Annals of Nutrition and Metabolism最新文献

Background: The nitrogen balance estimates a protein net difference. However, since it has a number of limitations, it is important to consider the trajectory of the nitrogen balance in the clinical course of critically ill patients.

Objectives: We herein exploratively classified the nitrogen balance trajectory using a machine learning method.

Method: This is a post hoc analysis of a single-center prospective study for the patients admitted to our Emergency and Critical Center ICU. The nitrogen balance was evaluated with 24-h urine collection from ICU days 1-10 with 9 points. K-means clustering was performed to classify the nitrogen balance trajectory. We also evaluated factors associated with uncovered clusters.

Results: Seventy-six eligible patients were included in the present study. After clustering, the nitrogen balance trajectory was classified into 4 classes. Class 1 was trajected as a negative balance over 10 days (24 patients). Class 2 had a positive conversion on day 3 or 4 (8 patients). Class 3 had a positive conversion on day 8 or 9 (28 patients). Class 4 initially had a positive balance and then converted to a negative balance (16 patients). Sepsis complication and steroid use were associated with negative nitrogen balance trajectory. Class 2 was associated with lower length of hospital stay and femoral muscle volume loss, however, frequently had frailty and sarcopenia on admission. Active nutrition therapy intention was not correlated with positive trajectory.

Conclusions: The nitrogen balance trajectory in critically ill patients may be classified into 4 classes for clinical practice. Among patients emergently admitted to the ICU, the positive conversion of the nitrogen balance might be delayed over 10 days.

Introduction: Several researchers have focused on the role of skeletal muscle in metabolic problems in recent years. We aimed to evaluate influence of sleeve gastrectomy on skeletal muscular fat infiltration determined by magnetic resonance imaging in patients with metabolic syndrome (MetS).

Methods: Sixty five MetS patients (male/female, 20/45; mean age, 35.5 years ± 6.6 [standard deviation]; age range, 22-59 years) enrolled in our study. Prior to and 1 year after sleeve gastrectomy, patients underwent routine measurement of skeletal muscular fat concentration (denoted by proton density fat fraction, PDFF) and chemical indexes. The associations of skeletal muscular fat concentration with other variables were determined using multiple linear regression analysis.

Results: Difference between skeletal muscular PDFF at baseline (4.46 ± 2.01%) and PDFF 1-year after sleeve gastrectomy (3.00 ± 1.47%) was significant. Multivariable predictors of baseline skeletal muscular PDFF by descending order of standardized coefficient were fasting serum glucose (0.459; p = 0.001), age (0.395; p < 0.001), systolic pressure (0.319; p = 0.029), insulin (0.030; p = 0.026), white cell count (0.302; p = 0.007), diastolic pressure (-0.301; p = 0.046), and total alkaline phosphatase (-0.474; p < 0.001) all at baseline. Furthermore, multivariable predictors of change in PDFF were serum total cholesterol (3.510; p < 0.001), total alkaline phosphatase (0.535; p < 0.001), estrogen (0.457; p < 0.001), diastolic pressure (0.352; p < 0.001), systolic pressure (-0.409; p < 0.001), high-density lipoprotein cholesterol (-0.719; p < 0.001), insulin (-0.774; p < 0.001), C-reactive protein (-0.900; p < 0.001), triglyceride (-1.756; p < 0.001), and low-density lipoprotein cholesterol (-2.854; p < 0.001) all at baseline.

Conclusion: Sleeve gastrectomy could alleviate myosteatosis in MetS patients during 1-year follow-up. The extent of remission on skeletal muscular fat infiltration after sleeve gastrectomy was influenced by baseline metabolic problems related to serum glucose, serum lipid, and blood pressure level.

Introduction: It has been well recognized that sarcopenia is closely related with osteoporosis, while the relationship between bone mass at different sites and muscle mass remains largely unexplored. This study aims to explore the relationship between bone mass at different sites and skeletal muscle mass in older adults.

Methods: A total of 228 patients over 65 years old were enrolled in this study, and then 180 valid participants with accessible dual-energy X-ray absorptiometry (DXA) scanning data and absence of malignant tumors, mobility disorders, serious liver and kidney disease, and cardiac insufficiency were selected (138 male and 42 female). These individuals were further divided into control group and low skeletal muscle mass index (SMI) group. DXA scanning was used to access skeletal muscle mass and bone mass. SMI or body mass index was defined as appendicular muscle mass or weight divided by squared height, respectively. Low SMI <7.0 kg/m2 in male or <5.4 kg/m2 in female was defined as low SMI; while the bone density score at or below 2.5 standard deviations (T-score) below normal peak bone values, was regarded as osteoporosis.

