Influenza and obesity: its odd relationship and the lessons for COVID-19 pandemic.

AIMS: Analyze the relationship between obesity and influenza. METHODS: Basal hormone milieu, defective response of both innate and adaptive immune system and sedentariness are major determinants in the severity of influenza viral infection in obese patients. Being overweight not only increases the risk of infection and of complications for the single obese person, but a large prevalence of obese individuals within the population might increase the chance of appearance of more virulent viral strain, prolongs the virus shedding throughout the total population and eventually might increase overall mortality rate of an influenza pandemic. RESULTS: Waiting for the development of a vaccination against COVID-19, isolation of positive cases and social distancing are the primary interventions. Nonetheless, evidence from previous influenza pandemics suggests the following interventions aimed at improving immune response: (1) lose weight with a mild caloric restriction; (2) include AMPK activators and PPAR gamma activators in the drug treatment for obesity associated with diabetes; and (3) practice mild-to-moderate physical exercise. CONCLUSIONS: Due to prolonged viral shedding, quarantine in obese subjects should likely be longer than normal weight individuals.

Visit-to-visit blood pressure variability in patients with type 2 diabetes with and without previous history of cardiovascular disease.

OBJECTIVE: Visit-to-visit variability in SBP is a risk factor for cardiovascular disease (CVD) in type 2 diabetes (T2DM) but little is known on whether in T2DM this differs according to presence or absence of previous CVD. METHODS: We retrospectively assessed the coefficient of variation (standard deviation/mean) of mean SBP (SBP-CV) in 970 patients (44% with established CVD) attending at least four times our secondary care diabetes clinic in 2015-2016 to estimate their risk of CVD-related events using the 10-year UKPDS Risk Engine. RESULTS: Patients with established CVD had a higher SBP-CV (10.3 ±â€Š4.8%) than patients without CVD (8.9 ±â€Š4.3%; P < 0.001) as confirmed by the progressively higher prevalence of established CVD in tertiles of SBP-CV (36.6, 46.1, and 52.0%; P < 0.001), in association with more aggressive and complex drug regimens. On the basis of the 10-year UKPDS Risk Engine, higher SBP-CV values were associated with increased risks of the CVD outcomes regardless of the previous history of CVD in multivariate models. CONCLUSION: Visit-to-visit variability of SBP was greater in T2DM patients with that in those without previous history of CVD, and maintained an independent association with higher estimated risk of CVD-related events regardless of the history of CVD, suggesting that its prognostic significance is relevant in the entire CVD continuum of patients with T2DM.

Fasting Whole-Body Energy Homeostasis and Hepatic Energy Metabolism in Nondiabetic Humans with Fatty Liver.

BACKGROUND: Fatty liver is believed to be sustained by a higher than normal adipose-derived NEFA flux to the liver. Also, hepatic energy metabolism may be a rate-limiting step of intrahepatic fat (IHF) accumulation. AIMS: To assess whole-body energy metabolism and hepatic high-energy phosphates (HEPs) in individuals with fatty liver. METHODS: We studied 22 individuals with fatty liver and 22 control individuals matched for anthropometric features by means of (1) hepatic 1H-magnetic resonance spectroscopy (MRS) to measure the IHF content, (2) hepatic 31P-MRS to assess the relative content of HEPs (phosphomonoesters, phosphodiesters, inorganic phosphorus, and ATP), and (3) indirect calorimetry to assess whole-body resting energy expenditure and substrate oxidation. RESULTS: Patients with newly diagnosed fatty liver and controls were not different for anthropometric parameters. Based on HOMA2%-S, individuals with fatty liver were more insulin resistant than controls. Resting energy expenditure and the pattern of substrate oxidation were not different between groups. Relative content of HEPs was not different between groups; in particular, the Pi/γ-ATP ratio, the most important signals in terms of monitoring energy homeostasis, was not different even if it was associated with indirect calorimetry-derived parameters of oxidative substrate disposal. CONCLUSIONS: These data demonstrate that fasting whole-body energy metabolism and the relative content of HEPs in nondiabetic patients with fatty liver are not different than those in controls when they are matched for anthropometric features.

Clinical signature and pathogenetic factors of diabetes associated with pancreas disease (T3cDM): a prospective observational study in surgical patients.

To characterize the clinical signature and etiopathogenetic factors of diabetes associated with pancreas disease [type 3 diabetes mellitus (T3cDM)]. To estimate incidence and identify predictors of both diabetes onset and remission after pancreatic surgery. A prospective observational study was conducted. From January 2008 to December 2012, patients (n = 651) with new diagnosis of pancreatic disease admitted to the Pancreatic Surgery Unit of the San Raffaele Scientific Institute were evaluated. Hospital and/or outpatient medical records were reviewed. Blood biochemical values including fasting blood glucose, insulin and/or C-peptide, glycosylated hemoglobin and anti-islet antibodies were determined. Diabetes onset was assessed after surgery and during follow-up. At baseline, the prevalence of diabetes was 38 % (age of onset 64 ± 11 years). In most cases, diabetes occurred within 48 months from pancreatic disease diagnosis. Among different pancreatic diseases, minor differences were observed in diabetes characteristics, with the exception of the prevalence. Diabetes appeared associated with classical risk factors for type 2 diabetes (i.e., age, sex, family history of diabetes and body mass index), and both beta-cell dysfunction and insulin resistance appeared relevant determinants. The prevalence of adult-onset autoimmune diabetes was as previously reported within type 2 diabetes. Within a few days after surgery, either diabetes remission or new-onset diabetes was observed. In patients with pancreatic cancer, no difference in diabetes remission was observed after palliative or resective surgery. Classical risk factors for type 2 diabetes were associated with the onset of diabetes after surgery. T3cDM appeared as a heterogeneous entity strongly overlapped with type 2 diabetes.

Inter-day glycemic variability assessed by continuous glucose monitoring in insulin-treated type 2 diabetes patients on hemodialysis.

BACKGROUND: Type 2 diabetes patients on chronic hemodialysis have a high prevalence of cardiovascular complications and often show a poor glycemic control. Single-spot glycemic measurements are not always meaningful, and the hemoglobin A1c (HbA1c) value does not reflect short-term variations in glucose metabolism in this patient category. Therefore, to better understand their metabolic balance, we studied a group of diabetes patients on hemodialysis by a continuous glucose monitoring (CGM) system. METHODS: Twelve insulin-treated type 2 diabetes patients on hemodialysis were studied by a microdialysis-based subcutaneous glucose sensor over a period of 2 days, including the dialysis day (HD) and the following inter-dialytic period ("free" day [FD]). RESULTS: The mean 24-h glycemic value, the mean amplitude of glucose excursions, and the SD of mean glucose were significantly higher in the HD than the FD (186 ± 50 vs. 154 ± 25 mg/dL, P<0.05; 75 ± 22 vs. 56 ± 15 mg/dL, P<0.05; and 57 ± 6 vs. 35 ± 11 mg/dL, P<0.05, respectively). Considering the 48-h recording, there was a direct correlation between the mean glucose concentration and the HbA1c (r=0.47, P<0.05), whereas no association was observed between the measures of glucose variability and HbA1c. CONCLUSIONS: Insulin-treated diabetes patients on hemodialysis showed different glucose profiles between the HD and the FD. In particular, in the HD they have had an increased glycemic variability, which may represent an adjunctive risk factor for cardiovascular complications. Therefore the use of a CGM system, as a means of assessing the measures of glycemic variability, could improve the management of insulin therapy in these patients.