10 resultados para bioelectrical impedance analysis

em Scielo Saúde Pública - SP


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Malnutrition constitutes a major public health concern worldwide and serves as an indicator of hospitalized patients’ prognosis. Although various methods with which to conduct nutritional assessments exist, large hospitals seldom employ them to diagnose malnutrition. The aim of this study was to understand the prevalence of child malnutrition at the University Hospital of the Ribeirão Preto Medical School, University of São, Brazil. A cross-sectional descriptive study was conducted to compare the nutritional status of 292 hospitalized children with that of a healthy control group (n=234). Information regarding patients’ weight, height, and bioelectrical impedance (i.e., bioelectrical impedance vector analysis) was obtained, and the phase angle was calculated. Using the World Health Organization (WHO) criteria, 35.27% of the patients presented with malnutrition; specifically, 16.10% had undernutrition and 19.17% were overweight. Classification according to the bioelectrical impedance results of nutritional status was more sensitive than the WHO criteria: of the 55.45% of patients with malnutrition, 51.25% exhibited undernutrition and 4.20% were overweight. After applying the WHO criteria in the unpaired control group (n=234), we observed that 100.00% of the subjects were eutrophic; however, 23.34% of the controls were malnourished according to impedance analysis. The phase angle was significantly lower in the hospitalized group than in the control group (P<0.05). Therefore, this study suggests that a protocol to obtain patients’ weight and height must be followed, and bioimpedance data must be examined upon hospital admission of all children.

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Body composition analysis is relevant to characterize the nutritional requirements and finishing phase of fish. The aim of this study was to investigate the relationship between ichthyometric (weight, total and standard length, density and yields), bromatological (fat, protein, ash and water content) and bioelectrical-impedance-analysis (BIA) (resistance, reactance, phase angle and composition indexes) variables in the hybrid tambatinga (Colossoma macropomum × Piaractus brachypomus). In a non-fertilized vivarium, 520 juveniles were housed and fed commercial rations. Then, 136 days after hatching (DAH), 15 fish with an average weight of 37.69 g and average total length of 12.96 cm were randomly chosen, anesthetized (eugenol) and subjected to the first of fourteen fortnightly assessments (BIA and biometry). After euthanasia, the following parts were weighed: whole carcass with the head, fillet, and skin (WC); fillet with skin (FS); and the remainder of the carcass with the head (CH). Together, FS and CH were ground and homogenized for the bromatological analyses. Estimates of the body composition and yields of tambatinga, with models including ichthyometric and BIA variables, showed correlation coefficients ranging from 0.81 (for the FS yield) to 1,00 (for the total ash). Similarly, models that included only BIA variables had correlation coefficients ranging from 0.81 (FS and CH yields) to 0.98 (for the total ash). Therefore, in tambatinga, the BIA technique allows the estimation of the yield of the fillet with skin and the body composition (water content, fat, ash, and protein). The best models combine ichthyometric and BIA variables.

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The assessment of fluid volume in neonates by a noninvasive, inexpensive, and fast method can contribute significantly to increase the quality of neonatal care. The objective of the present study was to calibrate an acquisition system and software to estimate the bioelectrical impedance parameters obtained by a method of bioelectrical impedance spectroscopy based on step response and to develop specific equations for the neonatal population to determine body fluid compartments. Bioelectric impedance measurements were performed by a laboratory homemade instrument. The volumes were estimated in a clinical study on 30 full-term neonates at four different times during the first month of life. During the first 24 hours of life the total body water, extracellular water and intracellular water were 2.09 ± 0.25, 1.20 ± 0.19, and 0.90 ± 0.25 liters, respectively. By the 48th hour they were 1.87 ± 0.27, 1.08 ± 0.17, and 0.79 ± 0.21 liters, respectively. On the 10th day they were 2.02 ± 0.25, 1.29 ± 0.21, and 0.72 ± 0.14 liters, respectively, and after 1 month they were 2.34 ± 0.27, 1.62 ± 0.20, and 0.72 ± 0.13 liters, respectively. The behavior of the estimated volume was correlated with neonatal body weight changes, leading to a better interpretation of such changes. In conclusion, this study indicates the feasibility of bioelectrical impedance spectroscopy as a method to help fluid administration in intensive care neonatal units, and also contribute to the development of new equations to estimate neonatal body fluid contents.

