Nutrients / The Effect of Electrolytes on Blood Pressure: A Brief Summary of Meta-Analyses

Nutrition is known to exert an undeniable impact on blood pressure with especially salt (sodium chloride), but also potassium, playing a prominent role. The aim of this review was to summarize meta-analyses studying the effect of different electrolytes on blood pressure or risk for hypertension, respectively. Overall, 32 meta-analyses evaluating the effect of sodium, potassium, calcium and magnesium on human blood pressure or hypertension risk were included after literature search. Most of the meta-analyses showed beneficial blood pressure lowering effects with the extent of systolic blood pressure reduction ranging between 0.7 (95% confidence interval: 2.6 to 1.2) to 8.9 (14.1 to 3.7) mmHg for sodium/salt reduction, 3.5 (5.2 to 1.8) to 9.5 (10.8 to 8.1) mmHg for potassium, and 0.2 (0.4 to 0.03) to 18.7 (22.5 to 15.0) mmHg for magnesium. The range for diastolic blood pressure reduction was 0.03 (0.4 to 0.4) to 5.9 (9.7 to 2.1) mmHg for sodium/salt reduction, 2 (3.1 to 0.9) to 6.4 (7.3 to 5.6) mmHg for potassium, and 0.3 (0.5 to 0.03) to 10.9 (13.1 to 8.7) mmHg for magnesium. Moreover, sufficient calcium intake was found to reduce the risk of gestational hypertension.(VLID)491878

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

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