Intestinal fermentation in patients with self-reported food hypersensitivity: painful, but protective?

Purpose: Enterometabolic disturbances may cause meal-related symptoms. We performed a functional evaluation of the intestinal microflora in patients with unexplained, self-reported food hypersensitivity by measuring fecal short-chain fatty acids (SCFAs). Patients and methods: Thirty-five consecutive patients with self-reported food hypersensitivity and 15 healthy volunteers of similar age, gender, and body mass index collected all feces for 72 hours. Fecal concentrations of acetic, propionic, n-butyric, i-butyric, n-valeric, i-valeric, n-caproic, and i-caproic acids were analyzed by gas-liquid chromatography. Concentrations and excretions (output) of SCFAs in patients and controls were compared and related to gastrointestinal symptoms. Results: Despite nonsignificant differences between patients and controls for both total and individual SCFA concentrations and excretions, n-butyric acid comprised a higher (P = 0.035) and acetic acid a lower (P = 0.012) proportion of total SCFA in patients compared to controls. There were no significant correlations between symptom scores and concentrations or excretions of individual or total SCFAs, but the proportion of n-butyric acid was significantly higher in patients with severe symptoms compared to patients with moderate symptoms (P = 0.016). Conclusion: The results indicate an enterometabolic disturbance in patients with self-reported food hypersensitivity. Higher proportions of n-butyric acid may be related to abdominal symptom generation, but may also protect against organic bowel disease. Further studies are needed to clarify these aspects

Monitoring children and adolescents with severe obesity: body mass index (BMI), BMI z‐score or percentage above the International Obesity Task Force overweight cut‐off?

Aim: Body mass index (BMI) metrics are widely used as a proxy for adiposity in children with severe obesity. The BMI expressed as the percentage of a cut‐off percentile for overweight or obesity has been proposed as a better alternative than BMI z‐scores when monitoring children and adolescents with severe obesity. Methods: Annual changes in BMI, BMI z‐score and the percentage above the International Obesity Task Force overweight cut‐off (%IOTF‐25) were compared with dual‐energy X‐ray absorptiometry (DXA) derived body fat (%BF‐DXA) in 59 children and adolescents with severe obesity. Results: The change in %BF‐DXA was correlated with the change in %IOTF‐25 (r = 0.68) and BMI (r = 0.70), and somewhat less with the BMI z‐score (r = 0.57). Cohen's Kappa statistic to detect an increase or decrease in %BF‐DXA was fair for %IOTF‐25 (κ = 0.25; p = 0.04) and BMI (κ = 0.33; p = 0.01), but not for the BMI z‐score (κ = 0.08; p = 0.5). The change in BMI was positively biased due to a natural increase with age. Conclusion: Changes in the BMI metrics included in the study are associated differently with changes in %BF‐DXA. The BMI z‐score is widely used to monitor changes in adiposity in children and adolescents with severe obesity, but the %IOTF‐25 might be a better alternative

Comparison of nutritional risk screening with NRS2002 and the GLIM diagnostic criteria for malnutrition in hospitalized patients

Nutritional risk screening, to identify patients at risk of malnutrition, is the first step in the prevention and treatment of malnutrition in hospitalized patients, and should be followed by a thorough nutritional assessment resulting in a diagnosis of malnutrition and subsequent treatment. In 2019, a consensus on criteria has been suggested for the diagnosis of malnutrition by the Global Leadership Initiative for Malnutrition (GLIM). This study investigates the diagnosis of malnutrition in hospitalized patients using nutritional risk screening and the diagnostic assessment suggested by GLIM. Hospitalized patients (excluding cancer, intensive care, and transmissible infections) who underwent nutritional risk screening (by NRS2002) were included. Nutritional risk screening was followed by anthropometric measurements including measurement of muscle mass, assessment of dietary intake and measurement of serum C-reactive protein (CRP) for inflammation in all patients. Malnutrition was diagnosed according to the GLIM-criteria. In total, 328 patients (median age 71 years, 47% women, median length of stay 7 days) were included. Nutritional risk screening identified 143 patients as at risk of malnutrition, while GLIM criteria led to a diagnosis of malnutrition in 114 patients. Of these 114 patients, 77 were also identified as at risk of malnutrition by NRS2002, while 37 patients were not identified by NRS2002. Malnutrition was evident in fewer patients than at risk of malnutrition, as expected. However, a number of patients were malnourished who were not identified by the screening procedure. More studies should investigate the importance of inflammation and reduced muscle mass, which is the main difference between nutritional risk screening and GLIM diagnostic assessment.publishedVersio