Dysnatremia in COVID-19 Patients-An Analysis of the COLOS Study.

BACKGROUND: Sodium imbalance is one of the most common electrolyte disturbances encountered in the medical practice, and it may present with either hyponatremia or hypernatremia. Both sodium abnormalities are related with unfavorable outcomes. OBJECTIVE: Elucidation of the prevalence of dysnatremia among COVID-19 patients and its impact on 30- and 90-day mortality and need for ICU admission was the goal. DESIGN AND PARTICIPANTS: A single-center, retrospective, observational study was conducted. A total of 2026 adult, SARS-CoV-2 positive patients, admitted to Wroclaw University Hospital between 02.2020 and 06.2021, were included. On admission, patients were divided into groups: normonatremic (N), hyponatremic (L), and hypernatremic (H). Acquired data was processed, and Cox hazards regression and logistic regression were implemented. KEY RESULTS: Hyponatremia on admission occurred in 17.47% (n = 354) of patients and hypernatremia occurred in 5.03% (n = 102). Dysnatremic patients presented with more comorbidities, used more drugs, and were statistically more often admitted to the ICU. Level of consciousness was the strongest predictor of ICU admission (OR = 1.21, CI: 1.16-1.27, p < 0.001). Thirty-day mortality was significantly higher in both the L and H groups (28.52%, p = 0.0001 and 47.95%, p < 0.0001, respectively), in comparison to 17.67% in the N group. Ninety-day mortality showed a similar trend in all study groups: 34.37% in the L group (p = 0.0001), 60.27% (p < 0.0001) in the H group, and 23.32% in the N group. In multivariable analyses, hypo- and hypernatremia were found to be independent predictors of 30- and 90-day mortality. CONCLUSIONS: Both hypo- and hypernatremia are strong predictors of mortality and disease severity in COVID-19 patients. Extraordinary care should be taken when dealing with hypernatremic, COVID-positive patients, as this group exhibits the highest mortality rates.

The Usefulness of the COVID-GRAM Score in Predicting the Outcomes of Study Population with COVID-19.

BACKGROUND: The COVID-GRAM is a clinical risk rating score for predicting the prognosis of hospitalized COVID-19 infected patients. AIM: Our study aimed to evaluate the use of the COVID-GRAM score in patients with COVID-19 based on the data from the COronavirus in the LOwer Silesia (COLOS) registry. MATERIAL AND METHODS: The study group (834 patients of Caucasian patients) was retrospectively divided into three arms according to the risk achieved on the COVID-GRAM score calculated at the time of hospital admission (between February 2020 and July 2021): low, medium, and high risk. The Omnibus chi-square test, Fisher test, and Welch ANOVA were used in the statistical analysis. Post-hoc analysis for continuous variables was performed using Tukey's correction with the Games-Howell test. Additionally, the ROC analysis was performed over time using inverse probability of censorship (IPCW) estimation. The GRAM-COVID score was estimated from the time-dependent area under the curve (AUC). RESULTS: Most patients (65%) had a low risk of complications on the COVID-GRAM scale. There were 113 patients in the high-risk group (13%). In the medium- and high-risk groups, comorbidities occurred statistically significantly more often, e.g., hypertension, diabetes, atrial fibrillation and flutter, heart failure, valvular disease, chronic kidney disease, and obstructive pulmonary disease (COPD), compared to low-risk tier subjects. These individuals were also patients with a higher incidence of neurological and cardiac complications in the past. Low saturation of oxygen values on admission, changes in C-reactive protein, leukocytosis, hyperglycemia, and procalcitonin level were associated with an increased risk of death during hospitalization. The troponin level was an independent mortality factor. A change from low to medium category reduced the overall survival probability by more than 8 times and from low to high by 25 times. The factor with the strongest impact on survival was the absence of other diseases. The medium-risk patient group was more likely to require dialysis during hospitalization. The need for antibiotics was more significant in the high-risk group on the GRAM score. CONCLUSION: The COVID-GRAM score corresponds well with total mortality. The factor with the strongest impact on survival was the absence of other diseases. The worst prognosis was for patients who were unconscious during admission. Patients with higher COVID-GRAM score were significantly less likely to return to full health during follow-up. There is a continuing need to develop reliable, easy-to-adopt tools for stratifying the course of SARS-CoV-2 infection.

Usefulness of the C2HEST Score in Predicting the Clinical Outcomes of COVID-19 in Diabetic and Non-Diabetic Cohorts.

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.

