The coronavirus disease 2019 (COVID-19) shows high incidence of thromboembolic events in humans. In the present study, we aimed to evaluate if anticoagulation prior to COVID-19 infection may impact clinical profile, as well as mortality rate among patients hospitalized with COVID-19. The study was based on retrospective analysis of medical records of patients with laboratory confirmed SARS-CoV-2 infection. After propensity score matching (PSM), a group of 236 patients receiving any anticoagulant treatment prior to COVID-19 infection (AT group) was compared to 236 patients without previous anticoagulation (no AT group). In 180 days, the observation we noted comparable mortality rate in AT and no AT groups (38.5% vs. 41.1%, p = 0.51). Similarly, we did not observe any statistically significant differences in admission in the intensive care unit (14.1% vs. 9.6%, p = 0.20), intubation and mechanical ventilation (15.0% vs. 11.6%, p = 0.38), catecholamines usage (14.3% vs. 13.8%, p = 0.86), and bleeding rate (6.3% vs. 8.9%, p = 0.37) in both groups. Our results suggest that antithrombotic treatment prior to COVID-19 infection is unlikely to be protective for morbidity and mortality in patients hospitalized with COVID-19.

Deviations in laboratory tests assessing liver function in patients with COVID-19 are frequently observed. Their importance and pathogenesis are still debated. In our retrospective study, we analyzed liver-related parameters: aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin (TBIL), albumin, comorbidities and other selected potential risk factors in patients admitted with SARS-CoV-2 infection to assess their prognostic value for intensive care unit admission, mechanical ventilation necessity and mortality. We compared the prognostic effectiveness of these parameters separately and in pairs to the neutrophil-to-lymphocyte ratio (NLR) as an independent risk factor of in-hospital mortality, using the Akaike Information Criterion (AIC). Data were collected from 2109 included patients. We created models using a sample with complete laboratory tests n = 401 and then applied them to the whole studied group excluding patients with missing singular variables. We estimated that albumin may be a better predictor of the COVID-19-severity course compared to NLR, irrespective of comorbidities (p < 0.001). Additionally, we determined that hypoalbuminemia in combination with AST (OR 1.003, p = 0.008) or TBIL (OR 1.657, p = 0.001) creates excellent prediction models for in-hospital mortality. In conclusion, the early evaluation of albumin levels and liver-related parameters may be indispensable tools for the early assessment of the clinical course of patients with COVID-19.

Background: Diabetes mellitus is among the most frequent comorbidities worsening COVID-19 outcome. Nevertheless, there are no data regarding the optimal risk stratification of patients with diabetes and COVID-19. Since individual C2HEST components reflect the comorbidities, we assumed that the score could predict COVID-19 outcomes. Material and Methods: A total of 2184 medical records of patients hospitalized for COVID-19 at the medical university center were analyzed, including 473 diabetic patients and 1666 patients without any glucose or metabolic abnormalities. The variables of patients’ baseline characteristics were retrieved to calculate the C2HEST score and subsequently the diabetic and non-diabetic subjects were assigned to the following categories: low-, medium- or high-risk. The measured outcomes included: in-hospital mortality; 3-month and 6-month all-cause mortality; non-fatal end of hospitalization (discharged home/sudden-deterioration/rehabilitation) and adverse in-hospital clinical events. Results: A total of 194 deaths (41%) were reported in the diabetic cohort, including 115 in-hospital deaths (24.3%). The 3-month and 6-month in-hospital mortality was highest in the high-risk C2HEST stratum. The C2HEST score revealed to be more sensitive in non-diabetic-group. The estimated six-month survival probability for high-risk subjects reached 0.4 in both cohorts whereas for the low-risk group, the six-month survival probability was 0.7 in the diabetic vs. 0.85 in the non-diabetic group—levels which were maintained during whole observation period. In both cohorts, receiver operating characteristics revealed that C2HEST predicts the following: cardiogenic shock; acute heart failure; myocardial injury; and in-hospital acute kidney injury. Conclusions: We demonstrated the usefulness and performance of the C2HEST score in predicting the adverse COVID-19 outcomes in hospitalized diabetic subjects.

Senility has been identified among the strongest risk predictors for unfavorable COVID-19-outcome. However, even in the elderly population, the clinical course of infection in individual patients remains unpredictable. Hence, there is an urgent need for developing a simple tool predicting adverse COVID-19-outcomes. We assumed that the C2HEST-score could predict unfavorable clinical outcomes in the elderly subjects with COVID-19-subjects. Methods: We retrospectively analyzed 1047 medical records of patients at age > 65 years, hospitalized at the medical university center due to COVID-19. Subsequently, patients were divided into three categories depending on their C2HEST-score result. Results: We noticed significant differences in the in-hospital and 3-month and 6-month mortality-which was the highest in high-risk-C2HEST-stratum reaching 35.7%, 54.4%, and 65.9%, respectively. The medium-risk-stratum mortalities reached 24.1% 43.4%, and 57.6% and for low-risk-stratum 14.4%, 25.8%, and 39.2% respectively. In the C2HEST-score model, a change from the low to the medium category increased the probability of death intensity approximately two-times. Subsequently, transfer from the low-risk to the high-risk-stratum raised all-cause-death-intensity 2.7-times. Analysis of the secondary outcomes revealed that the C2HEST-score has predictive value for acute kidney injury, acute heart failure, and cardiogenic shock. Conclusions: C2HEST-score analysis on admission to the hospital may predict the mortality, acute kidney injury, and acute heart failure in elderly subjects with COVID-19.

Background: Since the outbreak of the COVID-19 pandemic, a growing number of evidence suggests that COVID-19 presents sex-dependent differences in clinical course and outcomes. Nevertheless, there is still an unmet need to stratify the risk for poor outcome at the beginning of hospitalization. Since individual C2HEST components are similar COVID-19 mortality risk factors, we evaluated sex-related predictive value of the score. Material and Methods: A total of 2183 medical records of consecutive patients hospitalized due to confirmed SARS-CoV-2 infections were analyzed. Subjects were assigned to one of two of the study arms (male vs. female) and afterward allocated to different stratum based on the C2HEST score result. The measured outcomes included: in-hospital-mortality, three-month- and six-month-all-cause-mortality and in-hospital non-fatal adverse clinical events. Results: The C2HEST score predicted the mortality with better sensitivity in female population regarding the short- and mid-term. Among secondary outcomes, C2HEST-score revealed predictive value in both genders for pneumonia, myocardial injury, myocardial infarction, acute heart failure, cardiogenic shock, and acute kidney injury. Additionally in the male cohort, the C2HEST value predicted acute liver dysfunction and all-cause bleeding, whereas in the female arm-stroke/TIA and SIRS. Conclusion: In the present study, we demonstrated the betterC2HEST-score predictive value for mortality in women and illustrated sex-dependent differences predicting non-fatal secondary outcomes.