Search Results (101)

Background: Critical illness is characterized by profound and rapidly evolving metabolic derangements driven by systemic inflammation, hypercatabolism, fluid shifts, and endocrine dysregulation. These dynamic changes markedly limit the accuracy of predictive equations, increasing the risk of both underfeeding and overfeeding. Indirect Calorimetry Energy represents the gold standard for measuring energy expenditure, while bioelectrical impedance vector analysis (BIVA) provides complementary insights into hydration status, cellular integrity, and body cell mass. In palliative care, AI-supported integration of indirect calorimetry and BIVA enables goal-concordant artificial nutrition by aligning energy delivery with real-time metabolic status while minimizing symptom burden. Artificial intelligence (AI) has emerged as a promising tool to integrate these heterogeneous data streams and support adaptive nutritional strategies. Methods: We conducted a structured narrative review of the literature published between 2000 and 2025 using PubMed, Scopus, Embase, and Web of Science. Artificial intelligence was not used to perform the literature search or study selection. Instead, AI was analyzed as a clinical and technological component within the included studies and explored as a future enabling strategy. Eligible publications involved adult critically ill patients and addressed indirect calorimetry, BIVA-derived parameters, or AI-based metabolic modeling applied to nutritional support. Given the heterogeneity of study designs and outcomes, findings were synthesized qualitatively. Results: Predictive equations showed substantial inaccuracy in unstable metabolic states, with errors frequently exceeding ±20–40%. Indirect calorimetry enabled individualized assessment of energy expenditure but remained limited by intermittent availability. Serial BIVA assessments consistently identified clinically relevant alterations in hydration status, body cell mass, and phase angle, the latter being strongly associated with adverse outcomes. Studies incorporating AI demonstrated improved integration of calorimetry, BIVA, and clinical variables, allowing identification of metabolic phenotypes, anticipation of metabolic shifts, and generation of adaptive nutritional recommendations. Conclusions: This narrative review highlights the complementary roles of Indirect Calorimetry and BIVA in characterizing metabolic needs in critical illness. Artificial intelligence does not replace these tools but enhances their clinical utility by integrating multidimensional data into dynamic, patient-specific nutritional strategies. The combined AI–IC–BIVA approach represents a promising framework for metabolic precision nutrition in the ICU, warranting prospective validation. Full article

Reliable property prediction in extrusion-based additive manufacturing remains challenging under extreme data scarcity (e.g., sample size of <50), particularly when experiments are constrained by designed studies such as Taguchi orthogonal arrays. In direct ink writing of lignocellulosic composites, limited experimental runs restrict the development of predictive models capable of guiding formulation and process optimization. This study introduces a physics-consistent data augmentation framework to enhance predictive reliability while preserving material-consistent behavior. Synthetic data are evaluated using four criteria: sensitivity to augmentation size, distributional consistency with experimental observations, stability with respect to boosting depth in regression modeling, and preservation of physics-consistent factor hierarchies through interpretability analysis. The framework is validated using compressive strength data from direct ink writing experiments conducted under an extremely small data regime. Results show that augmentation performance depends on the augmentation scale and model capacity. Variational autoencoder-based augmentation produced more stable and physically consistent predictions than conditional tabular generative adversarial networks in this application. Increasing predictive accuracy alone, or applying excessive augmentation, can distort material hierarchies and reduce physics consistency. The proposed evaluation framework supports reliable and interpretable property prediction in additive manufacturing when experimental data are severely limited. Full article

