Advanced Hybrid Closed-Loop System Achieves and Maintains Recommended Time in Range Levels for Up To 2 Years: Predictors of Best Efficacy.

Aim: To evaluate the long-term efficacy, up to 2 years, of an advanced hybrid closed-loop (AHCL) system and to assess predictors of best results of the therapy. Methods: We retrospectively evaluated 296 adults with type 1 diabetes mellitus [mean age 42.8 ± 16.5 years, men 42.9%, duration of diabetes 22.5 ± 12.8 years, body mass index 24.9 ± 4.7 kg/m2, baseline glycated hemoglobin (HbA1c) 63.4 ± 12.2 mmol/mol (8.0 ± 1.1%) ] who used the MiniMed™ 780G system. Demographic and clinical data were recorded. Continuous glucose monitoring (CGM)-derived metrics and insulin requirement were analyzed from the 4 weeks before and from every quarter after the switch to the AHCL system. Results: In the first quarter of AHCL treatment, all CGM metrics improved. Time in range (TIR) increased from 58.1 ± 17.5% to 70.3 ± 9.5% (P < 0.0001). The improvement lasted for up to 2 years of observation regardless of previous insulin therapies. Throughout the period of observation, 53.4% of participants achieved mean TIR >70%, 92.6% mean time below range <4%, and 46% mean glucose management indicator <53 mmol/mol (7.0%). At univariable logistic regression older age, lower baseline HbA1c and insulin requirement were associated with mean TIR >70%. At multivariable analysis, lower HbA1c remained independently associated with a better glycemic control. However, mean TIR increased more in participants with a higher baseline HbA1c. Conclusions: Switching to an AHCL leads to a rapid improvement in glycemic control lasting for up to 24 months along with a low risk for hypoglycemia, confirming the safety of the system. Lower baseline HbA1c was the main predictor of better efficacy of therapy, although higher baseline HbA1c was associated with the greatest improvement in mean TIR.

Predictive markers for clinical outcomes in a cohort of diabetic patients hospitalized for COVID-19.

INTRODUCTION: The role of glycemic control, both prior and during hospitalization, on mortality from COVID-19 in diabetic patients is debated. Furthermore, it is not clear whether hyperglycemia has a direct effect or requires inflammatory mechanisms. OBJECTIVE: To identify predictors of clinical outcomes (in-hospital mortality, length of hospitalization, respiratory failure, need for intensive care), considering hyperglycemia, inflammation markers and clinical history. METHODS: Retrospective observational study of 291 diabetic patients hospitalized with COVID-19 in the Spedali Civili di Brescia from February 1th 2020 to March 31th 2021, with also outpatient electronic records. Glucose, inflammatory parameters, creatinine were collected within 24 h after admission to the hospital. A causal mediation analysis allowed the estimation of the direct and indirect effects of hyperglycemia on mortality. RESULTS: Glucose at admission ≥ 165 mg/dL and reduced renal function were associated with an increased risk of in-hospital mortality and length of hospitalization (all p < 0.001), while an increase in inflammatory parameters was significantly associated with an increased risk of all outcomes. High basophil count was associated with reduced mortality (p < 0.001). Hyperglycemia had a direct effect on mortality (p < 0.001); the indirect, through inflammatory markers, was significant only for absolute neutrophil count, C-Reactive protein and procalcitonin (p = 0.007, p = 0.029, p = 0.042). Patients with microvascular complications and with chronic kidney disease showed higher mortality (p = 0.03, p = 0.01). CONCLUSIONS: Hyperglycemia at admission, renal function and inflammatory parameters were found to be predictors of in-hospital mortality, while an increased basophil count was protective. Hyperglycemia had a direct effect on mortality, the indirect effect was only through few markers and markedly lower than the direct one.

Revaluation of clinical and histological criteria for diagnosis of dysmetabolic iron overload syndrome.

AIM: To re-evaluate the diagnostic criteria of insulin resistance hepatic iron overload based on clinical, biochemical and histopathological findings. METHODS: We studied 81 patients with hepatic iron overload not explained by known genetic and acquired causes. The metabolic syndrome (MS) was defined according to ATPIII criteria. Iron overload was assessed by liver biopsy. Liver histology was evaluated by Ishak's score and iron accumulation by Deugnier's score; steatosis was diagnosed when present in >or=5% of hepatocytes. RESULTS: According to transferrin saturation levels, we observed significant differences in the amount of hepatic iron overload and iron distribution, as well as the number of metabolic abnormalities. Using Receiving Operating Curve analysis, we found that the presence of two components of the MS differentiated two groups with a statistically significant different hepatic iron overload (P<0.0001). Patients with >or=2 metabolic alterations and steatosis had lower amount of hepatic iron, lower transferrin saturation and higher sinusoidal iron than patients with <2 MS components and absence of steatosis. CONCLUSION: In our patients, the presence of >or2 alterations of the MS and hepatic steatosis was associated with a moderate form of iron overload with a prevalent sinusoidal distribution and a normal transferrin saturation, suggesting the existence of a peculiar pathogenetic mechanism of iron accumulation. These patients may have the typical dysmetabolic iron overload syndrome. By contrast, patients with transferrin saturation>or=60% had more severe iron overload, few or no metabolic abnormalities and a hemochromatosis-like pattern of iron overload.