The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

Advancements in nutritional diagnosis and support strategies during the perioperative period for patients with liver cancer

Liver cancer represents a grave hepatic condition and constitutes a significant global health concern. Surgical resection remains the principal therapeutic modality for liver cancer. Nevertheless, perioperative malnutrition exerts a notable impact on patients with liver cancer, emerging as an independent risk factor for disease mortality and adverse outcomes. Hence, precise nutritional diagnosis and timely nutritional support hold the potential to enhance therapeutic efficacy and quality of life for liver cancer patients. This study represents a meticulous foray into the literature, extracting data from PubMed, Web of Science, and EMBASE databases, with a focus on the past 5 years. It scrutinizes the impact of malnutrition on patients undergoing liver cancer surgery, the etiological underpinnings of malnutrition within this patient cohort, the critical assessment of perioperative nutritional status, and the strategic approaches to nutritional support. Utilizing rigorous inclusion and exclusion criteria, the amassed scholarly works are meticulously synthesized, methodically organized, and categorically elaborated upon. Ultimately, the authors propose the incorporation of a multidisciplinary nutrition management team during the perioperative period, comprising nutritionists, pharmacists, physicians, nurses, psychologists, and rehabilitation therapists, among other specialized professionals. Together, they collaborate to devise and implement personalized nutritional support plans, monitor patients’ nutritional status, and make necessary adjustments as required. Through comprehensive management and intervention, improvements in the nutritional status of liver cancer patients can be achieved, thereby enhancing surgical success rates and facilitating postoperative recovery. It is believed that this manuscript will offer valuable insights to advance the nutritional management during the perioperative phase of liver cancer, aiding in ameliorating patients' nutritional status and treatment outcomes.

Validation of Bioelectrical Impedance Devices for the Determination of Body Fat Percentage in Firefighters

ABSTRACT

Jagim, AR, Luedke, J, Erickson, JL, Fields, JB, and Jones, MT. Validation of bioelectrical impedance devices for the determination of body fat percentage in firefighters. J Strength Cond Res 38(8): e448-e453, 2024-To cross-validate bioelectrical impedance devices for the determination of body fat percentage (BF%) in firefighters. Twenty-eight structural firefighters were evaluated (female, n = 2; male, n = 26 [mean ± SD] age: 38.2 ± 8.3 years; height: 180.2 ± 7.5 cm; body mass: 86.7 ± 20.8 kg; body mass index: 25.8 ± 7.8 kg·m-2) using multifrequency bioelectrical impedance analysis (MFBIA) hand-to-foot device, and single-frequency BIA foot scale (F2FBIA), and a single-frequency handheld BIA device (HHBIA). Dual X-ray absorptiometry served as the criterion. Validity metrics were examined to establish each method's performance. Body fat % values produced by MFBIA (r = 0.913), F2FBIA (r = 0.695), and HHBIA (r = 0.876) were strongly associated (p < 0.001) with criterion BF% measures. However, MFBIA, F2FBIA, and HHBIA all significantly (p < 0.001) underestimated BF% when compared with the criterion measure. Constant error ranged between 4.0 and 5.5% across all BIA devices. Despite strong associations between the BIA devices included in the current study and the criterion measure, all BIA devices underestimated BF%, which resulted in an overestimation of fat-free mass. In addition, proportional bias was observed in which BF% was overestimated at lower values and underestimated at higher values.

Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning

Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection is a public health priority but challenging. In this study, an adhesive, soft on-skin sensor with low electrode-skin contact impedance for early-stage NAFLD detection is fabricated. A method is developed to synthesize platinum nanoparticles and reduced graphene quantum dots onto the on-skin sensor to reduce electrode-skin contact impedance by increasing double-layer capacitance, thereby enhancing detection accuracy. Furthermore, an attention-based deep learning algorithm is introduced to differentiate impedance signals associated with early-stage NAFLD in high-fat-diet-fed low-density lipoprotein receptor knockout (Ldlr-/-) mice compared to healthy controls. The integration of an adhesive, soft on-skin sensor with low electrode-skin contact impedance and the attention-based deep learning algorithm significantly enhances the detection accuracy for early-stage NAFLD, achieving a rate above 97.5% with an area under the receiver operating characteristic curve (AUC) of 1.0. The findings present a non-invasive approach for early-stage NAFLD detection and display a strategy for improved early detection through on-skin electronics and deep learning.

High-standard predictive equations for estimating body composition using bioelectrical impedance analysis: a systematic review

The appropriate use of predictive equations in estimating body composition through bioelectrical impedance analysis (BIA) depends on the device used and the subject's age, geographical ancestry, healthy status, physical activity level and sex. However, the presence of many isolated predictive equations in the literature makes the correct choice challenging, since the user may not distinguish its appropriateness. Therefore, the present systematic review aimed to classify each predictive equation in accordance with the independent parameters used. Sixty-four studies published between 1988 and 2023 were identified through a systematic search of international electronic databases. We included studies providing predictive equations derived from criterion methods, such as multi-compartment models for fat, fat-free and lean soft mass, dilution techniques for total-body water and extracellular water, total-body potassium for body cell mass, and magnetic resonance imaging or computerized tomography for skeletal muscle mass. The studies were excluded if non-criterion methods were employed or if the developed predictive equations involved mixed populations without specific codes or variables in the regression model. A total of 106 predictive equations were retrieved; 86 predictive equations were based on foot-to-hand and 20 on segmental technology, with no equations used the hand-to-hand and leg-to-leg. Classifying the subject's characteristics, 19 were for underaged, 26 for adults, 19 for athletes, 26 for elderly and 16 for individuals with diseases, encompassing both sexes. Practitioners now have an updated list of predictive equations for assessing body composition using BIA. Researchers are encouraged to generate novel predictive equations for scenarios not covered by the current literature.Registration code in PROSPERO: CRD42023467894.

