The treatment of obesity and cardiovascular diseases is one of the most difficult and important challenges nowadays. Weight loss is frequently offered as a therapy and is aimed at improving some of the components of the metabolic syndrome. Among various diets, ketogenic diets, which are very low in carbohydrates and usually high in fats and/or proteins, have gained in popularity. Results regarding the impact of such diets on cardiovascular risk factors are controversial, both in animals and humans, but some improvements notably in obesity and type 2 diabetes have been described. Unfortunately, these effects seem to be limited in time. Moreover, these diets are not totally safe and can be associated with some adverse events. Notably, in rodents, development of nonalcoholic fatty liver disease (NAFLD) and insulin resistance have been described. The aim of this review is to discuss the role of ketogenic diets on different cardiovascular risk factors in both animals and humans based on available evidence.
BackgroundGrowth arrest-specific gene 6 (Gas6), a vitamin K-dependent protein interacting with anionic phospholipids and TAM tyrosine kinase receptors, is elevated in plasma of septic patients. Previous studies did not find different levels between survivors and non-survivors at admission because either they included a low number of patients (<50) or a low number of non-survivors (5%).ObjectivesTo determine, in a larger cohort of septic patients comprising an expected number of non-survivors, the performance of the plasma level of Gas6 and its soluble receptor Axl (sAxl) within 24 hours of admission to predict in-ICU mortality.PatientsSeptic adults with or without shock.MethodsGas6 and sAxl were prospectively measured by ELISA at day 0, 3, 7, and then weekly until discharge or death.ResultsWe evaluated 129 septic patients, including 82 with and 47 without shock, with in-ICU mortality rate of 19.4% and in-hospital mortality rate of 26%. Gas6 level was higher in non-survivors than in survivors (238 vs. 167%, P = 0.003); this difference remained constant during the ICU stay. The area under the ROC curve for Gas6 (0.695 [95% CI: 0.58–0.81]) was higher than for sAxl, procalcitonin, CRP, IL-1beta, IL-6 and-alpha, and slightly higher than for IL-8, IL-10, SOFA and APACHEII scores in predicting in-ICU mortality. Considering 249% as a cut-off value, Gas6 measurement had a negative predictive value for mortality of 87%.ConclusionIt seems that Gas6 plasma level within 24 hours of ICU admission may predicts in-ICU mortality in patients with sepsis. If our result are confirmed in external validation, Gas6 plasma level measurement could contribute to the identification of patients who may benefit most from more aggressive management.
Purpose of Review To assess the pleiotropic effects of ketogenic diets (KD) on glucose control, changes in medication, and weight loss in individuals with type 2 diabetes, and to evaluate its practical feasibility Recent Findings KD results in improved HbA1c already after 3 weeks, and the effect seems to persist for at least 1 year. This is associated with a reduction in glucose-lowering medications. The weight loss observed after a short time period seems to be maintained with a long-term diet. Adequate support (supportive psychological counseling, enhancing positive affectivity, reinforcing mindful eating) is necessary to achieve a benefit and to assure adherence. Summary Despite the documented decrease in HbA1, a definitive causal effect of KD remains to be proven. KD should be performed under strict medical supervision. Future research should clarify how compliance can be maximized and how ketosis can be optimally monitored.
Background Quantification of dietary intake is key to the prevention and management of numerous metabolic disorders. Conventional approaches are challenging, laborious, and lack accuracy. The recent advent of depth-sensing smartphones in conjunction with computer vision could facilitate reliable quantification of food intake. Objective The objective of this study was to evaluate the accuracy of a novel smartphone app combining depth-sensing hardware with computer vision to quantify meal macronutrient content using volumetry. Methods The app ran on a smartphone with a built-in depth sensor applying structured light (iPhone X). The app estimated weight, macronutrient (carbohydrate, protein, fat), and energy content of 48 randomly chosen meals (breakfasts, cooked meals, snacks) encompassing 128 food items. The reference weight was generated by weighing individual food items using a precision scale. The study endpoints were (1) error of estimated meal weight, (2) error of estimated meal macronutrient content and energy content, (3) segmentation performance, and (4) processing time. Results In both absolute and relative terms, the mean (SD) absolute errors of the app’s estimates were 35.1 g (42.8 g; relative absolute error: 14.0% [12.2%]) for weight; 5.5 g (5.1 g; relative absolute error: 14.8% [10.9%]) for carbohydrate content; 1.3 g (1.7 g; relative absolute error: 12.3% [12.8%]) for fat content; 2.4 g (5.6 g; relative absolute error: 13.0% [13.8%]) for protein content; and 41.2 kcal (42.5 kcal; relative absolute error: 12.7% [10.8%]) for energy content. Although estimation accuracy was not affected by the viewing angle, the type of meal mattered, with slightly worse performance for cooked meals than for breakfasts and snacks. Segmentation adjustment was required for 7 of the 128 items. Mean (SD) processing time across all meals was 22.9 seconds (8.6 seconds). Conclusions This study evaluated the accuracy of a novel smartphone app with an integrated depth-sensing camera and found highly accurate volume estimation across a broad range of food items. In addition, the system demonstrated high segmentation performance and low processing time, highlighting its usability.
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