Sex Differences in Clinical Characteristics and Outcomes of Patients with SARS-CoV-2-Infection Admitted to Intensive Care Units in Austria.

IMPORTANCE: A male predominance is reported in hospitalised patients with COVID-19 alongside a higher mortality rate in men compared to women. OBJECTIVE: To assess if the reported sex bias in the COVID-19 pandemic is validated by analysis of a subset of patients with severe disease. DESIGN: A nationwide retrospective cohort study was performed using the Austrian National COVID Database. We performed a sex-specific Lasso regression to select the covariates best explaining the outcomes of mechanical ventilation and death using variables known before ICU admission. We use logistic regression to construct a sex-specific "risk score" for the outcomes using these variables. SETTING: We studied the characteristics and outcomes of patients admitted to intensive care units (ICUs) in Austria. PARTICIPANTS: 5118 patients admitted to the ICU in Austria with a COVID-19 diagnosis in 03/2020-03/2021. EXPOSURES: Demographic and clinical characteristics, vital signs and laboratory tests, comorbidities, and management of patients admitted to ICUs were analysed for possible sex differences. MAIN OUTCOMES AND MEASURES: The aim was to define risk scores for mechanical ventilation and mortality for each sex to provide better sex-sensitive management and outcomes in the future. RESULTS: We found balanced accuracies between 55% and 65% to predict the outcomes. Regarding outcome death, we found that the risk score for pre-ICU variables increases with age, renal insufficiency (f: OR 1.7(2), m: 1.9(2)) and decreases with observance as admission cause (f: OR 0.33(5), m: 0.36(5)). Additionally, the risk score for females also includes respiratory insufficiency (OR 2.4(4)) while heart failure for males only (OR 1.5(1)). CONCLUSIONS AND RELEVANCE: Better knowledge of how sex influences COVID-19 outcomes at ICUs will have important implications for the ongoing pandemic's clinical care and management strategies. Identifying sex-specific features in individuals with COVID-19 and fatal consequences might inform preventive strategies and public health services.

Sex and Gender Impact Mental and Emotional Well-Being During COVID-19 Pandemic: A European Countries Experience.

Objective: The COVID-19 pandemic influences mental health drastically. Therefore, our aim was to investigate whether biological sex and gender-related factors are associated with mental health during the COVID-19 pandemic. Materials and Methods: The International COVID-19 Awareness and Responses Evaluation Study is an international multiwave cross-sectional observational cohort study of public awareness, attitudes, and responses to public health policies (www.mbmc- cmcm.ca/covid19). The study is led by the Montreal Behavioural Medicine Centre in collaboration with 200 international collaborators from 42 countries. It has received research ethics board approval from the Comité d'éthique de recherche du CIUSSS-NIM (Centre intégré universitaire de santé et de services sociaux du Nord- de-l'île-de-Montréal), approval no.: 2020-2099/25-03-2020. Recruitment began on March 27, 2020, and the survey is available in 34 languages. The associations between biological sex, sociocultural gender, and mental health were assessed in multivariate logistic regression models only for the European population (n = 12,300). Results: Positive correlations were found between female sex and "feeling nervous, anxious or worried" (OR = 3.2, p < 0.001, 95% CI 1.87-5.63) and "feeling sad, depressed or hopeless" (OR 1.8, p = 0.031, CI 1.05-3.05). Male sex was related to more frequently "feeling irritable, frustrated, and angry" (OR = 1.8, p = 0.04, 95% CI 1.03-2.99). Concerning gender, a negative correlation between being employed and "feeling lonely or isolated" (OR = 0.26, p < 0.001, 95% CI 0.11-0.59) was observed in the female cohort. Conclusion: Sex and gender differences exist in the emotional responses during the COVID-19 pandemic. Especially, within the female cohort, unemployment is negatively associated with mental health. Therefore, this study suggests more targeted psychological and social support for females during the pandemic.

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.

HbA1c and Glucose Management Indicator Discordance Associated with Obesity and Type 2 Diabetes in Intermittent Scanning Glucose Monitoring System.

Glucose management indicator (GMI) is frequently used as a substitute for HbA1c, especially when using telemedicine. Discordances between GMI and HbA1c were previously mostly reported in populations with type 1 diabetes (T1DM) using real-time CGM. Our aim was to investigate the accordance between GMI and HbA1c in patients with diabetes using intermittent scanning CGM (isCGM). In this retrospective cross-sectional study, patients with diabetes who used isCGM >70% of the time of the investigated time periods were included. GMI of four different time spans (between 14 and 30 days), covering a period of 3 months, reflected by the HbA1c, were investigated. The influence of clinical- and isCGM-derived parameters on the discordance was assessed. We included 278 patients (55% T1DM; 33% type 2 diabetes (T2DM)) with a mean HbA1c of 7.63%. The mean GMI of the four time periods was between 7.19% and 7.25%. On average, the absolute deviation between the four calculated GMIs and HbA1c ranged from 0.6% to 0.65%. The discordance was greater with increased BMI, a diagnosis of T2DM, and a greater difference between the most recent GMI and GMI assessed 8 to 10 weeks prior to HbA1c assessment. Our data shows that, especially in patients with increased BMI and T2DM, this difference is more pronounced and should therefore be considered when making therapeutic decisions.