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The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.

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Introduction Visceral leishmaniasis (VL) is caused by the intracellular protozoan Leishmania donovani complex. VL may be asymptomatic or progressive and is characterized by fever, anemia, weight loss and the enlargement of the spleen and liver. The nutritional status of the patients with VL is a major determinant of the progression, severity and mortality of the disease, as it affects the clinical progression of the disease. Changes in lipoproteins and plasma proteins may have major impacts in the host during infection. Thus, our goal was evaluate the serum total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides, glucose, albumin, globulin and total protein levels, as well as the body composition, of VL patients before and after treatment. Methods Nutritional evaluation was performed using the bioelectrical impedance analysis (BIA) to assess body composition. Biochemical data on the serum total cholesterol, HDL, LDL, triglycerides, glucose, albumin, globulin and total protein were collected from the medical charts of the patients. Results BIA indicated that both pre-treatment and post-treatment patients exhibited decreased phase angles compared to the controls, which is indicative of disease. Prior to treatment, the patients exhibited lower levels of total body water compared to the controls. Regarding the biochemical evaluation, patients with active VL exhibited lower levels of total cholesterol, HDL, LDL and albumin and higher triglyceride levels compared to patients after treatment and the controls. Treatment increased the levels of albumin and lipoproteins and decreased the triglyceride levels. Conclusions Our results suggest that patients with active VL present biochemical and nutritional changes that are reversed by treatment.

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The objective of the present study was to evaluate the predictive values of percent body fat (PBF) and body mass index (BMI) for cardiovascular risk factors, especially when PBF and BMI are conflicting. BMI was calculated by the standard formula and PBF was determined by bioelectrical impedance analysis. A total of 3859 ambulatory adult Han Chinese subjects (2173 males and 1686 females, age range: 18-85 years) without a history of cardiovascular diseases were recruited from February to September 2009. Based on BMI and PBF, they were classified into group 1 (normal BMI and PBF, N = 1961), group 2 (normal BMI, but abnormal PBF, N = 381), group 3 (abnormal BMI, but normal PBF, N = 681), and group 4 (abnormal BMI and PBF, N = 836). When age, gender, lifestyle, and family history of obesity were adjusted, PBF, but not BMI, was correlated with blood glucose and lipid levels. The odds ratio (OR) and 95% confidence interval (CI) for cardiovascular risk factors in groups 2 and 4 were 1.88 (1.45-2.45) and 2.06 (1.26-3.35) times those in group 1, respectively, but remained unchanged in group 3 (OR = 1.32, 95%CI = 0.92-1.89). Logistic regression models also demonstrated that PBF, rather than BMI, was independently associated with cardiovascular risk factors. In conclusion, PBF, and not BMI, is independently associated with cardiovascular risk factors, indicating that PBF is a better predictor.

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Growth hormone (GH) and glutamine (GLN) are considered bowel trophic factors and are used experimentally after bowel resection. Their clinical uses in short bowel syndrome (SBS) are still not standardized. It is of interest to verify metabolic, nutritional and side effects of the association of GH and GLN in SBS. Three patients, 39 (A), 33 (B), and 01 years old (C) underwent bowel resection with jejunum anastomosis 15 cm (A) and 60 cm (B) distant from the Treitz angle, and 40 cm (C) preserving the ileo cecal valve. GH Saizen (Serono - A), Genotropin (Pharmacia - B), and Norditropin (Novonordisk C) were administered in doses of 0.14 mg /kg/day. GLN (0.4 g/kg/day) was given orally for 10 days (A), 30 days (B) and 60 days to patient C (0.28 g/kg/day). Central TPN and adequate oral diet was administered according to the bowel adaptation phase. On the first day after beginning treatment patient A exhibited symptoms of hypoglycemia. There were no other side effects. After treatment, body weight was higher and analysis by bioelectrical impedance showed more lean mass and less fat mass compared to pre-treatment measurements. Nitrogen retention was progressively higher with treatment. Simultaneous treatment with GH and GLN does not cause significant side effects, and is associated with a favorable distribution of the body compartments and nitrogen retention in patients with the short bowel syndrome.

