Evaluation of risk scores as predictors of mortality and hospital length of stay for older COVID-19 patients.

Objective: This study was intended to research the sensitivity of the Charlson Comorbidity Index (CCI), COVID-GRAM, and MuLBSTA risk scores for hospital length of stay (LOS) and mortality in older patients hospitalized with coronavirus disease 2019 (COVID-19). Methods: A total of 217 patients (119 women) were included in the study. The first clinical signs, comorbidities, laboratory and radiology findings, and hospital LOS were recorded for each patient. The CCI, COVID-GRAM, and MuLBSTA risk scores were calculated, and their sensitivities for hospital LOS and mortality were evaluated using receiver operating characteristic (ROC) curve analysis. Results: Of the hospitalized patients, 59 (27.2%) were followed in the intensive care unit, and mortality developed in 44 (20.3%). The CCI positively correlated with COVID-GRAM and MuLBSTA scores (P < 0.001). COVID-GRAM and MuLBSTA results correlated with LOS and mortality (P < 0.001). According to the ROC curve analysis, the cutoff points for mortality were 5 for CCI, 169 for COVID-GRAM, and 9 for MuLBSTA. Conclusion: Older patients with comorbidities are the major risk group for severe COVID-19. COVID-GRAM and MuLBSTA scores appear to be sensitive and reliable mortality indicators for these patients.

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.

Clinical Management of COVID-19 in Cancer Patients with the STAT3 Inhibitor Silibinin.

COVID-19 pathophysiology is caused by a cascade of respiratory and multiorgan failures arising, at least in part, from the SARS-CoV-2-driven dysregulation of the master transcriptional factor STAT3. Pharmacological correction of STAT3 over-stimulation, which is at the root of acute respiratory distress syndrome (ARDS) and coagulopathy/thrombosis events, should be considered for treatment of severe COVID-19. In this perspective, we first review the current body of knowledge on the role of STAT3 in the pathogenesis of severe COVID-19. We then exemplify the potential clinical value of treating COVID-19 disease with STAT3 inhibitors by presenting the outcomes of two hospitalized patients with active cancer and COVID-19 receiving oral Legalon®-a nutraceutical containing the naturally occurring STAT3 inhibitor silibinin. Both patients, which were recruited to the clinical trial SIL-COVID19 (EudraCT number: 2020-001794-77) had SARS-CoV-2 bilateral interstitial pneumonia and a high COVID-GRAM score, and showed systemic proinflammatory responses in terms of lymphocytopenia and hypoalbuminemia. Both patients were predicted to be at high risk of critical COVID-19 illness in terms of intensive care unit admission, invasive ventilation, or death. In addition to physician's choice of best available therapy or supportive care, patients received 1050 mg/day Legalon® for 10 days without side-effects. Silibinin-treated cancer/COVID-19+ patients required only minimal oxygen support (2-4 L/min) during the episode, exhibited a sharp decline of the STAT3-regulated C-reactive protein, and demonstrated complete resolution of the pulmonary lesions. These findings might inspire future research to advance our knowledge and improve silibinin-based clinical interventions aimed to target STAT3-driven COVID-19 pathophysiology.

Pneumonia severity indices predict prognosis in coronavirus disease-2019.

BACKGROUND: Early recognition of the severe illness is critical in coronavirus disease-19 (COVID-19) to provide best care and optimize the use of limited resources. OBJECTIVES: We aimed to determine the predictive properties of common community-acquired pneumonia (CAP) severity scores and COVID-19 specific indices. METHODS: In this retrospective cohort, COVID-19 patients hospitalized in a teaching hospital between 18 March-20 May 2020 were included. Demographic, clinical, and laboratory characteristics related to severity and mortality were measured and CURB-65, PSI, A-DROP, CALL, and COVID-GRAM scores were calculated as defined previously in the literature. Progression to severe disease and in-hospital/overall mortality during the follow-up of the patients were determined from electronic records. Kaplan-Meier, log-rank test, and Cox proportional hazard regression model was used. The discrimination capability of pneumonia severity indices was evaluated by receiver-operating-characteristic (ROC) analysis. RESULTS: Two hundred ninety-eight patients were included in the study. Sixty-two patients (20.8%) presented with severe COVID-19 while thirty-one (10.4%) developed severe COVID-19 at any time from the admission. In-hospital mortality was 39 (13.1%) while the overall mortality was 44 (14.8%). The mortality in low-risk groups that were identified to manage outside the hospital was 0 in CALL Class A, 1.67% in PSI low risk, and 2.68% in CURB-65 low-risk. However, the AUCs for the mortality prediction in COVID-19 were 0.875, 0.873, 0.859, 0.855, and 0.828 for A-DROP, PSI, CURB-65, COVID-GRAM, and CALL scores respectively. The AUCs for the prediction of progression to severe disease was 0.739, 0.711, 0,697, 0.673, and 0.668 for CURB-65, CALL, PSI, COVID-GRAM, A-DROP respectively. The hazard ratios (HR) for the tested pneumonia severity indices demonstrated that A-DROP and CURB-65 scores had the strongest association with mortality, and PSI, and COVID-GRAM scores predicted mortality independent from age and comorbidity. CONCLUSION: Community-acquired pneumonia (CAP) scores can predict in COVID-19. The indices proposed specifically to COVID-19 work less than nonspecific scoring systems surprisingly. The CALL score may be used to decide outpatient management in COVID-19.