Total body water (TBW) undergoes substantial physiological expansion during pregnancy, reflecting coordinated cardiovascular, renal, and endocrine adaptations required to support maternal metabolism, uteroplacental perfusion, and fetal growth. These changes involve not only an overall increase in body water but also shifts in the distribution of extracellular water (ECW) and intracellular water (ICW), which influence maternal body composition, the interpretation of biochemical biomarkers affected by hemodilution, and pregnancy-related clinical outcomes. Despite its physiological and clinical relevance, the regulation and assessment of body-water compartments during pregnancy remain insufficiently integrated within nutritional and clinical research. This narrative review synthesizes current knowledge on the physiological regulation of TBW and its compartments across gestation and provides a critical analysis of the methodological approaches used to assess body-water distribution in pregnant populations. We review the mechanisms underlying plasma volume expansion, interstitial fluid accumulation, and tissue hydration, and discuss their implications for fetal growth, hypertensive disorders of pregnancy, and gestational diabetes mellitus. We also examine the principles, strengths, and limitations of the main techniques used to assess TBW and body-water compartments during pregnancy. Isotope dilution using stable isotopes (²H₂O and H₂¹⁸O) remains the reference method for TBW assessment, whereas bioelectrical impedance-based approaches, including bioelectrical impedance analysis (BIA), bioelectrical impedance spectroscopy (BIS), and bioelectrical impedance vector analysis (BIVA), offer practical alternatives for longitudinal monitoring of fluid redistribution during gestation. By integrating physiological and methodological perspectives, this review provides a framework for understanding body-water dynamics during pregnancy and for selecting appropriate approaches to assess maternal body composition and hydration. Full article

Objective: Since specific bioelectrical reference values for Italian adults are lacking, this study aims to define specific values and test their suitability in pathological cases and athletes. Methods: A sample of 1049 Italian individuals (441 men, 608 women) aged 30–65 years was considered. Competitive athletes (bodybuilding, streetlifting and tennis) were identified within the general sample, and an independent group of individuals with obesity or anorexia nervosa was analyzed for comparison. Anthropometric (weight, kg; stature, mid-upper arm, waist and calf circumferences; cm) and bioelectrical (resistance and reactance, at 50 kHz) variables were taken. Resistivity, (Rsp, Ωcm), reactivity (Xcsp, Ωcm), impedivity (Zsp, Ωcm) and phase angle (PhA, °) were calculated. Two-way ANOVA and Hotelling’s T² test were applied to assess group differences. These data were then pooled with existing datasets to create a comprehensive reference for individuals aged 18 to 100 years. Results: The specific bioelectrical variables were: Rsp = 352.3 ± 55.5, Xcsp = 41.8 ± 9.1, PhA = 6.8 ± 1.0, r (Rsp, Xcsp) = 0.67 (men); Rsp = 384.9 ± 71.2, Xcsp = 40.7 ± 9.4, PhA = 6.1 ± 1.0, r (Rsp, Xcsp) = 0.72 (women). Men showed higher PhA values (p < 0.001), reflecting higher muscle mass and quality, and shorter vectors (p < 0.001), indicative of lower relative fat mass (FM%), than women. Advancing age was associated with lower PhA and longer vectors (p < 0.001). Bioelectrical vectors of individuals with obesity or anorexia nervosa were outside the 95% variability, indicating abnormal values of FM%, whereas those of athletes fell within the lower left quadrant. Conclusions: The specific tolerance ellipses for the Italian adult population fill a gap in the existing literature, providing essential new tools for evaluating body composition in clinical and sports settings, and for comparative analyses. Full article

