UNASSIGNED: Bioelectrical impedance analysis (BIA) serves as a method to estimate body composition. Parameters such as phase angle (PA), standardized phase angle (SPA), body mass cell (BCM), BCM index (BCMI), and fat-free mass (FFM) might significantly impact the prognosis of head and neck cancer (HNC) patients. The present study aimed to investigate whether bioelectrical parameters can be used to predict survival in the HNC population and establish the optimal cutoff points for predictive accuracy.
UNASSIGNED: A multicenter observational study was performed across 12 tertiary hospitals in Andalusia (a region from the south of Spain). A total of 494 patients diagnosed with HNC between 2020 and 2022 at different stages were included in this study, with a minimum follow-up period of 12 months. The BIA assessment was carried out during the first 2 weeks of radical radiotherapy treatment with chemotherapy or other systemic treatments. A multivariate logistic regression analysis of overall survival, complications, hospital admission, and palliative care and its relationship with BIA nutritional assessment was performed.
UNASSIGNED: Significant prognostic factors identified in the multivariable analysis encompassed phase angle (PA), standardized phase angle (SPA), body cell mass (BCM), and BCM index (BCMI). Lower PA and BCM values were significantly associated with adverse clinical outcomes. A BCM threshold above 17 kg/m2 was the most significant predictor for predicting survival within the overall HNC population. The PA values of <5.1° in male and <4.8° in female patients showed the best predictive potential for mortality. Increased PA (as a continuous variable) demonstrated a significantly reduced risk for mortality (OR, 0.64; 95% CI, 0.43-0.94; p < 0.05) and a decreased likelihood of hospital admission (OR, 0.75; 95% CI, 0.52-1.07; p < 0.05). Higher BCM correlated with a lower risk of mortality (OR, 0.88; 95% CI, 0.80-0.96; p < 0.01) and a diminished probability of hospital admission (OR, 0.91; 95% CI, 0.83-0.99; p < 0.05).
UNASSIGNED: BIA is a crucial tool in the nutritional assessment of HNC patients. BCM and PA are the main bioelectrical parameters used to predict clinical outcomes in this population. Future studies are needed to validate BIA variables in a large cohort to ensure whether early intensification of nutritional treatment would improve survival.

UNASSIGNED: The present study was designed to estimate phase angle percentile curves for a broad age range of healthy individuals.
UNASSIGNED: This is a cross-sectional study of healthy Brazilian individuals aged five to 80. InBodyS10 was used to assess phase angle. Reference curves were stratified by sex and estimated using Generalized additive models for location, scale, and shape as a continuous function of age. The phase angle determinants analyzed were physical activity, age, BMI, and SES variables.
UNASSIGNED: Data were analyzed from 2,146 individuals, 1,189 (55.2%) of whom were female. In both sexes, the phase angles showed a similar pattern (an increasing trend from childhood to the teenage phase, followed by stabilization during adult ages and a decrease in old adults). In female, the relationship between phase angle and age were associated with BMI and family income. In the male, the relationship between phase angle and age were associated with skin color and family income.
UNASSIGNED: To the best of our knowledge, it is the first attempt to apply the GAMLSS technique to estimate phase angle percentiles in a healthy population covering most of the life cycle. We also showed that there are different phase angle determinants according to sex.

BACKGROUND: This study was designed to verify whether early posttransplant standardized phase angle (SPhA) determines nutrition status of hemodialysis patients in regard to different nutritional markers and predicts handgrip strength (HGS) 6 months after kidney transplantation.
METHODS: A total of 82 kidney transplant recipients on maintenance hemodialysis treatment entered the study. Nutritional status was evaluated before kidney transplantation, at the hospital discharge date, and 6 months after. We used bioelectrical impedance analysis (BIA), three different malnutrition screening tools, HGS, and anthropometric measurements. Demographic profiles and biochemical nutritional markers were collected. SPhA values, adjusted for age and BMI, were used in our study.
RESULTS: In the early posttransplant period, kidney transplant recipients lost muscle mass, gained fat mass, and developed mostly negative SPhA, accompanied by significantly lower albumin levels. The subjects with lower than median (<-1.46) SPhAdis [the SPhA (at discharge) adjusted for hospitalization time and the baseline SPhA] displayed lower values of albumin concentration (43.4 vs. 45.1 g/l, p = 0.010), hemoglobin (124 vs. 133 g/l, p = 0.016), GNRI (113 vs. 118, p = 0.041), and HGS (30 vs. 33 kg, p = 0.043). These patients had higher ferritin concentrations (420 vs. 258 mkmol/l, p = 0.026), longer inpatient stays (32 vs. 21 days, p < 0.001), and higher MIS scores (3 vs. 1, p = 0.001).
CONCLUSIONS: At the moment of hospital discharge, lower than the median SPhA is related to protein-energy wasting, represented as lower concentrations of nutrition biomarkers and an active inflammatory response. Higher SPhA before kidney transplantation predicts HGS 6 months after kidney transplantation, especially in women.

