European Safety Analysis of mRNA and Viral Vector COVID-19 Vaccines on Glucose Metabolism Events.

Few data have been published on the effects of impaired glucose metabolism induced by COVID-19 vaccines. We decided to perform a study to describe Individual Case Safety Reports (ICSRs) of impaired glucose metabolism events reported in the European database (Eudravigilance, EV). ICSRs were retrieved from the online website of Eudravigilance. The reporting odds ratios (ROR) were computed to assess the reporting frequency for COVID-19 mRNA vaccines compared to COVID-19 viral vector-based vaccines. A total of 3917 ICSRs with a COVID-19 vaccine suspected were retrieved, with a total of 4275 impaired glucose metabolism events. Overall, the most reported events were related to "high glucose levels" (2012; 47.06%). The mRNA vaccines were associated with an increased reporting frequency of "type 1 diabetes mellitus" (ROR 1.86; 95% CI 1.33-2.60), "type 2 diabetes mellitus" (ROR 1.58; 95% CI 1.03-2.42), "high glucose levels" (ROR 1.16; 95% CI 1.06-1.27), "diabetes mellitus inadequate control" (ROR 1.63; 95% CI 1.25-2.11), and "hypoglycemia" (ROR 1.62; 95% CI 1.41-1.86) compared to viral vector-based vaccines. mRNA COVID-19 vaccines were associated with an increased reporting frequency of alterations of glucose homeostasis compared to viral-vector COVID-19 vaccines. Clinicians should be aware of these events to better manage glycemic perturbations. Larger nationwide studies are warranted to verify these findings.

Antibiotic resistance in diabetic foot infection: how it changed with COVID-19 pandemic in a tertiary care center.

AIM: To investigate the rate of antibiotic resistance and its main risk factors in a population of patients with diabetic foot infection (DFI) during the COVID-19 pandemic, in comparison with the population of 2019. METHODS: Two hundred and twenty-five patients with DFI were admitted in a tertiary care center from January 2019 to December 2020. Antibiotic resistance was evaluated by microbiological examination of soft tissues' or bone's biopsy. RESULTS: Compared with 2019 group (n = 105), 2020 group (n = 120) had a significantly higher prevalence of antibiotic resistance [2019 vs 2020, 36% vs 63%, P <0.001] and more often was admitted with recent or current antibiotic therapy (18% vs 52%, P <0.001), which was frequently self-administered (5% vs 30%, P = 0.032). The risk of antibiotic resistance was also higher in 2020 group [OR 95% CI, 2.90 (1.68 to 4.99)]. Prior hospitalization, antibiotic self-administration and antibiotic prescription by general practitioners resulted as independent predictors of antibiotic resistance. CONCLUSIONS: In a population of people with DFI admitted in a tertiary care center during the COVID-19 pandemic the prevalence of antibiotic resistance was higher than 2019. Previous hospitalization, antibiotic self-administration /prescription by general practitioners were related to higher risk of antibiotic resistant infections.

Teleassistance for Patients With Type 1 Diabetes During the COVID-19 Pandemic: Results of a Pilot Study.

BACKGROUND: Telemedicine use in chronic disease management has markedly increased during health emergencies due to COVID-19. Diabetes and technologies supporting diabetes care, including glucose monitoring devices, software analyzing glucose data, and insulin delivering systems, would facilitate remote and structured disease management. Indeed, most of the currently available technologies to store and transfer web-based data to be shared with health care providers. OBJECTIVE: During the COVID-19 pandemic, we provided our patients the opportunity to manage their diabetes remotely by implementing technology. Therefore, this study aimed to evaluate the effectiveness of 2 virtual visits on glycemic control parameters among patients with type 1 diabetes (T1D) during the lockdown period. METHODS: This prospective observational study included T1D patients who completed 2 virtual visits during the lockdown period. The glucose outcomes that reflected the benefits of the virtual consultation were time in range (TIR), time above range, time below range, mean daily glucose, glucose management indicator (GMI), and glycemic variability. This metric was generated using specific computer programs that automatically upload data from the devices used to monitor blood or interstitial glucose levels. If needed, we changed the ongoing treatment at the first virtual visit. RESULTS: Among 209 eligible patients with T1D, 166 completed 2 virtual visits, 35 failed to download glucose data, and 8 declined the visit. Among the patients not included in the study, we observed a significantly lower proportion of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) users (n=7/43, 16% vs n=155/166, 93.4% and n=9/43, 21% vs n=128/166, 77.1%, respectively; P<.001) compared to patients who completed the study. TIR significantly increased from the first (62%, SD 18%) to the second (65%, SD 16%) virtual visit (P=.02); this increase was more marked among patients using the traditional meter (n=11; baseline TIR=55%, SD 17% and follow-up TIR=66%, SD 13%; P=.01) than among those using CGM, and in those with a baseline GMI of ≥7.5% (n=46; baseline TIR=45%, SD 15% and follow-up TIR=53%, SD 18%; P<.001) than in those with a GMI of <7.5% (n=120; baseline TIR=68%, SD 15% and follow-up TIR=69%, SD 15%; P=.98). The only variable independently associated with TIR was the change of ongoing therapy. The unstandardized beta coefficient (B) and 95% CI were 5 (95% CI 0.7-8.0) (P=.02). The type of glucose monitoring device and insulin delivery systems did not influence glucometric parameters. CONCLUSIONS: These findings indicate that the structured virtual visits help maintain and improve glycemic control in situations where in-person visits are not feasible.

Glycemic control in people with type 1 diabetes using a hybrid closed loop system and followed by telemedicine during the COVID-19 pandemic in Italy.

AIMS: This study aims at evaluating the metrics of glycemic control in people with type 1 diabetes using the hybrid closed loop (HCL) system during the COVID-19 lockdown. METHODS: This is a retrospective study of thirty adults with type 1 diabetes using HCL and followed with telemedicine at an Italian University Hospital. Data on metrics of glucose control were collected at different times: two weeks before the lockdown (Time 0), first two weeks of lockdown (Time 1), last two weeks of lockdown (Time 2) and first two weeks after the lockdown (Time 3). The primary endpoint was the change in glucose management indicator (GMI) across the different time points. RESULTS: GMI did not worsen over time (Time 1 vs Time 3, 7% vs 6.9%, P < 0.05), whereas a reduction of mean glucose (P = 0.004) and indices of glucose variability was observed. Time in range (TIR) significantly increased (68.5% vs 73.5%, P = 0.012), and time above range (TAR) level 2 (251-400 mg/dL) significantly decreased (P = 0.002). The improvement of TIR and glucose variability was mainly observed in participants < 35 years. CONCLUSIONS: Adults with type 1 diabetes using HCL showed a significant improvement of most of the metrics of glucose control during the COVID-19 lockdown.

Treating type 2 diabetes in COVID-19 patients: the potential benefits of injective therapies.

The coronavirus disease 2019 (COVID-19) has been declared as pandemic by the World Health Organization and is causing substantial morbidity and mortality all over the world. Type 2 diabetes, hypertension, and cardiovascular disease significantly increase the risk for hospitalization and death in COVID-19 patients. Hypoglycemia and hyperglycemia are both predictors for adverse outcomes in hospitalized patients. An optimized glycemic control should be pursued in patients with diabetes and SARS-CoV-2 infection in order to reduce the risk of severe COVID-19 course. Both insulin and GLP-1RAs have shown optimal glucose-lowering and anti-inflammatory effects in type 2 diabetic patients and may represent a valid therapeutic option to treat asymptomatic and non-critically ill COVID-19 diabetic patients.