Background/Objectives: Anorexia nervosa (AN) is a severe psychiatric disorder characterized by energy restriction and associated with profound metabolic and body composition alterations. The loss of Body Cell Mass (BCM) leads to impaired muscle strength and functional capacity. Traditional monitoring based on body mass index (BMI, kg/m²) and weight primarily captures quantitative recovery, failing to reflect early qualitative metabolic and functional restoration. This study evaluated the longitudinal associations between improvements in physical performance and metabolic and structural recovery during intensive rehabilitation. Methods: A prospective longitudinal study was conducted on 21 AN patients undergoing a four-month intensive nutritional and functional rehabilitation program at Villa Miralago. Anthropometry, BIVA-derived parameters, indirect calorimetry and physical performance tests were assessed at baseline (T0), 2 months (T1) and 4 months (T2). Longitudinal associations were explored using Generalized Estimating Equations (GEE). Results: Improvements in functional performance (KPI-SUSS) were significantly associated with metabolic recovery, with a positive association with resting metabolic rate (β = +0.3635; p = 0.0088), indicating early metabolic reactivation before full structural reconstruction. Grip strength (KPI-grip) was significantly associated with cellular integrity (Xc β = +0.4129; p = 0.0088) and with favorable fluid redistribution (↑ intracellular water percentage (ICWp), ↓ extracellular water percentage (ECWp)). Structural recovery markers (Fat-Free Mass (FFM, kg), Fat-Free Mass Index (FFMI, kg/m²), BCM) increased significantly over time, confirming a time-dependent restoration of metabolically active mass. Fat mass (FM, kg) and fat mass percentage (FMp) were positively associated with functional improvement, although this effect attenuated longitudinally. These findings support strength performance as a sensitive functional indicator longitudinally associated with qualitative metabolic and cellular recovery. Conclusions: Muscle strength and functional performance tests are simple, non-invasive and cost-effective tools longitudinally associated with metabolic and structural normalization in AN. Their integration into clinical practice may enable the monitoring of meaningful recovery, personalized rehabilitation strategies and improving long-term outcomes. Full article

The rupture of the B-I dam at the Córrego do Feijão mine in Brumadinho, Minas Gerais, Brazil, on 25 January 2019, prompted the implementation of environmental remediation actions. Among these actions is the need for groundwater quality monitoring in the Feijão Pit (“Cava de Feijão”) area due to the disposal of tailings from dams B-I, B-IV, and B-IVA at this site. In order to assess potential impacts on groundwater, the determination of baseline values for elements of interest was proposed for ten monitoring wells installed in and around the pit, with monitoring results from 2019 to 2024, totaling 854 samples. Due to the lack of hydrochemistry data and local hydrogeological complexity of the existing aquifers within the context of the Iron Quadrangle (IQ), it was necessary to evaluate and determine individual baseline values for each monitoring well, assessing data variability and population distribution. For this purpose, the 95–95 Upper Tolerance Limit (UTL) method was applied to establish baseline values providing a robust statistical approach that encompasses 95% of observations with a 95% confidence interval as it is a widely used standard in statistics due to its practical balance between confidence and precision. This methodology proved effective and has potential for application in groundwater monitoring in areas that may present high compositional variability due to the chemical heterogeneity of the groundwater. The baseline values obtained for the main elements of interest, which are iron (Fe) and manganese (Mn), were consistent with findings from previous studies conducted in the hydrogeological units of the study area, also demonstrating that the adopted methodology was effective in identifying representative concentrations for the region. Full article

Background/Objectives: Energy availability (EA) is associated with Relative Energy Deficiency in Sport syndrome. This study assessed the EA, body composition, and phase angle (φ) of adolescent artistic gymnasts during a competitive season. Methods: Thirty non-elite artistic gymnasts aged 11–14 years participated in this cross-sectional study. Anthropometric data were collected and body mass index (BMI) was assessed using the World Health Organization growth charts. Bioelectrical impedance analysis was performed and diet and physical activity were recorded for three days. Dietary and physical activity records were analyzed to estimate energy intake, total energy expenditure (TEE), and exercise energy expenditure, from which energy balance (EB) and EA were calculated. The 95% confidence ellipses of the impedance (Z) vectors were compared with a reference population using the two-sample Hotelling’s T² test. Correlations between variables were examined by Pearson’s or Spearman’s correlation analysis. Statistical significance was set at α = 0.05. Results: All participants were classified within the normal BMI category, except for one who was classified as being overweight. Mean (± SD) fat mass, fat-free mass (FFM), and φ were 16.1 ± 3.4%, 83.9 ± 3.4%, and 6.0 ± 0.6°, respectively. The 95% confidence ellipses of Z vectors differed significantly from the reference population. Energy balance was 32 ± 223 kcal/day and EA was 49.2 ± 11.4 kcal/kg FFM/day. Energy availability was significantly correlated with EB, TEE, and body composition variables. Conclusions: Adolescent non-elite artistic gymnasts showed no clear indications of LEA and exhibited a normal body composition and φ during the competitive season, consistent with their EA. Full article

