Laboratory Markers Versus Ct Severity Score In Predicting Mortality In Covid 19
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 10, Pages 1824-1831
AbstractAim: Predicting the mortality of COVID-19 with a spectrum of complications is a difficult task for prognostication and management. When individual level data of COVID-19 patients were not yet available, there is a need for risk predictors to support the treatment decisions. The study aims to identify the high accurate marker to measure the prognosis and outcome of COVID19.
COVID-19 course is divided into four stages, according to chest computed tomography (C.T.) progress. The demographics, disease exposure history, clinical condition, laboratory tests, computed tomographic chest scan, and outcome data were collected and measured their correlation to assess the risk predictor.
The 10.4% mortality (n=52) was observed in total population. D-dimer (μg/dL) levels observed as 0.75 ± 0.65 in expired patients. NLR ratio observed as 17.1 in expired patients. Ferritin levels were observed as 49.8 ± 32.5 in expired patients. A D-dimer positive predictive value of 72.5% and a negative predictive value of 88% for a predictor of mortality. Ferritin positive predictive value of 35.5% and a negative predictive value of 76.5% for the predictor of mortality. Hence, the AUC of serum ferritin 0.598 represents the poor ability to discriminate the prediction for the cause of death than D-dimer levels. D‐dimer > 2 μg/dL on admission was associated with in‐hospital death. These main findings indicate that D‐dimer on admission >2.0 μg/dl was the independent predictor of hospital death in patients with Covid‐19. A D-dimer has the highest positive predictive value than serum ferritin levels.
Conclusion: The AUC for D- dimer at admission was 0.880, with an optimal cutoff of 2.2 μg/dL in predicting the cause of mortality. D‐dimer on admission > 2.0 μg/mL (fourfold increase) is the best predict in‐hospital mortality and a helpful marker to improve the management of Covid‐19.
- Article View: 330
- PDF Download: 307