We aimed to compare the sleep onset, dim light melatonin onset (DLMO) and phase angle (PA) between sleep onset and DLMO of insomnia patients with those of controls, and to examine the difference in these parameters in relation to objective sleep quality.
Participants were recruited from three Public Health Centers in Korea. Actigraphy recordings were conducted for seven days. Five hourly saliva samples were obtained from three hours prior to sleep onset. A total of 48 controls and 64 insomnia patients were analyzed. Nocturnal sleep parameters, DLMO, and PA were compared between the controls and insomnia patients, and between the controls and patients with difficulty in maintaining sleep (DMS). These sleep and circadian parameters were compared among the subgroups divided by wake after sleep onset (WASO) amount.
There were no significant differences in sleep parameters between the control and insomnia groups, and between the controls and DMS subgroup. The sleep onset, DLMO, and PA of the insomnia group or those of DMS subgroup were not different from those of controls. There were significant differences in the sleep onset and DLMO (p < 0.05) among mild, moderate, and severe WASO groups. A regression analysis revealed the earlier DLMO and shorter PA predicted the severity of WASO (p < 0.0001) in total participants.
Insomnia patients exhibited no difference in their sleep timing and melatonin rhythm compared to controls. However, these circadian parameters varied depending on the severity of WASO, and advanced melatonin phase and its shortened phase angle were associated with worsening of sleep maintenance.

BACKGROUND: The malnutrition-inflammation score (MIS) is a nutritional scoring system that has been validated in chronic kidney disease (CKD) stages III-V, especially in dialysis patients. We aimed to test whether the MIS changed in the early stages of CKD and whether it was associated with anthropometry and body composition measurements (BCMs) in patients with CKD.
METHODS: This was a cross-sectional study conducted in the Nephrology Department. A total of 144 patients with CKD were included in the study between May 2017 and December 2017. The MIS was calculated without computing the dialysis vintage in the scoring. Body composition was measured using a portable whole-body bioimpedance spectroscopy device. Anthropometric, laboratory, and other body composition parameters were recorded.
RESULTS: The MIS was increased in patients with CKD. It was negatively correlated with body mass index (BMI), mid-arm muscle circumference (MAMC), handgrip strength, lean tissue index (LTI), fat tissue index (FTI), phase angle (PA), and hemoglobin and albumin concentrations, and it was positively correlated with sex, overhydration, urinary protein excretion and IL-6. A high MIS was significantly correlated with a low LTI (r=-0.274; P=0.001), low FTI (r=-0.179; P=0.032), overhydration (r=0.457; P<0.001) and low PA (r=-0.475; P<0.001). A rather strong correlation was observed between the PA and the MIS. In the multivariate regressions, after adjusting for age, sex, presence of diabetes, handgrip strength, BMI, overhydration, glomerular filtration rate, albumin and IL-6 concentrations, these relationships did not diminish.
CONCLUSIONS: The MIS was strongly linked with indicators of nutrition. As a simple and practical tool for assessing nutritional status, the MIS should be calculated in the early stages of CKD.

Introduction: Direct parameters resistance (R), reactance (Xc), phase angle (PA), capacitance of membrane (Cm), and impedance ratio (Z200/Z5)) determined by bioelectrical impedance analysis (BIA) detect changes in tissue electrical properties and have been found to be a marker of cell membrane function in various diseases. Materials and Method: The cross-sectional study was conducted to investigate whether direct bioimpedance parameters differ in a group of heart failure (HF) patients divided on the basis of the New York Heart Association (NYHA) functional classes I-II and III-IV. BIA was evaluated in 100 patients with HF treated in Clinic of Cardiology and Internal Medicine, Department of Cardiology, Military Hospital, Lublin. Results: In men, lower PA values (p = 0.01), Xc (p < 0.01), Cm (p = 0.02), and higher values of the Z200/Z5 ratio (p < 0.01) were observed in patients classified into NYHA groups III and IV in comparison to those with lower stages of disease. Similar correlations were noted in women (only Cm differences were insignificant). In addition, in men, C-Reactive Protein (CRP) correlated negatively with PA (p < 0.01), Xc (p < 0.01), and Cm (p < 0.01) and positively with the Z200/Z5 index (p < 0.01). There were no similar correlations observed in women. Conclusion: Patients with advanced CHF have altered electrical values. Changes in electrical values may directly reflect tissues as well as the whole-body condition.