Results: The average age of enrolled patients was 82.72 years; the ratios of osteoporosis, low SMI, and low SMI with osteoporosis were 48.8%, 23.3%, and 15.0%, respectively. Compared with the control group, the prevalence of osteoporosis was higher, and the total bone mass and bone mass at various sites including limbs, spine, and pelvis, were all lower in low SMI group. Correlation analysis showed that SMI was positively related with total bone mass and bone mass at various sites. Covariance analysis showed that only total bone mass and appendicular bone mass decreased with decreasing SMI. After multiple adjustment, osteoporosis was positively related with the prevalence of low SMI, as evidenced by logistic regression analysis (odds ratio = 1.33, 95% confidential interval: 1.04-3.24, p = 0.045). Furthermore, compared with the highest quartile of appendicular bone mass, the lowest quartile was related with the increasing prevalence of low SMI (odds ratio = 7.29, 95% confidential interval: 1.21-67.45, p = 0.042).

Conclusion: Compared with the other sites, the bone mass reduction at limbs of older adults was positively associated with skeletal muscle loss. It may be more beneficial to increase bone mass at the limbs for improved sarcopenia prevention and therapy. Further investigations are needed to explore the effects of other confounders (e.g., energy, calcium and vitamin D intake, and physical activity) on the osteoporosis and sarcopenia in older adults.

Introduction: The life expectancy of older adults continues to increase; however, knowledge regarding their total energy requirements is lacking. This study aimed to compare the total energy expenditure (TEE) of older adults ≥80 years measured using doubly labelled water (DLW), with estimated TEE. The hypothesis was that the Mifflin, Ikeda, and Livingston equations will more closely estimate energy requirements than the commonly used Schofield equation.

Methods: Resting metabolic rate (RMR) and TEE were measured using the reference methods of indirect calorimetry and DLW, respectively. Bland-Altman plots compared measured RMR and TEE with predicted RMR using equations (Mifflin, Ikeda, Livingston, Schofield) and predicted TEE (predicted RMR × physical activity level).

Results: Twenty-one older adults (age range 80.7-90.1 years, BMI 26.1 ± 5.5 kg/m2) were included. The Schofield equation demonstrated the greatest bias from measured RMR, overestimating approximately up to double the mean difference (865 ± 662 kJ/day) compared with the three other equations. The Schofield equation exhibited the greatest bias (overestimation of 641 ± 1,066 kJ/day) compared with measured TEE. The other three equations underestimated TEE, with the least bias from Ikeda (37 ± 1,103 kJ/day), followed by Livingston (251 ± 1,108 kJ/day), and Mifflin (354 ± 1,140 kJ/day). Data are mean ± SD.

Conclusions: In older adults ≥80 years, the Ikeda, Mifflin, and Livingston equations provide closer estimates of TEE than the widely used Schofield equation. The development of nutrition guidelines therefore should consider the utilization of equations which more accurately reflect age-specific requirements.

Introduction: Cancer cachexia occurs in cancer patients more frequently as the cancer progresses, with a negative impact on treatment outcomes. In this study, we sought to clarify the clinical impact of a cancer cachexia index (CXI) in patients with gastric cancer (GC) undergoing gastrectomy.

Methods: Between January 2013 and December 2018, we reviewed data from 556 patients treated for GC at our hospital. CXI was calculated using skeletal muscle index (SMI), serum albumin, and neutrophil-lymphocyte ratios (NLR). Patients were divided into high (n = 414) or low CXI (n = 142) groups. We investigated the clinical impact of CXI in patients with GC undergoing gastrectomy.

Results: Multivariate analyses of 5-year overall survival (OS) and cancer-specific survival (CSS) rates indicated that a low CXI was independently associated with unfavorable outcomes for patients with GC. In multivariate analyses, SMI was independent predictor of OS but not CSS. NLR was not an independent predictor of either OS or CSS. Complication incidences (≥ Clavien Dindo 3) were non-significantly higher in the low (vs. high) CXI group.

Conclusion: CXI was a more valuable prognostic biomarker when compared with SMI or NLR in GC patients undergoing gastrectomy. We suggest that patients with low CXI values should be given more comprehensive treatment, including exercise and nutritional therapy to improve clinical outcomes.

Introduction: Protein leverage (PL) is the phenomenon whereby a dominant appetite for protein drives overconsumption of energy with a decline in the ratio of protein to fat and carbohydrate in the diet. PL has been independently verified in several randomized control trials, and its predictions are supported by diet surveillance data. Our aim in the present study was to test whether surgical intervention through gastric bypass will ameliorate the PL effect.

Methods: Ten patients with gastric bypass (2-5 years postsurgical time) were given ad libitum access to study food comprising 10%, 15%, or 25% protein and no access to other foods for 3 days while controlling food palatability and variety. Food intake was measured, and energy and nutrient intakes were calculated. Body weight, blood chemistry, lipid profile, hormones (insulin, leptin, and ghrelin), and creatinine were determined before and after each experimental period.

Results: The gastric bypass patients in our study did not show evidence for protein intake regulation as predicted under PL but ate to constant total energy intake on the 10%, 15%, and 25% protein diets with protein intake varying significantly. Patients lost weight in the three study periods, but significant weight loss was observed only on the 15% protein diet.

Conclusion: Our results suggest that gastric bypass might disengage the PL mechanism, thus ameliorating an appetite-specific mechanism that drives energy overconsumption in modern food environments.