly important in clinical nutrition practice. It provides a means for the clinician to characterize nutrition status at a single time point, aiding in the identification and diagnosis of malnutrition, and to monitor changes over time by providing real-time information on the adequacy of nutrition interventions. Objective body composition measurement tools are available clinically but are often underused in nutrition care, particularly in the United States. This is, in part, due to a number of factors concerning their use in a clinical context: cost and accessibility of equipment, as well as interpretability of the results. This article focuses on the factors influencing interpretation of results in a clinical setting. Body composition assessment, regardless of the method, is inherently limited by its indirect nature. Therefore, an understanding of the strengths and limitations of any method is essential for meaningful interpretation of its results. This review provides an overview of body composition technologies available clinically (computed tomography, dual-energy x-ray absorptiometry, bioimpedance, ultrasound) and discusses the strengths and limitations of each device.

Phase Angle and Impedance Ratio: Reference Cut-Points From the United States National Health and Nutrition Examination Survey 1999-2004 From Bioimpedance Spectroscopy Data.

Background: Raw bioimpedance parameters (eg, 50-kHz phase angle [PA] and 200-kHz/5-kHz impedance ratio [IR]) have been investigated as predictors of nutrition status and/or clinical outcomes. However, their validity as prognostic measures depends on the availability of appropriate reference data. Using a large and ethnically diverse data set, we aimed to determine if ethnicity influences these measures and provide expanded bioimpedance reference data for the U.S. population. Methods: The National Health and Nutrition Examination Survey (NHANES) is an ongoing compilation of studies conducted by the U.S. Centers for Disease Control and Prevention designed to monitor nutrition status of the U.S. population. The NHANES data sets analyzed were from the years 1999–2000, 2001–2002, and 2003–2004. Results: Multivariate analysis showed that PA and IR differed by body mass index (BMI), age, sex, and ethnicity (n = 6237; R2 = 41.2%, P < .0001). Suggested reference cut-points for PA stratified by age decade, ethnicity, and sex are provided. Conclusion: Ethnicity is an important variable that should be accounted for when determining population reference values for PA and IR. We have provided sex-, ethnicity-, and age decade–specific reference values from PA for use by future studies in U.S. populations. Interdevice differences are likely to be important contributors to variability across published population-specific reference data and, where possible, should be evaluated in future research. Ultimately, further validation with physiologically relevant reference measures (eg, dual-energy x-ray absorptiometry) is necessary to determine if PA/IR are appropriate bedside tools for the assessment of nutrition status in a clinical population.

Long-Term Body Composition Changes in Women Following Roux-en-Y Gastric Bypass Surgery.

Background: Although most individuals experience successful weight loss following Roux-en-Y gastric bypass (RYGB), weight regain is a concern, the composition of which is not well documented. Our aim was to evaluate changes in body composition and handgrip strength as a measure of functional status in participants from a previous 1-year post-RYGB longitudinal study who had undergone RYGB approximately 9 years prior. Methods: Five women from an original larger cohort were monitored pre-RYGB and 1.5 months, 6 months, 1 year, and 9 years post-RYGB. Body composition was assessed at all time points using dual energy x-ray absorptiometry and multiple dilution. Handgrip strength was measured using a digital isokinetic hand dynamometer (Takei Scientific Instruments, Ltd, Tokyo, Japan). Results: Mean time to final follow-up was 8.7 years. Lean soft tissue (LST) loss over the ~9-year period was on average 11.9 ± 5.6 kg. Compared with 1-year post-RYGB, 9-year LST was 4.4 ± 3.0 kg lower (P = .03). Fat-free mass decreased over the 9-year period by 12.6 ± 5.8 kg. Mean fat mass (FM) decreased from 75.4 ± 22.6 kg pre-RYGB to 35.5 ± 21.5 kg 1 year post-RYGB but then trended toward an increase of 8.6 ± 7.0 kg between 1 year and 9 years post-RYGB (P = .053). Loss of LST was correlated with loss of handgrip strength (r = 0.64, P = .0005). Conclusion: The continued loss of lean mass associated with decreased handgrip strength occurring with long-term trend toward FM regain post-RYGB is concerning. The loss of LST and functional strength carries particular implications for the aging bariatric population and should be investigated further.

Preoperative Pectoralis Muscle Quantity and Attenuation by Computed Tomography Are Novel and Powerful Predictors of Mortality After Left Ventricular Assist Device Implantation

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 [PHUm]) 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.

Overstated metabolic adaptation after “the biggest loser” intervention

TO THE EDITOR: The recent Obesity publication by Fothergill et al. (1) on the “The Biggest Loser” contestants (BLC) asserts that intensive exercise-centric intervention, despite fat-free mass (FFM) retention, leads to persistent metabolic adaptation (MA), thwarting long-term weight loss success. Their case rests upon predicting resting metabolic rate (RMR) using a newly developed, unvalidated, regression-derived equation [different from their previous equation in the same population (2)], with potentially error-prone weighted variables.

Protein in the hospital : gaining perspective and moving forward

Provision of adequate protein is crucial for optimizing outcomes in hospitalized patients. However, the methodologies upon which current recommendations are based have limitations, and little is known about true requirements in any clinical population. In this tutorial, we aim to give clinicians an understanding of how current protein recommendations were developed, an appreciation for the limitations of these recommendations, and an overview of more sophisticated approaches that can be applied to better define protein requirements. A broader perspective of the challenges and opportunities in determining clinical protein requirements can help clinicians think critically about the individualized nutrition care they provide to their patients with the goal of administering adequate protein to optimize outcomes.