Sex Differences in Clinical Characteristics and Outcomes of Patients with SARS-CoV-2-Infection Admitted to Intensive Care Units in Austria

Importance: A male predominance is reported in hospitalised patients with COVID-19 alongside a higher mortality rate in men compared to women. Objective: To assess if the reported sex bias in the COVID-19 pandemic is validated by analysis of a subset of patients with severe disease. Design: A nationwide retrospective cohort study was performed using the Austrian National COVID Database. We performed a sex-specific Lasso regression to select the covariates best explaining the outcomes of mechanical ventilation and death using variables known before ICU admission. We use logistic regression to construct a sex-specific 'risk score';for the outcomes using these variables. Setting: We studied the characteristics and outcomes of patients admitted to intensive care units (ICUs) in Austria. Participants: 5118 patients admitted to the ICU in Austria with a COVID-19 diagnosis in 03/2020–03/2021. Exposures: Demographic and clinical characteristics, vital signs and laboratory tests, comorbidities, and management of patients admitted to ICUs were analysed for possible sex differences. Main outcomes and measures: The aim was to define risk scores for mechanical ventilation and mortality for each sex to provide better sex-sensitive management and outcomes in the future. Results: We found balanced accuracies between 55% and 65% to predict the outcomes. Regarding outcome death, we found that the risk score for pre-ICU variables increases with age, renal insufficiency (f: OR 1.7(2), m: 1.9(2)) and decreases with observance as admission cause (f: OR 0.33(5), m: 0.36(5)). Additionally, the risk score for females also includes respiratory insufficiency (OR 2.4(4)) while heart failure for males only (OR 1.5(1)). Conclusions and relevance: Better knowledge of how sex influences COVID-19 outcomes at ICUs will have important implications for the ongoing pandemic's clinical care and management strategies. Identifying sex-specific features in individuals with COVID-19 and fatal consequences might inform preventive strategies and public health services.

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.

Insulin as Monotherapy and in Combination with Other Glucose-Lowering Drugs Is Related to Increased Risk of Diagnosis of Pneumonia: A Longitudinal Assessment over Two Years.

OBJECTIVE: Patients with type 2 diabetes mellitus (T2DM) are at an increased risk of developing infectious diseases such as pneumonia. Hitherto, there has been uncertainty as to whether there is a relationship between different antidiabetic drug combinations and development of pneumonia in this specific cohort. RESEARCH DESIGN AND METHODS: In this longitudinal retrospective study we used multiple logistic regression analysis to assess the odds ratios (ORs) of pneumonia during an observational period of 2 years in 31,397 patients with T2DM under previously prescribed stable antidiabetic drug combinations over a duration of 4 years in comparison to 6568 T2DM patients without drug therapy over 4 years adjusted for age, sex and hospitalization duration. RESULTS: Of the 37,965 patients with T2DM, 3720 patients underwent stable monotherapy treatment with insulin (mean age: 66.57 ± 9.72 years), 2939 individuals (mean age: 70.62 ± 8.95 y) received stable statin and insulin therapy, and 1596 patients were treated with a stable combination therapy of metformin, insulin and statins (mean age: 68.27 ± 8.86 y). In comparison to the control group without antidiabetic drugs (mean age: 72.83 ± 9.96 y), individuals undergoing insulin monotherapy (OR: 2.07, CI: 1.54-2.79, p < 0.001); insulin and statin combination therapy (OR: 2.24, CI: 1.68-3.00, p < 0.001); metformin, insulin and statin combination therapy (OR: 2.27, CI: 1.55-3.31, p < 0.001); statin, insulin and dipeptidyl peptidase-4 inhibitor (DPP-IV inhibitor) combination therapy (OR: 4.31, CI: 1.80-10.33, p = 0.001); as well as individuals treated with metformin and sulfonylureas (OR: 1.70, CI: 1.08-2.69, p = 0.02) were at increased risk of receiving a diagnosis of pneumonia. CONCLUSIONS: Stable monotherapy with insulin, but also in combination with other antidiabetic drugs, is related to an increased risk of being diagnosed with pneumonia during hospital stays in patients with type 2 diabetes mellitus compared to untreated controls.

Does diabetes mellitus mitigate the gender gap in COVID-19 mortality?

