A new logistic regression derived combined index for early prediction of in-hospital mortality in COVID-19 patients

BACKGROUND: While the type and the number of treatments for Coronavirus Disease 2019 (COVID-19) have substantially evolved since the start of the pandemic a significant number of hospitalized patients continue to succumb. This requires ongoing research in the development and improvement of early risk stratification tools. METHOD(S): We developed a prognostic score using epidemiological, clinical, laboratory, and treatment variables collected on admission in 130 adult COVID-19 patients followed until in-hospital death (N.=38) or discharge (N.=92). Potential variables were selected via multivariable logistic regression modelling conducted using a logistic regression univariate analysis to create a combined index. RESULT(S): Age, Charlson Comorbidity Index, P/F ratio, prothrombin time, C-reactive protein and troponin were the selected variables. AUROC indicated that the model had an excellent AUC value (0.971, 95% CI 0.926 to 0.993) with 100% sensitivity and 83% specificity for in-hospital mortality. The Hosmer-Lemeshow calibration test yielded non-significant P values (chi2=1.79, P=0.99) indicates good calibration. CONCLUSION(S): This newly developed combined index could be useful to predict mortality of hospitalized COVID-19 patients on admission.Copyright © 2022 EDIZIONI MINERVA MEDICA.

Prothrombin time, international normalized rate and in-hospital mortality in COVID-19

BACKGROUND: Blood coagulation alterations are frequent in patients with Coronavirus disease 2019 (COVID-19), particularly in those with severe forms. We investigated the association between standard parameters of coagulation and in-hospital mortality in COVID-19. METHODS: Demographic, clinical and laboratory data at hospital admission, including prothrombin time (PT), international normalized rate (INR), activated thromboplastin time (aPTT), and D-dimer were retrospectively collected in a consecutive series of 309 COVID-19 hospitalized patients. The associations between parameters of coagulation and in-hospital mortality were investigated with receiver operating characteristics (ROC), multiple regression and Kaplan- Meyer analyses. RESULTS: In the overall population, 220 (71.2%) patients were discharged alive, whereas the remaining 89 (28.8%) died. Non-survivors had significantly higher INR (median: 1.20;IQR: 1.03-1.32 vs. 1.06;IQR: 1.02-1.11, P<0.001), PT (median: 12.0 sec;IQR: 11.1-14.0 vs. 11.4 sec;IQR: 11.0-11.9, P<0.001), aPTT (median: 25.1 sec;IQR: 22.7-29.6 vs. 23.4 sec;IQR: 21.4-25.1, P<0.001) and D-dimer (median: 1.36 μg/mL;IQR: 0.87-4.11 vs. 0.77 μg/mL;IQR: 0.43-1.58, P<0.001). In multivariate Cox regression analysis, both the INR (HR=1.8459;95% CI: 1.0713-3.1806, P=0.027) and PT (HR=1.071;95% CI: 1.0132-1.1303, P=0.015), but not the aPTT and D-dimer, remained independently associated with survival. CONCLUSIONS: Both the PTand INRare independently associated with in-hospital mortality in COVID-19. The clinical utility of these parameters for risk stratification warrants further investigations.

The Systemic Inflammation Index on admission is independently associated with length of stay in hospitalized COVID-19 patients

BACKGROUND: The early detection of factors predicting hospital length of stay (LOS) in patients affected by severe acute respiratory syndrome in Coronavirus 2 (SARS-CoV-2) disease (COVID-19) might facilitate therapeutic decisions and patient flow management. METHODS: We collected routine clinical and laboratory parameters and derived inflammatory indexes on admission in 65 consecutive COVID-19 patients transferred to the Unit of Respiratory and Infectious Disease of the University Hospital of Sassari (North-Sardinia, Italy) who were alive on discharge. RESULTS: Patients with prolonged length of stay (LOS) (PLOS >= 26 days, N.=22) had significantly higher chest CT severity scores, neutrophils, neutrophil lymphocyte ratio (NLR), aggregate index of systemic inflammation, Systemic Inflammation Response Index, Systemic Inflammation Index (SII), aspartate aminotransferase, lactate dehydrogenase (LDH), and rates of obesity and respiratory support, than non-PLOS patients (N.=43). In univariate analysis, LOS was significantly and negatively correlated with lymphocytes and monocytes, and positively correlated with Body Mass Index (BMI), intensity of care, chest CT severity score, NLR, platelet lymphocyte ratio, SII and LDH. In multivariate regression analysis, only the SII was significantly associated with LOS (beta=0.506, P=0.002) after adjusting for BMI, intensity of care, chest CT severity score and LDH. CONCLUSIONS: SII values on admission were independently associated with LOS in COVID-19 patients. Prospective studies in larger cohorts are required to confirm our findings and to determine the role of the SII in clinical decision making.