Ketogenic diet for epilepsy and obesity: Is it the same?

The term "ketogenic diet" (KD) is used for a wide variety of diets with diverse indications ranging from obesity to neurological diseases, as if it was the same diet. This terminology is confusing for patients and the medical and scientific community. The term "ketogenic" diet implies a dietary regimen characterized by increased levels of circulating ketone bodies that should be measured in blood (beta-hydroxybutyrate), urine (acetoacetate) or breath (acetone) to verify the "ketogenic metabolic condition". Our viewpoint highlights that KDs used for epilepsy and obesity are not the same; the protocols aimed at weight loss characterized by low-fat, low-CHO and moderate/high protein content are not ketogenic by themselves but may become mildly ketogenic when high calorie restriction is applied. In contrast, there are standardized protocols for neurological diseases treatment for which ketosis has been established to be part of the mechanism of action. Therefore, in our opinion, the term ketogenic dietary therapy (KDT) should be reserved to the protocols considered for epilepsy and other neurological diseases, as suggested by the International Study Group in 2018. We propose to adjust the abbreviations in VLCHKD for Very Low CarboHydrate Ketogenic Diet and VLEKD for Very Low Energy Ketogenic Diet, to clarify the differences in dietary composition. We recommend that investigators describe the researchers describing efficacy or side effects of KDs, to clearly specify the dietary protocol used with its unique acronym and level of ketosis, when ketosis is considered as a component of the diet's mechanism of action.

Nutrition education in medical schools (NEMS) project: Promoting clinical nutrition in medical schools - Perspectives from different actors.

BACKGROUND & AIMS: Nutrition education is not adequately represented in the medical curriculum, and this prompted the European Society for Clinical Nutrition and Metabolism (ESPEN) to launch the Nutrition Education in Medical Schools (NEMS) Project in 2017. The aim of this original paper was to describe the perspectives of different actors in the promotion of nutrition education in medical schools. METHODS: On 11 November 2021, an online meeting was held on this topic, where nine representatives from different backgrounds participated in the scientific programme. More than 640 participants registered to this webinar. RESULTS: The different models of Nutrition Education in Medical Schools were introduced by Prof. Cristina Cuerda (Spain) and Prof. Maurizio Muscaritoli (Italy). The students' perspective was given by Ms. Alexandra Archodoulakis (Germany) and Ms. Sila Gürbüz (Turkey), representing the European Medical Students' Association. The dietitian's perspective was given by Dr. Kirsten Berk (The Netherlands), whereas Dr. Matti Aapro (Switzerland) gave the medical doctor (oncology)'s perspective. Ms. Clare Farrand (Australia) gave the WHO perspective and Dr. Kristiina Patja (Finland) explained the healthy lifestyle teaching to medical students. Lastly, Prof. Michael Chourdakis (Greece) and Prof. Zeljko Krznaric (Croatia) hosted the round-table discussion. CONCLUSIONS: There was strong agreement among the representatives from different settings joining this ESPEN initiative that increasing nutritional knowledge and skills of young doctors is now possible and will launch a virtuous cycle that will proactively involve all the other healthcare professionals working in the nutritional field.

[Intermittent fasting in science and practice; what are the effects on weight and cardiometabolic health?] / Intermitterend vasten in wetenschap en praktijk.

Intermittent fasting (IF) is a broad concept and covers several fasting regimes. Studies of 'early time restricted feeding' and 'alternate day fasting' with energy restriction show a greater effect on weight and cardiometabolic health in overweight people in the short term, compared to a continuous caloric restriction (CCR). 'Late time restricted feeding' seems to have no or unfavorable effects. Long-term studies (up to 2 years) suggest that IF regimens are not superior to continuous caloric restriction. The few studies available show a similar compliance and metabolic adaptation between IF and CCR. There is insufficient knowledge about long-term safety in various groups of people, the influence of dietary quality and the practical feasibility of IF regimes. As a result, no recommendations can yet be made on the use of IF in the treatment of overweight and related diseases.