In this SARS-COV2-pandemic, diabetes mellitus (DM) soon emerged as one of the most prominent risk factors for a severe course of corona virus disease-2019 (COVID-19) and increased mortality due to hyperglycemia/insulin resistance, obesity, inflammation, altered immune status, and cardiovascular complications. In general, men are at a higher risk of severe or fatal COVID-19 disease irrespective of age, region and despite comparable infection rates in both sexes. In COVID-19, there is also a male predominance among hospitalized patients with diabetes, however, overall, data among patients with diabetes are ambiguous so far. Of note, similar to cardiovascular complications, women with type 2 diabetes (DM2) appear to lose their biological female advantage resulting in comparable death rates to those of men. The complex interplay of biological and behavioral factors, which may put men at greater risk of a severe or fatal course of COVID-19, and gender-related psychosocial factors, which may cause disadvantage to women concerning the infection rates, might explain why sex-disaggregated data among infected patients with diabetes are conflicting. Better knowledge on biological factors leading to functionally different immune responses and of gender-sensitive sociocultural determinants of COVID-19 infection rates may help to optimize prevention and management in the high-risk groups of men and women with diabetes.

Comparison of Bioelectrical Impedance-Based Methods on Body Composition in Young Patients with Obesity.

(1) Background: The determination of body composition is an important method to investigate patients with obesity and to evaluate the efficacy of individualized medical interventions. Bioelectrical impedance-based methods are non-invasive and widely applied but need to be validated for their use in young patients with obesity. (2) Methods: We compiled data from three independent studies on children and adolescents with obesity, measuring body composition with two bioelectrical impedance-based devices (TANITA and BIACORPUS). For a small patient group, additional data were collected with air displacement plethysmography (BOD POD) and dual-energy X-ray absorptiometry (DXA). (3) Results: Our combined data on 123 patients (age: 6-18 years, body mass index (BMI): 21-59 kg/m²) and the individual studies showed that TANITA and BIACORPUS yield significantly different results on body composition, TANITA overestimating body fat percentage and fat mass relative to BIACORPUS and underestimating fat-free mass (p < 0.001 for all three parameters). A Bland-Altman plot indicated little agreement between methods, which produce clinically relevant differences for all three parameters. We detected gender-specific differences with both methods, with body fat percentage being lower (p < 0.01) and fat-free mass higher (p < 0.001) in males than females. (4) Conclusions: Both bioelectrical impedance-based methods provide significantly different results on body composition in young patients with obesity and thus cannot be used interchangeably, requiring adherence to a specific device for repetitive measurements to ascertain comparability of data.

Sex-Related Differences in Drugs with Anti-Inflammatory Properties.

There is increasing evidence of sex differences in the action of anti-inflammatory drugs, with women being at significantly higher risk of adverse effects. Nevertheless, clinicians' awareness of the implications of these sex differences on dosing and adverse event monitoring in routine practice is still in need of improvement. We reviewed the literature evaluating sex differences in terms of pharmacokinetics and pharmacodynamics of anti-inflammatory drugs. The anti-thrombotic activity of selective and non-selective COX-inhibitors tends to be stronger in men than women. Side effect profiles differ with regards to gastro-intestinal, renal and hepatic complications. Glucocorticosteroids were found to be more effective in men; women were more sensitive to corticosteroids when their oestradiol levels were high, a finding important for women taking hormonal contraception. TNF-alpha inhibitors have a longer half-life in men, leading to stronger immunosuppression and this a higher incidence of infections as side effects. Although research on sex differences in the effectiveness and safety of drugs is increasing, findings are often anecdotal and controversial. There is no systematic sex-differentiated reporting from clinical trials, and women are often under-represented. As personalized medicine is gaining in importance, sex, and gender aspects need to become integral parts of future research and policy making.

COVID-19 fatality prediction in people with diabetes and prediabetes using a simple score upon hospital admission.

AIM: To assess predictors of in-hospital mortality in people with prediabetes and diabetes hospitalized for COVID-19 infection and to develop a risk score for identifying those at the greatest risk of a fatal outcome. MATERIALS AND METHODS: A combined prospective and retrospective, multicentre, cohort study was conducted at 10 sites in Austria in 247 people with diabetes or newly diagnosed prediabetes who were hospitalized with COVID-19. The primary outcome was in-hospital mortality and the predictor variables upon admission included clinical data, co-morbidities of diabetes or laboratory data. Logistic regression analyses were performed to identify significant predictors and to develop a risk score for in-hospital mortality. RESULTS: The mean age of people hospitalized (n = 238) for COVID-19 was 71.1 ± 12.9 years, 63.6% were males, 75.6% had type 2 diabetes, 4.6% had type 1 diabetes and 19.8% had prediabetes. The mean duration of hospital stay was 18 ± 16 days, 23.9% required ventilation therapy and 24.4% died in the hospital. The mortality rate in people with diabetes was numerically higher (26.7%) compared with those with prediabetes (14.9%) but without statistical significance (P = .128). A score including age, arterial occlusive disease, C-reactive protein, estimated glomerular filtration rate and aspartate aminotransferase levels at admission predicted in-hospital mortality with a C-statistic of 0.889 (95% CI: 0.837-0.941) and calibration of 1.000 (P = .909). CONCLUSIONS: The in-hospital mortality for COVID-19 was high in people with diabetes but not significantly different to the risk in people with prediabetes. A risk score using five routinely available patient variables showed excellent predictive performance for assessing in-hospital mortality.