ABSTRACT
BACKGROUND: To determine the predictive value of mid-regional pro-adrenomedullin (MR-proADM) compared to routine clinical and laboratory parameters in patients with COVID-19. METHODS: A total of 135 adult patients hospitalized with COVID-19 were included in a prospective single-centre study. In addition to routine parameters, the levels of MR-proADM in blood plasma were measured on the day of hospitalization. The patients were divided into 2 groups: those who survived and were discharged (n = 115, 85%) and those who did not survive (n = 20, 15%). Data are presented as median and interquartile range. RESULTS: The non-survivors had a statistically significantly greater age (73.4 [63.5-84.8] vs. 62.2 [50.3-71.4] years, P = 0.001), a lower level of haemoglobin oxygen saturation (91 [87-92] vs. 92 [92-93]%, P < 0.001), lower lymphocyte level (13 [7-30] vs. 21 [15-27]%, P = 0.03), higher lactate dehydrogenase (338 [273-480] vs. 280 [233-383] EU L-1, P = 0.04) and aspartate aminotransferase levels (49 [28-72] vs. 33 [23-47] EU L-1, P = 0.03), a higher National Early Warning (NEWS) score (7 [7- 8] vs. 6 [5-7] points, P < 0.001), and higher procalcitonin (0.16 [0.11-0.32] vs. 0.1 [0.07-0.18] ng mL-1, P = 0.006) and MR-proADM levels (1.288 [0.886-1.847] vs. 0.769 [0.6-0.955] nmol L-1, P < 0.001). MR-proADM had the highest predictive value for death during hospital stay (cut-off: 0.895 nmol L-1, AUC ROC 0.78 [95% CI: 0.66-0.90], sensitivity 75%, specificity 69%, OR 6.58 [95% CI: 2.22-19.51]). CONCLUSIONS: Compared with other indicators, MR-proADM has the highest predictive value for in-hospital mortality in patients with COVID-19.
Subject(s)
Adrenomedullin , COVID-19 , Adult , Aspartate Aminotransferases , Biomarkers , Hemoglobins , Hospital Mortality , Humans , Lactate Dehydrogenases , Procalcitonin , Prognosis , Prospective Studies , Protein PrecursorsABSTRACT
Cardiopulmonary disorders cause a significant increase in the risk of adverse events in patients with COVID-19. Therefore, the development of new diagnostic and treatment methods for comorbid disorders in COVID-19 patients is one of the main public health challenges. The aim of the study was to analyze patient survival and to develop a predictive model of survival in adults with COVID-19 infection based on transthoracic echocardiography (TTE) parameters. We conducted a prospective, single-center, temporary hospital-based study of 110 patients with moderate to severe COVID-19. All patients underwent TTE evaluation. The predictors of mortality we identified in univariate and multivariable models and the predictive performance of the model were assessed using receiver operating characteristic (ROC) analysis and area under the curve (AUC). The predictive model included three factors: right ventricle (RV)/left ventricle (LV) area (odds ratio (OR) = 1.048 per 1/100 increase, p = 0.03), systolic pulmonary artery pressure (sPAP) (OR = 1.209 per 1 mm Hg increase, p < 0.001), and right ventricle free wall longitudinal strain (RV FW LS) (OR = 0.873 per 1% increase, p = 0.036). The AUC-ROC of the obtained model was 0.925 ± 0.031 (95% confidence interval (95% CI): 0.863-0.986). The sensitivity (Se) and specificity (Sp) measures of the models at the cut-off point of 0.129 were 93.8% and 81.9%, respectively. A binary logistic regression method resulted in the development of a prognostic model of mortality in patients with moderate and severe COVID-19 based on TTE data. It may also have additional implications for early risk stratification and clinical decision making in patients with COVID-19.