Clinical Value of Platelets and Coagulation Parameters in Predicting the Severity of Delta Variant SARS-CoV-2.

INTRODUCTION: The present study aimed to analyze the clinical features and laboratory markers of patients with Delta variant SARS-CoV-2 and explore the role of platelet in predicting the severity of Delta. METHODS: This retrospective, observational study was conducted on 863 patients laboratory-confirmed Delta variant SARS-CoV-2. These cases were sub-classified based on disease severity into mild (n = 304), moderate (n = 537), and severe (n = 22). A series of laboratory findings and clinical data were collected and analyzed during hospitalization. RESULTS: Of 863 hospitalized patients with Delta, the median age was 38 years (interquartile range, 30-51 years) and 471 (54.58%) were male. The most common clinical symptoms mainly included cough, fever, pharyngalgia, expectoration, dyspnea, fatigue, and headache, and the commonest comorbidities were hypertension and diabetes. Among the hematological variables, neutrophil count, red blood cell count, and hemoglobin, were found to be statistically significant with regard to subcategories based of disease severity (p < 0.05). Among coagulation parameters, there was a statistically significant difference in D-dimer, fibrinogen, international normalized ratio, and prothrombin time (p < 0.05). Statistically significant differences were observed in platelet markers including platelet count, large platelet count, and plateletcrit (p < 0.05). Additionally, there was strong correlation between platelet and other parameters with disease severity. Logistical regression analysis and ROC curves showed that D-dimer was a single best marker of disease severity (p = 0.005, p < 0.0001); however, platelet (p = 0.009, p = 0.002) and plateletcrit (p = 0.002, p = 0.001) could also predict severe disease. Platelet was identified as an independent risk factor for severe Delta. CONCLUSION: Low platelet may be a marker of disease severity in Delta variant SARS-CoV-2 and may contribute to determine the severity of patients infected with Delta.

Lymphocyte blood levels that remain low can predict the death of patients with COVID-19.

ABSTRACT: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been rapidly spreading on a global scale and poses a great threat to human health. However, efficient indicators for disease severity have not been fully investigated. Here, we aim to investigate whether dynamic changes of lymphocyte counts can predict the deterioration of patients with COVID-19.We collected data from 2923 patients with laboratory-confirmed COVID-19. Patients were then screened, and we focused on 145 severe cases and 60 critical cases (29 recovered cases, 31 deaths). The length of hospitalization was divided into five time points, namely admission, 25%, 50%, 75% and discharge or death, according to the principle of interquartile distance. A series of laboratory findings and clinical data were collected and analyzed during hospitalization. The results showed that there were differences in levels of leukocytes, neutrophils and lymphocytes at almost every time point in the severe cases and 60 critical cases (29 recovered cases, 31 deaths). Further analysis showed that 70.2% of the COVID-19 cases had low circulating lymphocyte count, of which 64.1% were severe cases and 85.0% were critical cases (75.9% recovered cases and 93.5% died). Moreover, the lymphocyte count in dead cases was significantly lower than that of critical cases who recovered, at almost every time point in the critical groups. We also divided critical patients into group A (<1.1 × 109/L) and group B (>1.1 × 109/L) according to number of lymphocytes. Through survival analysis, we found that there was no significant difference in survival between group A and group B at admission (P = .3065). However, the survival rate according to lymphocyte levels in group A was significantly lower than that of group B at 25% hospital stay (on average day 6.5), 50% and 75% time points (P < .001).Lymphocyte counts that remain lower after the first week following symptom onset are highly predictive of in-hospital death of adults with COVID-19. This predictor may help clinicians identify patients with a poor prognosis and may be useful for guiding clinical decision-making at an early stage.

α-HBDH Is a Probably Higher Sensitive and Specific the Biomarkers of Poor Prognosis in Patients With COVID-19 (preprint)

Background: The coronavirus disease 2019 (COVID-19) that is caused by the severe acute respiratory syndrome-coronavirus2 (SARS-CoV2) has spread rapidly worldwide during the past nearly a year. SARS-CoV-2 particles spread through the respiratory mucosa and infect other cells, causing a storm of cytokines in the body 1 , producing a series of immune responses, and causing multiple organ dysfunction, including the heart. Some patients present with cardiovascular system damage, such as palpitations and shortness of breath as the first or secondary symptoms. Previous studies suggested that LDH, α-HBDH, CK and CK-MB reflect myocardial function. 2 Here, we aim to investigate whether these markers can predict poor prognosis of patients with COVID-19. Methods: : We collected data from 2338 patients with laboratory-confirmed COVID-19. Patients were then screened, and we focused on 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). We divided these patients into non-critical group (n = 49) and critical group (n = 151). Then, we also divided the length of hospitalization into five time points, namely admission, 25%, 50%, 75% and discharge or death, according to the principle of interquartile distance. Blood was collected from patients on the above five time points. Patients with five blood tests were 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). LDH, α-HBDH, CK and CK-MB of each group were collected for analysis. Results: : Our research found that α-HBDH and LDH of the critical groups significantly increased, diagnostic efficiency of LDH and α-HBDH have more advantages than that of CK and CK-MB compared with the non-critical group, and patients with α-HBDH greater than 182IU/L and LDH greater than 250IU/L at admission had lower survival rates. Then, CK, LDH, α-HBDH and CK-MB were observed dynamically in the 49 moderate cases, 98 severe cases and 53 critical cases (27 recovered cases, 26 deaths). It turns out that they increased progressively in the dead patients, while they decreased regularly in the severe case and the critical cases(recovered)(P＜0.001). Conclusions: : The prognosis of patients with abnormal α-HBDH was poor on admission. α-HBDH is a probably higher sensitive and specific the biomarkers of poor prognosis in patients with COVID-19. This predictor may help clinicians identify patients with a poor prognosis and may be useful for guiding clinical decision-making at an early stage.