Thyroid markers and body composition predict LDL-cholesterol change in lean healthy women on a ketogenic diet: experimental support for the lipid energy model.

Introduction: There is a large heterogeneity in LDL-cholesterol change among individuals adopting ketogenic diets. Interestingly, lean metabolically healthy individuals seem to be particularly susceptible, with an inverse association between body mass index and LDL-cholesterol change. The lipid energy model proposes that, in lean healthy individuals, carbohydrate restriction upregulates systemic lipid trafficking to meet energy demands. To test if anthropometric and energy metabolism markers predict LDL-cholesterol change during carbohydrate restriction. Methods: Ten lean, healthy, premenopausal women who habitually consumed a ketogenic diet for ≥6 months were engaged in a three-phase crossover study consisting of continued nutritional ketosis, suppression of ketosis with carbohydrate reintroduction, and return to nutritional ketosis. Each phase lasted 21 days. The predictive performance of all available relevant variables was evaluated with the linear mixed-effects models. Results: All body composition metrics, free T3 and total T4, were significantly associated with LDL-cholesterol change. In an interaction model with BMI and free T3, both markers were significant independent and interacting predictors of LDL-cholesterol change. Neither saturated fat, HOMA-IR, leptin, adiponectin, TSH, nor rT3 was associated with LDL-cholesterol changes. Discussion: Among lean, healthy women undergoing carbohydrate restriction, body composition and energy metabolism markers are major drivers of LDL-cholesterol change, not saturated fat, consistent with the lipid energy model.

Distinctions between survivors and non-survivors with SARS-CoV-2 vaccine-induced thrombotic thrombocytopenia: A systematic review and meta-analysis.

Vaccine-inducing immune thrombocytopenia, thrombosis, and bleeding emerge as infrequent and potential complications with mortality risk in healthy subjects. However, differences between survivors and non-survivors with SARS-CoV-2 vaccine-induced thrombotic thrombocytopenia (VITT) are unclear. Methods: According to the PRISMA statement, we conducted a systematic review and meta-analysis, and the protocol was registered in PROSPERO. The main objective is to identify differences among survivors and non-survivors of SARS-CoV-2 VITT patients. We systematically searched through PubMed, Scopus, and Web of Science. We included cohorts, case series, and case reports. We classified bleeding complications according to the ISTH definition. Statistics: unpaired Student's t-test or one-way ANOVA, Wilcoxon, and Kruskal-Wallis. Results: We systematically searched from January 2021 to June 2021 and identified 51 studies that included 191 patients. Non-survivors had the most severe thrombocytopenia (p 0.02) and lower fibrinogen measurements (p 0.01). Subjects vaccinated with mRNA vaccines (BNT162b2 and mRNA-1273) had an earlier onset of adverse events following immunization (p 0.001). We identified a higher trend of overall thrombotic events (p 0.001) in recipients of viral mechanism-dependent vaccines (Table 2). Non-survivors with cerebral venous sinus thrombosis (CVST) had more severe thrombocytopenia (p 0.01) than survivors with CVST. Finally, 61 % of survivors and 50 % with thrombosis received heparin. Conclusion: We identified more severe thrombocytopenia, lower fibrinogen measurements, and a higher trend of overall thrombotic events, including CVST and thrombotic storm, particularly with viral mechanisms-dependent vaccines in non-survivors VITT patients.