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.

Hüftfrakturinzidenz und Lockdown: Gibt es Zusammenhänge? Hip fracture incidence and lockdown: is there a connection?

Zur Eindämmung der COVID-19-Pandemie wurde in Österreich bereits mehrfach ein Lockdown verhängt. Durch die häusliche Isolation und dadurch reduzierte physische Aktivität könnte die Frakturhäufigkeit initial positiv beeinflusst werden, aber mittel- bis langfristig aufgrund eines reduzierten Trainingsstatus und verringerter Koordinationsfähigkeit, welche zu einem erhöhten Sturz- und damit Frakturrisiko führen, steigen. Basierend auf Daten der österreichischen Allgemeinen Unfallversicherungsanstalt (AUVA) zeigte sich die Häufigkeit von Hüftfrakturen im Zeitraum des ersten Lockdowns (16. März bis 31. Mai 2020) unverändert im Vergleich zu den gleichen Zeiträumen der Jahre zuvor, jedoch ergab eine Subanalyse eine reduzierte Frakturrate bei Frauen in der Altersgruppe 50-69 Jahre während des ersten Lockdowns verglichen mit dem gleichen Zeitraum des Jahres 2018.

Hüftfrakturinzidenz und Lockdown: Gibt es Zusammenhänge?

Zur Eindämmung der COVID-19-Pandemie wurde in Österreich bereits mehrfach ein Lockdown verhängt. Durch die häusliche Isolation und dadurch reduzierte physische Aktivität könnte die Frakturhäufigkeit initial positiv beeinflusst werden, aber mittel- bis langfristig aufgrund eines reduzierten Trainingsstatus und verringerter Koordinationsfähigkeit, welche zu einem erhöhten Sturz- und damit Frakturrisiko führen, steigen. Basierend auf Daten der österreichischen Allgemeinen Unfallversicherungsanstalt (AUVA) zeigte sich die Häufigkeit von Hüftfrakturen im Zeitraum des ersten Lockdowns (16. März bis 31. Mai 2020) unverändert im Vergleich zu den gleichen Zeiträumen der Jahre zuvor, jedoch ergab eine Subanalyse eine reduzierte Frakturrate bei Frauen in der Altersgruppe 50-69 Jahre während des ersten Lockdowns verglichen mit dem gleichen Zeitraum des Jahres 2018.

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.

The Impact of Lockdown during COVID-19 Pandemic on Hip Fracture Cases in Austria (preprint)

Mini AbstractSocial lockdowns may have an impact on fracture cases. During the first lockdown in Austria (March 16th to May 31st 2020), hip fracture cases did not significantly change, except a decreased rate in female patients aged 50-69 years.IntroductionSocial lockdown has been repeatedly imposed worldwide due to the coronavirus disease 2019 (COVID-19). Resultant isolation with less physical activity and restricted health care access may have an impact on fracture incidences. The aim of this analysis was to assess the effect of a social lockdown on hip fracture cases in Austria.MethodsThis analysis is based on the data of the Austrian Workers' Compensation Board (AUVA), which is the social insurance for the majority in Austria. Hip fracture cases in the time period March 16th to May 31st, 2020 (first lockdown period in Austria) were compared with those in the same period of previous years (2016-2019). Further analysis included stratification by gender, age and weekly intervals using repeated measures analysis of variance (ANOVA), while a p-value of less than 0.05 was considered statistically significant.ResultsIn the time period March 16th to May 31st 2020 the fracture cases of 445 lied within the standard deviation (SD) of years before (438 ± 20.1). The mean cases of weekly separated intervals in 2016-2019 did not differ significantly from those in 2020. In patients aged 50 to 69 years, the fracture cases in 2020 was below the SD of those in years before (64 vs. 77 ± 10). Stratified by weekly intervals and age group, mean fracture cases of years before were comparable with those of 2020, except 2018, which had significant lower rates in patients aged 50-69 years (p<0.05). Separated by gender, this difference was only seen in women.ConclusionHip fracture cases did not significantly change during first social lockdown (March 16th to May 31st 2020) in Austria, except a decreased fracture rate in female patients aged 50-69 years.

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.