Background/Objectives: Malnutrition is highly prevalent in patients with acute leukemia and is frequently underrecognized at diagnosis. Traditional screening tools based on anthropometry often fail to identify early nutritional deterioration. This study aimed to evaluate the prognostic utility of a comprehensive morphofunctional assessment—including bioelectrical impedance vector analysis (BIVA), handgrip strength (HGS), and muscle ultrasound—conducted at diagnosis and after induction therapy, to evaluate the prognostic association with 12-month mortality. Methods: In this prospective cohort study, 52 adult patients with newly diagnosed acute leukemia were enrolled between November 2022 and November 2024 at two tertiary hospitals in Málaga, Spain. Nutritional status was determined using GLIM criteria. Morphofunctional assessment included BIVA-derived phase angle (PhA), HGS via dynamometry, and rectus femoris ultrasound. A second evaluation was performed prior to haematopoietic stem cell transplantation. Mortality at 12 months was the primary outcome. Logistic regression and ROC analysis were used to assess prognostic associations. Results: At baseline, 65.4% of patients were classified as malnourished. After three months, patients showed significant declines in PhA (−0.55°, p < 0.001), body cell mass (−3.15 kg, p < 0.01), skeletal muscle mass (−1.66 kg, p < 0.01), and rectus femoris cross-sectional area (−0.36 cm², p = 0.011). Baseline malnutrition (OR = 6.88; 95% CI: 1.17–40.38; p = 0.033) and PhA decline ≥ 0.90° were both independently associated with higher 12-month mortality. Conclusions: Early morphofunctional assessment using GLIM criteria, BIVA, and muscle ultrasound identifies patients at nutritional and functional risk. PhA decline during treatment was associated with higher 12-month mortality, supporting the need for early, personalized nutritional intervention in leukemia care. Full article

The agri-food supply chain is a relevant contributor to the Italian economy but shows a high incidence of occupational injuries and musculoskeletal disorders, such as lower back pain. Repetitive manual handling and biomechanical overload highlight the need for a prevention-oriented, system-level assessment. This protocol aims to implement a harmonized One Health approach procedure for the multidimensional evaluation of food supply chain workers in real-world settings. The protocol integrates bioelectrical impedance vector analysis (BIVA), nutritional parameters, quality-of-life and psychological measures, and assessments of systemic oxidative stress and systemic serotonin levels. Data from active workers will be compared with those from sedentary individuals. The study will evaluate whether BIVA profiles differ between these groups and examine how the additional indicators contribute to a multidimensional well-being framework. By operationalizing an integrated One Health approach that bridges nutritional, psychological, and biomarker domains, this protocol is designed to guide targeted preventive and educational strategies and inform evidence-based occupational and public health policies across the food supply chain. Trial registration: NCT06896877 (ClinicalTrials.gov), 26 March 2025. Full article

Elderly patients with femoral fractures need specific rehabilitation after surgery that aims to improve their self-reliance and life quality, reducing their mortality rate. Although worsening patient body composition increased the risk of an unfavourable prognosis, it remains unclear whether evaluating bioelectrical impedance analysis (BIA) parameters can predict any functional recovery. A longitudinal design was conducted on 45 elders (84.59 ± 7.18 years, 75.6% female) who underwent femoral surgery to examine BIA features as rehabilitation biomarkers. The patient’s body composition, assessed by anthropometry and bioimpedance analysis (BIA), and self-reliance were evaluated three times during follow-up in both healthy and surgical lower limbs. The ANCOVA test, adjusted for gender and side of surgery, found improvements in daily living activities, while only thigh circumferences decreased over time. Regarding the BIA, the surgical leg showed a wider decrement in bioelectrical resistance (R), whereas the bioelectric reactance (Xc) exhibited similar trends. Females who underwent surgery on their dominant leg showed significant changes (p < 0.001) in bioimpedance vectorial analysis (BIVA), with a linear trend from baseline to postoperative time, while males exhibited beneficial variations only between baseline and time 2 (p < 0.01). Geriatric patients exhibit characteristic traits that require additional attention. BIA may be a feasible and non-invasive method for monitoring patient prognosis and reducing national health system costs. Full article

