The classical ketogenic diet (cKD) is an isocaloric, high fat, very low-carbohydrate diet that induces ketosis, strongly influencing leptin and ghrelin regulation. However, not enough is known about the impact of a long-term cKD. This study evaluated the effects of a 12-month cKD on ghrelin and leptin concentrations in children, adolescents and adults affected by the GLUT1-Deficiency Syndrome or drug resistant epilepsy (DRE). We also investigated the relationship between the nutritional status, body composition and ghrelin and leptin variations. We carried out a longitudinal study on 30 patients: Twenty-five children and adolescents (15 females, 8 ± 4 years), and five adults (two females, 34 ± 16 years). After 12-monoths cKD, there were no significant changes in ghrelin and leptin, or in the nutritional status, body fat, glucose and lipid profiles. However, a slight height z-score reduction (from −0.603 ± 1.178 to −0.953 ± 1.354, p ≤ 0.001) and a drop in fasting insulin occurred. We found no correlations between ghrelin changes and nutritional status and body composition, whereas leptin changes correlated positively with variations in the weight z-score and body fat (ρ = 0.4534, p = 0.0341; ρ = 0.5901, p = 0.0135; respectively). These results suggest that a long-term cKD does not change ghrelin and leptin concentrations independently of age and neurological condition.

The ketogenic diet (KD) is the first line intervention for glucose transporter 1 deficiency syndrome and pyruvate dehydrogenase deficiency, and is recommended for refractory epilepsy. It is a normo-caloric, high-fat, adequate-protein, and low-carbohydrate diet aimed at switching the brain metabolism from glucose dependence to the utilization of ketone bodies. Several variants of KD are currently available. Depending on the variant, KDs require the almost total exclusion, or a limited consumption of carbohydrates. Thus, there is total avoidance, or a limited consumption of cereal-based foods, and a reduction in fruit and vegetable intake. KDs, especially the more restrictive variants, are characterized by low variability, palatability, and tolerability, as well as by side-effects, like gastrointestinal disorders, nephrolithiasis, growth retardation, hyperlipidemia, and mineral and vitamin deficiency. In recent years, in an effort to improve the quality of life of patients on KDs, food companies have started to develop, and commercialize, several food products specific for such patients. This review summarizes the foods themselves, including sweeteners, and food products currently available for the ketogenic dietary treatment of neurological diseases. It describes the nutritional characteristics and gives indications for the use of the different products, taking into account their metabolic and health effects.

The use of the ketogenic diet (KD) as an adjuvant therapy in high-grade gliomas (HGG) is supported by preclinical studies, but clinical data on its effects on metabolism are currently lacking. In this study, we describe the effects of a KD on glucose profile, ketonemia, energy metabolism, and nutritional status, in adults affected by HGG. This was a single-arm prospective study. An isocaloric 3:1 KD was administered for 1 mo. Glucose profile was assessed by using fasting glycemia, insulin, and glycated hemoglobin. To evaluate ketonemia changes, a hand-held ketone meter was used from home. Energy metabolism was assessed by indirect calorimetry. Nutritional status was evaluated through changes in body composition and in lipid and hepatic profile. No changes in fasting glycemia were observed; however, insulinemia dropped to half of baseline levels. The KD shifted the metabolism, rising ketonemia and decreasing glucose oxidation rate to a quarter of the initial values. Moreover, the KD was generally safe. One-month intervention with the KD was able to act upon key metabolic substrates potentially involved in HGG metabolism. The lack of a significant reduction in fasting glycemia should be investigated in future studies.

Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status. To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations. Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients. In naïve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009).In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949).Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error. We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations.