Biomarkers Predictive for In-Hospital Mortality in Patients with Diabetes Mellitus and Prediabetes Hospitalized for COVID-19 in Austria: An Analysis of COVID-19 in Diabetes Registry.

BACKGROUND: This study assessed the predictive performance of inflammatory, hepatic, coagulation, and cardiac biomarkers in patients with prediabetes and diabetes mellitus hospitalized for COVID-19 in Austria. METHODS: This was an analysis of a multicenter cohort study of 747 patients with diabetes mellitus or prediabetes hospitalized for COVID-19 in 11 hospitals in Austria. The primary outcome of this study was in-hospital mortality. The predictor variables included demographic characteristics, clinical parameters, comorbidities, use of medication, disease severity, and laboratory measurements of biomarkers. The association between biomarkers and in-hospital mortality was assessed using simple and multiple logistic regression analyses. The predictive performance of biomarkers was assessed using discrimination and calibration. RESULTS: In our analysis, 70.8% had type 2 diabetes mellitus, 5.8% had type 1 diabetes mellitus, 14.9% had prediabetes, and 8.6% had other types of diabetes mellitus. The mean age was 70.3 ± 13.3 years, and 69.3% of patients were men. A total of 19.0% of patients died in the hospital. In multiple logistic regression analysis, LDH, CRP, IL-6, PCT, AST-ALT ratio, NT-proBNP, and Troponin T were significantly associated with in-hospital mortality. The discrimination of NT-proBNP was 74%, and that of Troponin T was 81%. The calibration of NT-proBNP was adequate (p = 0.302), while it was inadequate for Troponin T (p = 0.010). CONCLUSION: Troponin T showed excellent predictive performance, while NT-proBNP showed good predictive performance for assessing in-hospital mortality in patients with diabetes mellitus hospitalized with COVID-19. Therefore, these cardiac biomarkers may be used for prognostication of COVID-19 patients.

The Arrhythmogenic Face of COVID-19: Brugada ECG Pattern in SARS-CoV-2 Infection.

In 1992, Brugada syndrome (BS) was first described; an often unrecognized cardiac conduction disorder mainly associated with unexplained sudden cardiac arrest and consecutive syncope. Nevertheless, the pathomechanism of BS and sudden cardiac death remains mainly explained. Mutations in the cardiac sodium channels, which cause a reduction or functional loss of these channels, are associated with characteristic electrocardiographic (ECG) abnormalities and malignant arrhythmia. The majority of affected people are previously healthy and unaware of their genetic predisposition for BS and might experience ventricular tachyarrhythmias and cardiac arrest potentially triggered by several factors (e.g., alcohol, sodium channel blockers, psychotropic drugs, and fever). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was firstly identified in Wuhan in early December 2019 and rapidly spread worldwide as coronavirus disease (COVID-19). COVID-19 is typically characterized by a severe inflammatory response, activation of the immune system, and high febrile illness. Due to this condition, symptomatic COVID-19 infection or vaccination might serve as inciting factor for unmasking the Brugada pattern and represents a risk factor for developing proarrhythmic complications. The aim of this narrative review was to detail the association between virus-related issues such as fever, electrolyte disturbance, and inflammatory stress of COVID-19 infection with transient Brugada-like symptoms and ECG-pattern and its susceptibility to proarrhythmogenic episodes.

Simplified Acute Physiology Score 3 Performance in Austrian COVID-19 Patients Admitted to Intensive Care Units with and without Diabetes.

This study evaluated and compared the performance of simplified acute physiology score 3 (SAPS 3) for predicting in-hospital mortality in COVID-19 patients admitted to intensive care units (ICUs) with and without diabetes in Austria. The Austrian national public health institute (GÖG) data of COVID-19 patients admitted to ICUs (n = 5850) were analyzed. Three versions of SAPS 3 were used: standard equation, Central European equation, and Austrian equation customized for COVID-19 patients. The observed in-hospital mortality was 38.9%, 42.9%, and 37.3% in all, diabetes, and non-diabetes patients, respectively. The overall C-statistics was 0.69 with an insignificant (p = 0.193) difference between diabetes (0.70) and non-diabetes (0.68) patients. The Brier score was > 0.20 for all SAPS 3 equations in all cohorts. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients only. The SAPS 3 score demonstrated low discrimination and accuracy in Austrian COVID-19 patients, with an insignificant difference between diabetes and non-diabetes. All equations were miscalibrated particularly in non-diabetes patients, while the Austrian equation showed satisfactory calibration in diabetes patients only. Both uncalibrated and calibrated versions of SAPS 3 should be used with caution in COVID-19 patients.

The Arrhythmogenic Face of COVID-19: Brugada ECG Pattern in SARS-CoV-2 Infection

In 1992, Brugada syndrome (BS) was first described;an often unrecognized cardiac conduction disorder mainly associated with unexplained sudden cardiac arrest and consecutive syncope. Nevertheless, the pathomechanism of BS and sudden cardiac death remains mainly explained. Mutations in the cardiac sodium channels, which cause a reduction or functional loss of these channels, are associated with characteristic electrocardiographic (ECG) abnormalities and malignant arrhythmia. The majority of affected people are previously healthy and unaware of their genetic predisposition for BS and might experience ventricular tachyarrhythmias and cardiac arrest potentially triggered by several factors (e.g., alcohol, sodium channel blockers, psychotropic drugs, and fever). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was firstly identified in Wuhan in early December 2019 and rapidly spread worldwide as coronavirus disease (COVID-19). COVID-19 is typically characterized by a severe inflammatory response, activation of the immune system, and high febrile illness. Due to this condition, symptomatic COVID-19 infection or vaccination might serve as inciting factor for unmasking the Brugada pattern and represents a risk factor for developing proarrhythmic complications. The aim of this narrative review was to detail the association between virus-related issues such as fever, electrolyte disturbance, and inflammatory stress of COVID-19 infection with transient Brugada-like symptoms and ECG-pattern and its susceptibility to proarrhythmogenic episodes.

Humoral immune response to COVID-19 vaccination in diabetes is age-dependent but independent of type of diabetes and glycaemic control: The prospective COVAC-DM cohort study.

AIMS: To investigate the seroconversion following first and second COVID-19 vaccination in people with type 1 and type 2 diabetes in relation to glycaemic control prior to vaccination and to analyse the response in comparison to individuals without diabetes. MATERIALS AND METHODS: This prospective, multicentre cohort study analysed people with type 1 and type 2 diabetes and a glycated haemoglobin level ≤58 mmol/mol (7.5%) or >58 mmol/mol (7.5%), respectively, and healthy controls. Roche's Elecsys anti-SARS-CoV-2 S immunoassay targeting the receptor-binding domain was used to quantify anti-spike protein antibodies 7 to 14 days after the first and 14 to 21 days after the second vaccination. RESULTS: A total of 86 healthy controls were enrolled in the study, as well as 161 participants with diabetes, of whom 150 (75 with type 1 diabetes and 75 with type 2 diabetes) were eligible for the analysis. After the first vaccination, only 52.7% of participants in the type 1 diabetes group and 48.0% of those in the type 2 diabetes group showed antibody levels above the cut-off for positivity. Antibody levels after the second vaccination were similar in participants with type 1 diabetes, participants with type 2 diabetes and healthy controls after adjusting for age, sex and multiple testing (P > 0.05). Age (r = -0.45, P < 0.001) and glomerular filtration rate (r = 0.28, P = 0.001) were significantly associated with antibody response. CONCLUSIONS: Anti-SARS-CoV-2 S receptor-binding domain antibody levels after the second vaccination were comparable in healthy controls and in participants with type 1 and type 2 diabetes, irrespective of glycaemic control. Age and renal function correlated significantly with the extent of antibody levels.

COVID-19 In-Hospital Mortality in People with Diabetes Is Driven by Comorbidities and Age-Propensity Score-Matched Analysis of Austrian National Public Health Institute Data.

BACKGROUND: It is a matter of debate whether diabetes alone or its associated comorbidities are responsible for severe COVID-19 outcomes. This study assessed the impact of diabetes on intensive care unit (ICU) admission and in-hospital mortality in hospitalized COVID-19 patients. METHODS: A retrospective analysis was performed on a countrywide cohort of 40,632 COVID-19 patients hospitalized between March 2020 and March 2021. Data were provided by the Austrian data platform. The association of diabetes with outcomes was assessed using unmatched and propensity-score matched (PSM) logistic regression. RESULTS: 12.2% of patients had diabetes, 14.5% were admitted to the ICU, and 16.2% died in the hospital. Unmatched logistic regression analysis showed a significant association of diabetes (odds ratio [OR]: 1.24, 95% confidence interval [CI]: 1.15-1.34, p < 0.001) with in-hospital mortality, whereas PSM analysis showed no significant association of diabetes with in-hospital mortality (OR: 1.08, 95%CI: 0.97-1.19, p = 0.146). Diabetes was associated with higher odds of ICU admissions in both unmatched (OR: 1.36, 95%CI: 1.25-1.47, p < 0.001) and PSM analysis (OR: 1.15, 95%CI: 1.04-1.28, p = 0.009). CONCLUSIONS: People with diabetes were more likely to be admitted to ICU compared to those without diabetes. However, advanced age and comorbidities rather than diabetes itself were associated with increased in-hospital mortality in COVID-19 patients.

Application of Telemedicine in Diabetes Care: The Time is Now.

The utilization of telemedicine solutions to reduce outpatient clinic visits and visits to physicians' offices, thus saving financial and personal resources as well as time, has gained substantial importance in recent years. The COVID19 pandemic has made it necessary to abruptly adjust outpatient care methods in various medical settings that needlessly require consultations in person to monitor and change the disease management of patients in specific risk groups. People with diabetes represent a vulnerable population who need to be protected from avoidable outpatient clinic visits, particularly in times of influenza or other pandemic outbreaks. However, the treatment and care of patients with diabetes and its comorbidities require careful and regular monitoring and therapy adjustments by medical staff. Advanced age or cognitive impairment and insufficient access to the health care system due to low socioeconomic status can complicate the use of possible alternatives to in-person consultations in outpatient clinics or physicians' offices. Telemedicine solutions may offer suitable alternatives to standard face-to-face consultations in outpatient settings and provide sufficient access to appropriate diabetes care. Nevertheless, telemedicine methods for monitoring diabetes issues are yet to find widespread use due to numerous barriers, such as a lack of acceptance and doubt about its time- and cost-effectiveness, availability, and potential technical and regulatory issues. This article offers an overview of existing applications that provide telemedicine diabetes care. Furthermore, it discusses potential ways to restructure and revolutionize diabetes outpatient care.