Background: Institutionalized older adults often experience cognitive and functional decline and altered body composition (BC), making nutritional assessment difficult. Bioelectrical impedance analysis (BIA) offers a simple and non-invasive method to evaluate BC; classic and specific bioelectrical impedance vector analysis do not require predictive models or assumptions about hydration status. Objective: This study aimed to evaluate the utility of BIA, classic bioelectrical impedance vector analysis (BIVA), and specific BIVA (BIVA-Sp) in detecting nutritional and other related disorders in institutionalized psychogeriatric patients. Methods: A cross-sectional study was conducted in 95 institutionalized older adults (52 men, 43 women; mean age: 80 years). Clinical and functional data, including frailty, dependency, handgrip strength, and anthropometry, were collected. BC was assessed using BIA. Nutritional diagnoses included malnutrition (GLIM criteria), sarcopenia (EWGSOP2), adiposity, and sarcopenic obesity (SOGLI criteria). Mean impedance vectors and 95% confidence ellipses were generated for BIVA and BIVA-Sp. Individual vectors were compared with reference data from healthy older adults. Statistical analyses compared clinical variables and impedance vector distributions between groups. Results: Classic BIVA differentiated patients with sarcopenia and sarcopenic obesity, while BIVA-Sp identified vector shifts associated with adiposity and sarcopenic obesity. Neither BIVA nor BIVA-Sp discriminated patients based on body mass index or malnutrition status. Conclusions: The application of BIVA in institutionalized psychogeriatric patients allows for easier, faster, and more effective detection of changes in BC and hydration status compared with conventional methods. This enables individualized monitoring and facilitates interventions that may reduce complications, functional decline, and hospitalizations, thereby improving their quality of life. Full article

The identification of factors related to performance that can be improved during training is of primary interest for athletes. However, little is known about this issue among artistic gymnasts. The current pilot study aims to assess the association between training factors and anthropometric, body composition, and muscle strength (MS) variables in adolescent female artistic gymnastics. A total of 22 young female artistic gymnasts taking part in a professional team, who had a median age of 12.21 years and a median body mass index (BMI) of 18.72 kg/m², were categorized into a competitive-level (8.00–17.00 h [h]/week) group (n = 16) and a pre-team-level (<4 h/week) one (n = 6). The training factors considered were (i) training hours per session, (ii) training hours per week, and (iii) training years. All the participants underwent complete anthropometric measurements, including body composition assessments by means of bioelectrical impedance vector analysis (BIVA), and an objective physical activity evaluation with a portable accelerometer SenseWear Armband (SWA). MS was assessed using a handgrip dynamometer. The correlation and partial correlation were evaluated to test the associations between variables. The competitive-level group had higher fat-free mass (FFM), body cell mass (BCM), and MS compared to the pre-team group. However, after adjusting for confounders, only the number of training hours per session was associated with MS (ρ = 0.445, p < 0.05) and BCM (ρ = 0.475, p < 0.05). In conclusion MS and BCM but not FFM are correlated with the number of training hours per session. Future studies are needed to test the effects of specific programs based on this training parameter on these variables, to determine whether they can impact athletic performance in young female artistic gymnasts. Full article

Background: Bioelectrical Impedance Vector Analysis (BIVA) is a qualitative method that standardizes resistance and reactance relative to stature (R/H and Xc/H) and plots them as vectors on an R-Xc graph. This equation-free approach assesses body composition, allowing for the evaluation of hydration status and cellular integrity through tolerance ellipses. This study aimed to systematically map BIVA reference ellipses across general, pediatric, pathological, and athletic populations. Methods: A scoping review was conducted according to PRISMA-ScR guidelines. Five databases were searched. Extracted data included (a) sample characteristics (sample size, age, sex, BMI, country, ethnicity), (b) population type, (c) analyzer specifications, and (d) R/H and Xc/H means, standard deviations, and correlation values. Results: A total of 53 studies published between 1994 and July 2025 were included. From these, 508 tolerance ellipses were identified: 281 for the general population (18–92 years), 133 for children/adolescents (0–18 years), 49 for athletes, and 45 for pathological groups. Studies were primarily conducted in Europe and the Americas, using 11 analyzers with variations in measurement protocols, including body side, posture, and electrode placement. Conclusions: This scoping review categorizes the existing BIVA tolerance ellipses by population type, sex, age, BMI, device used, and measurement protocol. The structured presentation is intended to guide researchers, clinicians, nutritionists, and sports professionals in selecting appropriate reference ellipses tailored to specific populations and contexts. Full article

