Levi M. Teigen

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 Influence of Bariatric Surgery on Serum Bile Acids in Humans and Potential Metabolic and Hormonal Implications: a Systematic Review.

Recent research suggests a mechanistic role for bile acids (BA) in the metabolic improvement following bariatric surgery. It is believed that the hormonal and metabolic effects associated with changes in systemic BAs may be related to the farnesoid X receptor (FXR) and a G-protein coupled receptor (TGR5). This systematic review examines changes in systemic BAs following bariatric procedures. Studies were included if they reported the measurement of systemic BAs in humans at at least one time point after bariatric surgery. Eleven papers were identified that met the inclusion criteria. Seven studies reported the effect of Roux-en-Y gastric bypass (RYGB) on fasting BAs. The majority (6/7) reported that fasting BAs increased after RYGB. Data regarding fasting BAs after vertical sleeve gastrectomy (VSG) and laparoscopic gastric banding (LAGB) are inconsistent. Data regarding post-prandial BA changes after RYGB, VSG, and LAGB are also inconsistent. More research is needed to investigate the connection between BAs and the metabolic improvement seen after bariatric surgery.

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.

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.

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.

Impact of Software Selection and ImageJ Tutorial Corrigendum on Skeletal Muscle Measures at the Third Lumbar Vertebra on Computed Tomography Scans in Clinical Populations

BACKGROUND There is growing interest in computed tomography (CT) measures of skeletal muscle cross-sectional area (CSA) for nutrition assessment. Multiple software programs are available, but little work has been done comparing programs. We aimed to determine if CT-derived measures of skeletal muscle CSA at the level of the L3 are influenced by the software program used. We also demonstrate the importance of the ImageJ corrigendum published in this journal. METHODS Two software programs, National Institutes of Health ImageJ and Tomovision sliceOmatic, were compared. ImageJ measures were obtained using both the original tutorial and corrigendum instructions. Skeletal muscle CSA at the level of the L3 was measured in advanced heart failure and head and neck cancer populations by 3 different investigators. Intraclass correlation coefficients were used to calculate intrarater and interrater reliability. Bland-Altman analysis was used to assess agreement. RESULTS Both software programs yielded excellent intrarater and interrater reliability scores (intraclass correlation coefficients, 0.985-1.000). The overall mean difference (ImageJ tutorial with corrigendum - sliceOmatic) for the entire sample (N = 51) was found to be 1.53 cm2 (95% CI, 0.59-2.47 cm2 ). The overall mean difference (ImageJ corrected - original) for the entire sample (N = 51) was found to be -11.35 cm2 (95% CI, -12.75 to -9.95 cm2 ). CONCLUSION Measures of skeletal muscle CSA at the L3 were found to be ∼1.53 cm2 higher with ImageJ than sliceOmatic. This difference was not found to affect interpretation against a published cut point. The importance of accounting for the ImageJ tutorial corrigendum was shown to be clinically significant when applied to published cut points.