Diet-induced weight loss and markers of endothelial dysfunction and inflammation in treated patients with type 2 diabetes.

BACKGROUND & AIMS: Overweight and obesity increase cardiovascular mortality in patients with type 2 diabetes (T2D). In a recent trial, however, diet-induced weight loss did not reduce the cardiovascular risk of patients with T2D, possibly due to the parallel intensive medical treatment. We investigated the effect of diet-induced weight loss on cardiovascular risk factors in overweight and obese patients with T2D, and whether this effect was influenced by the use of statins, ACE inhibitors, metformin and duration of T2D. METHODS: Patients with T2D and BMI >27 were subjected to an energy-restricted diet during 4 months. Before and after intervention, plasma levels of sICAM-1, sVCAM-1, hsCRP, vWF and classical biomarkers were measured. The association of the change in biomarker levels with medication use and T2D history, corrected for age, sex and change in insulin dose, was tested by matched linear regression analyses. RESULTS: In 131 patients, the diet resulted in weight loss of 10.2 kg (95%CI 9.2, 11.3; p < 0.001), improved median levels of HbA1c (-7.0 mmol/mol (95%CI -8.5, -5.0); p < 0.001), LDL cholesterol (-0.2 mmol/L (95%CI -0.4, -0.1); p < 0.001), sICAM-1 (-22.4 ng/mL (95%CI -37.1, -8.7); p = 0.001), vWF (-3.9 IU/mL (95%CI -6.4, -1.4); p = 0.003) and hs-CRP (-0.6 mg/L (95%CI -1.2, -0.2); p = 0.007), but did not affect sVCAM-1 levels (1.6 ng/mL (95%CI -41.5, 48.6); p = 0.949). Duration of T2D and medical treatment were not associated with these effects, except for an association between statin use and change in sVCAM-1, where statin users improved more. CONCLUSION: Diet-induced weight loss reduced the levels of biomarkers of endothelial dysfunction and inflammation in overweight and obese patients with T2D independently of medication use and T2D duration. Even on intensive medical drug treatment as well as after a long history of T2D, patients may still profit from diet-induced weight reduction.

Repeated measures with zeros.

Consider repeated measures data with many zeros. For the case with one grouping factor and one repeated measure, we examine several models, assuming that the nonzero data are roughly lognormal. One of the simplest approaches is to model the zeros as left-censored observations from the lognormal distribution. A random effect is assumed for subjects. The censored model makes a strong assumption about the relationship between the zeros and the nonzero values. To check on this, you can instead assume that some of the zeros are 'true' zeros and model them as Bernoulli. Then the other values are modeled with a censored lognormal. A logistic model is used for the Bernoulli p, the probability of a true nonzero. The fit of the pure left-censored lognormal can be assessed by testing the hypothesis that p is 1, as described by Moulton and Halsey. The model can also be simplified by omitting the censoring, leaving a logistic model for the zeros and a lognormal model for the nonzero values. This is approximately equivalent to modeling the zero and nonzero values separately, a two-part model. In contrast to the censored model, this model assumes only a slight relationship (a covariance component) between the occurrence of zeros and the size of the nonzero values. The models are compared in terms of an example with data from children's private speech.

Computing for incomplete repeated measures.

Repeated-measures experiments involve two or more intended measurements per subject. If the within-subjects design is the same for each subject and no data are missing, then the analysis is relatively simple and there are readily available programs that do the analysis automatically. However, if the data are incomplete, and do not have the same arrangement for each subject, then the analysis becomes much more difficult. Beginning with procedures that are not optimal but are comparatively simple, we discuss unbalanced linear model analysis and then normal maximum likelihood (ML) procedures. Included are ML and REML (restricted maximum likelihood) estimators for the mixed model and also estimators for a model that allows arbitrary within-subject covariance matrices. The objective is to give procedures that can be implemented with available software.