Background/Objectives: Severe radiation-induced mucositis (RIM) is the most distressing acute side effect experienced by oropharyngeal squamous cell carcinoma (OPSCC) patients during chemo-radiotherapy (CRT), with a prevalence between 40 and 68%. RIM severity exhibits a multifactorial etiology that remains unclear. We aimed to analyze nutritional and morphofunctional predictive factors for severe RIM in OPSCC patients undergoing CRT. Methods: A prospective cohort study was conducted. Global Leadership Initiative on Malnutrition (GLIM) criteria, bioelectrical impedance vector analysis (BIVA), functional assessment and dosimetric analysis were performed prior to radiotherapy. Results: Eighty-two patients were analyzed. Severe RIM affected 46.3% of patients. Severe malnutrition according to GLIM (p = 0.011), prolonged Timed Up and Go (TUG) test (p = 0.025) and larger PTV54 volume (p = 0.049) were independent predictive factors for severe RIM, while higher fat-free mass (FFM) (p = 0.006) showed a protective effect. Conclusions: These findings highlight the importance of a comprehensive early nutritional assessment for accurately identifying patients at a higher risk of severe RIM. Full article

Background: Sarcopenia and low muscle mass are prevalent and prognostically relevant in patients with lung cancer, yet their diagnosis remains challenging in routine clinical practice. Opportunistic assessment using computed tomography (CT) has emerged as a valuable tool for body composition evaluation. We aimed to assess the utility of thoracic CT at T12 and T4 levels in identifying sarcopenia and low muscle mass and explore their correlation with morphofunctional tools such as bioelectrical impedance vector analysis (BIVA), nutritional ultrasound (NU), and functional performance tests. Methods: In this prospective observational study, 80 patients with lung cancer were evaluated at diagnosis. Body composition was assessed using BIVA-, NU-, and CT-derived parameters at T12 and T4 levels. Functional status was measured using the Timed Up and Go (TUG) and 30-Second Chair Stand Test. Sarcopenia was defined according to EWGSOP2 criteria. Results: Sarcopenia was identified in 20% of patients. CT-derived indices at T12CT demonstrated better diagnostic performance than T4CT. For detecting low muscle mass, the optimal SMI cut-off values were SMI_T12CT < 31.98 cm²/m² and SMI_T4CT < 59.05 cm²/m² in men and SMI_T12CT < 28.23 cm²/m² and SMI_T4CT < 41.69 cm²/m² in women. For sarcopenia diagnosis, the values were SMI_T12CT < 24.78 cm²/m² and SMI_T4CT < 57.23 cm²/m² in men and SMI_T12CT < 21.24 cm²/m² and SMI_T4CT < 49.35 cm²/m² in women. A combined model including SMI_T12CT, RF_CSA, and the 30 s squat test showed high diagnostic accuracy (AUC = 0.826). In multivariable analysis, lower SMA_T12CT was independently associated with risk of sarcopenia (OR = 0.96, 95% CI: 0.92–0.99, p = 0.022), as were older age (OR = 1.23, 95% CI: 1.07–1.47, p = 0.010) and fewer repetitions in the 30 s squat test (OR = 0.78, 95% CI: 0.63–0.91, p = 0.007). Conclusions: CT-derived body composition assessment, particularly at the T12 level, shows good correlation with morphofunctional tools and may offer a reliable and timely alternative for identifying sarcopenia and low muscle mass in patients with lung cancer. Full article