The Usefulness of the C2HEST Risk Score in Predicting Clinical Outcomes among Hospitalized Subjects with COVID-19 and Coronary Artery Disease.

BACKGROUND: Even though coronary artery disease (CAD) is considered an independent risk factor of an unfavorable outcome of SARS-CoV-2-infection, the clinical course of COVID-19 in subjects with CAD is heterogeneous, ranging from clinically asymptomatic to fatal cases. Since the individual C2HEST components are similar to the COVID-19 risk factors, we evaluated its predictive value in CAD subjects. MATERIALS AND METHODS: In total, 2183 patients hospitalized due to confirmed COVID-19 were enrolled onto this study consecutively. Based on past medical history, subjects were assigned to one of two of the study arms (CAD vs. non-CAD) and allocated to different risk strata, based on the C2HEST score. RESULTS: The CAD cohort included 228 subjects, while the non-CAD cohort consisted of 1956 patients. In-hospital, 3-month and 6-month mortality was highest in the high-risk C2HEST stratum in the CAD cohort, reaching 43.06%, 56.25% and 65.89%, respectively, whereas in the non-CAD cohort in the high-risk stratum, it reached: 26.92%, 50.77% and 64.55%. Significant differences in mortality between the C2HEST stratum in the CAD arm were observed in post hoc analysis only for medium- vs. high-risk strata. The C2HEST score in the CAD cohort could predict hypovolemic shock, pneumonia and acute heart failure during hospitalization, whereas in the non-CAD cohort, it could predict cardiovascular events (myocardial injury, acute heart failure, myocardial infract, carcinogenic shock), pneumonia, acute liver dysfunction and renal injury as well as bleedings. CONCLUSIONS: The C2HEST score is a simple, easy-to-apply tool which might be useful in risk stratification, preferably in non-CAD subjects admitted to hospital due to COVID-19.

Liver Function Tests in COVID-19: Assessment of the Actual Prognostic Value.

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.

Usefulness of C2HEST Score in Predicting Clinical Outcomes of COVID-19 in Heart Failure and Non-Heart-Failure Cohorts.

BACKGROUND: Patients with heart failure represent a vulnerable population for COVID-19 and are prone to having worse prognoses and higher fatality rates. Still, the clinical course of the infection is dynamic, and complication occurrence in particular in patients with heart failure is fairly unpredictable. Considering that individual components of the C2HEST (C2: Coronary Artery Diseases (CAD)/Chronic obstructive pulmonary disease (COPD); H: Hypertension; E: Elderly (Age ≥ 75); S: Systolic HF; T: Thyroid disease) are parallel to COVID-19 mortality risk factors, we evaluate the predictive value of C2HEST score in patients with heart failure (HF) Material and Methods: The retrospective medical data analysis of 2184 COVID-19 patients hospitalized in the University Hospital in Wroclaw between February 2020 and June 2021 was the basis of the study. The measured outcomes included: in-hospital mortality, 3-month and 6-month all-cause-mortality, non-fatal end of hospitalization, and adverse in-hospital clinical events. RESULTS: The heart failure cohort consists of 255 patients, while 1929 patients were assigned to the non-HF cohort. The in-hospital, 3-month, and 6-month mortality rates were highest in the HF cohort high-risk C2HEST stratum, reaching 38.61%, 53.96%, and 65.36%, respectively. In the non-HF cohort, in-hospital, 3-month, and 6-month mortalities were also highest in the high-risk C2HEST stratum and came to 26.39%, 52.78%, and 65.0%, respectively. An additional point in the C2HEST score increased the total death intensity in 10% of HF subjects (HR 1.100, 95% CI 0.968-1.250 p = 0.143) while in the non-HF cohort, the same value increased by 62.3% (HR 1.623, 95% CI 1.518-1.734 p < 0.0001). CONCLUSIONS: The C2HEST score risk in the HF cohort failed to show discriminatory performance in terms of mortality and other clinical adverse outcomes during hospitalization. C2HEST score in the non-HF cohort showed significantly better performance in terms of predicting in-hospital and 6-month mortality and other non-fatal clinical outcomes such as cardiovascular events (myocardial injury, acute heart failure, myocardial infarction, cardiogenic shock), pneumonia, sepsis, and acute renal injury.

Sex-Dependent Differences in Predictive Value of the C2HEST Score in Subjects with COVID-19-A Secondary Analysis of the COLOS Study.

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 better C2HEST-score predictive value for mortality in women and illustrated sex-dependent differences predicting non-fatal secondary outcomes.