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Our objective was to determine whether anthropometric measurements of the midarm (MA) could identify subjects with whole body fat-free mass (FFM) depletion. Fifty-five patients (31% females; age: 64.6 ± 9.3 years) with mild/very severe chronic obstructive pulmonary disease (COPD), 18 smokers without COPD (39% females; age: 49.0 ± 7.3 years) and 23 never smoked controls (57% females; age: 48.2 ± 9.6 years) were evaluated. Spirometry, muscle strength and MA circumference were measured. MA muscle area was estimated by anthropometry and MA cross-sectional area by computerized tomography (CT) scan. Bioelectrical impedance was used as the reference method for FFM. MA circumference and MA muscle area correlated with FFM and biceps and triceps strength. Receiver operating characteristic curve analysis showed that MA circumference and MA muscle area cut-off points presented sensitivity and specificity >82% to discriminate FFM-depleted subjects. CT scan measurements did not provide improved sensitivity or specificity. For all groups, there was no significant statistical difference between MA muscle area [35.2 (29.3-45.0) cm²] and MA cross-sectional area values [36.4 (28.5-43.3) cm²] and the linear correlation coefficient between tests was r = 0.77 (P < 0.001). However, Bland-Altman plots revealed wide 95% limits of agreement (-14.7 to 15.0 cm²) between anthropometric and CT scan measurements. Anthropometric MA measurements may provide useful information for identifying subjects with whole body FFM depletion. This is a low-cost technique and can be used in a wider patient population to identify those likely to benefit from a complete body composition evaluation.

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Our objective was to determine if automated peritoneal dialysis (APD) leads to changes in nutritional parameters of patients treated by continuous ambulatory peritoneal dialysis (CAPD). Twenty-six patients (15 males; 50.5 ± 14.3 years) were evaluated during CAPD while training for APD and after 3 and 6 months of APD. Body fat was assessed by the sum of skinfold thickness and the other body compartments were assessed by bioelectrical impedance. During the 6-month follow-up, 12 patients gained more than 1 kg (GW group), 8 patients lost more than 1 kg (LW group), and 6 patients maintained body weight (MW group). Except for length on dialysis that was longer for the LW group compared with the GW group, no other differences were found between the groups at baseline. After 6 months on APD, the LW group had a reduction in body fat (24.5 ± 7.7 vs 22.1 ± 7.3 kg; P = 0.01), body cell mass (22.6 ± 6.2 vs 21.6 ± 5.8 kg, P = 0.02) and phase angle (5.4 ± 0.9 vs 5.1 ± 0.8 degrees, P = 0.004). In the GW group, body fat (25 ± 7.6 vs 27.2 ± 7.6 kg, P = 0.001) and body cell mass (20.1 ± 3.9 vs 20.8 ± 4.0 kg, P = 0.05) were increased. In the present study, different patterns of change in body composition were found. The length of previous dialysis treatment seems to be the most important factor in determining these nutritional modifications.

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The penetration resistance (PR) is a soil attribute that allows identifies areas with restrictions due to compaction, which results in mechanical impedance for root growth and reduced crop yield. The aim of this study was to characterize the PR of an agricultural soil by geostatistical and multivariate analysis. Sampling was done randomly in 90 points up to 0.60 m depth. It was determined spatial distribution models of PR, and defined areas with mechanical impedance for roots growth. The PR showed a random distribution to 0.55 and 0.60 m depth. PR in other depths analyzed showed spatial dependence, with adjustments to exponential and spherical models. The cluster analysis that considered sampling points allowed establishing areas with compaction problem identified in the maps by kriging interpolation. The analysis with main components identified three soil layers, where the middle layer showed the highest values of PR.