Bioelectrical Impedance Vector Analysis, Nutritional Ultrasound®, and Handgrip Strength as Innovative Methods for Monitoring Critical Anorexia Nervosa Physical Recovery: A Pilot Study

Eating disorders (EDs) manifest as persistent disruptions in eating habits or related behaviors, significantly impacting physical health and psychosocial well-being. Nutritional assessment in ED patients is crucial for monitoring treatment efficacy. While dual-energy X-ray absorptiometry (DEXA) remains standard, interest in alternative methods such as bioelectrical impedance vector analysis (BIVA) and Nutritional Ultrasound® (NU) has risen due to their affordability and portability. Additionally, hand dynamometry offers a user-friendly approach to assessing grip strength (HGS), indicative of nutritional status. A prospective study was carried out to evaluate the utility of BIVA, NU®, and HGS in 43 female AN patients. Measurements were taken at baseline and hospital discharge. A total of 41 patients completed the study. After the intervention, numerous BIVA-related parameters such as fat (3.5 ± 2 kg vs. 5.3 ± 2.7 kg, p < 0.001) and free fat mass (33.9 ± 3.8 kg vs. 37.5 ± 4.1 kg, p < 0.001) were partially restored. Similarly, Nutritional Ultrasound® showed promising results in assessing body composition changes such as total abdominal fat tissue (0.5 ± 0.3 cm vs. 0.9 ± 0.3 cm, p < 0.05). In the same way, rectus femoris cross-sectional area values correlated with clinical outcomes such as free fat mass (0.883, p < 0.05) and appendicular muscle mass (0.965, p < 0.001). HGS reached the normality percentile after the intervention (21.6 ± 9.1 kg vs. 25.9 ± 12.3 kg, p < 0.05), demonstrating a significant association between grip strength and body composition parameters such as free fat mass (0.658, p < 0.001) and appendicular muscle mass (0.482, p < 0.001). Incorporating BIVA-, NU®-, and HGS-enhanced nutritional assessment into the treatment of AN patients offers cost-effective, portable, and non-invasive alternatives to DEXA. These techniques offer valuable insights into changes in body composition and nutritional status, which, in turn, facilitate treatment monitoring and contribute to improved patient outcomes.

Specific bioelectrical vectors pattern in individuals with sarcopenic obesity

BACKGROUND

Sarcopenic obesity is a common condition in the elderly associated with excessive adiposity and low muscle mass and strength.

AIMS

This study aims to establish a method for detecting bioelectrical characteristics in individuals with sarcopenic obesity through specific Bioelectrical Impedance Vector Analysis (specific BIVA), while considering the characteristics of individuals with healthy, sarcopenic, and obese conditions.

METHODS

The sample was composed by 915 Italian adults over 50 years of age (men: 74.6 ± 8.8 y; women:76.3 ± 8.8 y) living in Sardinia (Italy). A dataset of 1590 US adults aged 21 - 49 years retrieved from the 2003 - 2004 National Health and Nutrition Examination Survey was also considered in a final step of the study. Anthropometric (stature, weight, waist, arm, and calf circumferences) and whole-body bioelectrical variables were taken. In the Italian sample, bioelectrical impedance was applied to estimate the relative content of fat mass and skeletal muscle mass. Groups with healthy body composition (NS-NO), or consistent with sarcopenia (S), sarcopenic obesity (S-O), and obesity (O) were defined based on the cut-offs suggested by European expert guidelines (EWGSOP2 and ESPEN-EASO). Specific BIVA was applied to compare groups and to identify the area for sarcopenic obesity within young-adults tolerance ellipses. The position of the specific vector of US individuals with S-O, selected on the basis of DXA measurements, was also considered.

RESULTS

In both sexes of the Italian sample, the bioelectrical characteristics of the four groups were different (p < 0.001). The differences were mainly related to vector length, indicative of higher fat mass, which was longer in the O and S-O groups, and phase angle, a proxy of intracellular/extracellular water and muscle mass, lower in the sarcopenic groups. Bioelectrical vectors of the S-O group fell in the right quadrant, outside of the 95 % tolerance ellipses of young adults. The mean vector of the US sample with S-O fell in the same area. Within the S-O area, women had similar bioelectrical values, while men showed phase angle variability, which was related to the severity of the condition.

CONCLUSIONS

Specific BIVA detects body composition peculiarities of individuals with sarcopenic obesity, thus allowing their diagnosis when associated with low handgrip strength values.