ABSTRACT
BACKGROUND: Although there are many COVID-19 case series studies, few studies report the relationship between variations in blood cell parameters and inflammatory factors and disease severity. This study aims to describe the dynamic trends in COVID-19 blood cell parameters and inflammatory factors. METHODS: Ninety-two patients with confirmed COVID-19 at Jingzhou Central Hospital, Hubei Province, China, between January 23, 2020, and April 10, 2020, were enrolled. Epidemiological data, clinical information, and laboratory test results were collected and analyzed. RESULTS: As patient age increased, disease severity increased (P<0.0001). The inflammatory factor C-reactive protein (CRP) showed a gradual increasing trend with disease aggravation. Based on dynamic change graphs, CRP in all patients with severe and critical COVID-19 initially increased and then decreased; however, CRP in patients with a good prognosis did not increase again after the initial decline (<20 mg/L). CRP in patients with a poor prognosis returned to a high level (>50 mg/L) 1 week after the initial decrease and continued to fluctuate at a high level. Lymphocyte count (LYM#) in patients with severe and critical disease was significantly lower (<1×109/L) than that in patients with moderate disease; LYM# was significantly increased 3 weeks after disease onset in patients with a good prognosis (>1×109/L), but patients with a poor prognosis continued to have a low LYM#. CONCLUSIONS: CRP and LYM# showed strong correlation with disease progression, suggesting that these parameters could be used to monitor changes in patient condition.
ABSTRACT
BACKGROUND: The global mortality rate for coronavirus disease 2019 (COVID-19) is 3.68%, but the mortality rate for critically ill patients is as high as 50%. Therefore, the exploration of prognostic predictors for patients with COVID-19 is vital for prompt clinical intervention. Our study aims to explore the predictive value of hematological parameters in the prognosis of patients with severe COVID-19. METHODS: Ninety-eight patients who were diagnosed with COVID-19 at Jingzhou Central Hospital and Central Hospital of Wuhan, Hubei Province, were included in this study. RESULTS: The median age of the patients was 59 [28-80] years; the median age of patients with a good prognosis was 56 [28-79] years, and the median age of patients with a poor outcome was 67 [35-80] years. The patients in the poor outcome group were older than the patients in the good outcome group (P<0.05). The comparison of hematological parameters showed that lymphocyte count (Lym#), red blood cells (RBCs), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) were significantly lower in the poor outcome group than in the good outcome group (P<0.05). Further, the red cell volume distribution width-CV (RDW-CV) and red cell volume distribution width-SD (RDW-SD) were significantly higher in the poor outcome group than in the good outcome group (P<0.0001). Receiver operating characteristic (ROC) curves showed RDW-SD, with an area under the ROC curve (AUC) of 0.870 [95% confidence interval (CI) 0.796-0.943], was the most significant single parameter for predicting the prognosis of severe patients. When the cut-off value was 42.15, the sensitivity and specificity of RDW-SD for predicting the prognosis of severe patients were 73.1% and 80.2%, respectively. Reticulocyte (RET) channel results showed the RET level was significantly higher in critical patients than in moderate patients and severe patients (P<0.05), which may be one cause of the elevated RDW in patients with a poor outcome. CONCLUSIONS: In this study, the hematological parameters of COVID-19 patients were statistically analyzed. RDW was found to be a prognostic predictor for patients with severe COVID-19, and the increase in RET may contribute to elevated RDW.
ABSTRACT
BACKGROUND: The third fatal coronavirus is the novel coronavirus (SARS-CoV-2) that causes novel coronavirus pneumonia (COVID-19) which first broke out in December 2019. Patients will develop rapidly if there is no any intervention, so the risk identification of severe patients is critical. The aim of this study was to investigate the characteristics and rules of hematology changes in patients with COVID-19, and to explore the possibility differentiating moderate and severe patients using conventional hematology parameters or combined parameters. METHODS: The clinical data of 45 moderate and severe type patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in Jingzhou Central Hospital from January 23 to February 13, 2020 were collected. The epidemiological indexes, clinical symptoms, and laboratory test results of the patients were retrospectively analyzed. Those parameters with significant differences between moderate and severe cases were analyzed, and the combination parameters with the best diagnostic performance were selected using the linear discriminant analysis (LDA) method. RESULTS: Of the 45 patients with the novel 2019 corona virus (COVID-19) (35 moderate and 10 severe cases), 23 were male and 22 were female, with ages ranging from 16 to 62 years. The most common clinical symptoms were fever (89%) and dry cough (60%). As the disease progressed, white blood cell count (WBC), neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), red blood cell distribution width-coefficient of variation (RDW-CV), and red cell volume distribution width-standard deviation (RDW-SD) parameters in the severe group were significantly higher than those in the moderate group (P<0.05); meanwhile, lymphocyte count (Lym#), eosinophil count (Eos#), high fluorescent cell percentage (HFC%), red blood cell count (RBC), hemoglobin (HGB), and hematocrit (HCT) parameters in the severe group were significantly lower than those in the moderate group (P<0.05). For NLR parameter, it's area under the curve (AUC), cutoff, sensitivity and specificity were 0.890, 13.39, 83.3% and 82.4% respectively; meanwhile, for PLR parameter, it's AUC, cutoff, sensitivity and specificity were 0.842, 267.03, 83.3% and 74.0% respectively. The combined parameters of NLR and RDW-SD had the best diagnostic efficiency (AUC =0.938), and when the cutoff value was 1.046, the sensitivity and the specificity were 90.0% and 84.7% respectively, followed by the combined parameter NLR&RDW-CV (AUC =0.923). When the cut-off value was 0.62, the sensitivity and the specificity for distinguishing severe type from moderate cases of COVID-19 were 90.0% and 82.4% respectively. CONCLUSIONS: The combined NLR and RDW-SD parameter is the best hematology index. It may help clinicians to predict the severity of COVID-19 patients and can be used as a useful indicator to help prevent and control the epidemic.