ABSTRACT
Covid-19 pandemic reveals that the virus causes Covid-19 associated coagulopathy and it is well known that thrombotic risk is associated with ethnicity. To describe the Covid-19 associated coagulopathy in Indian population and to correlate it with the disease severity and survivor status. A cross sectional descriptive study of 391 confirmed Covid-19 cases was carried out over a period of 1.5 months. Patients were categorised as mild to moderate, severe and very severe and also labelled as survivors and non survivors. Prothrombin time (PT), International normalised ratio (INR), activated partial thromboplastin time, D dimer, Fibrin degradation products (FDP), fibrinogen and thrombin time and platelet counts were investigated among the subgroups. Mean age was higher in patients with severe disease (57.62 ± 13.08) and among the non survivors (56.54 ± 12.78). Statistically significant differences in D dimer, FDP, PT, INR and age were seen among the 3 subgroups and survivors. Strong significant positive correlation was noted between D dimer and FDP (r = 0.838, p < .001), PT and INR (r = 0.986, p < 0.001). D dimer was the best single coagulation parameter as per the area under curve (AUC: 0.762, p < 0.001) and D dimer + FDP was the best combination parameter (AUC: 0.764, p = 0) to differentiate mild moderate from severe disease. Raised levels of D dimer, FDP, PT, PT INR and higher age correlated positively with disease severity and mortality in Indian Population.
ABSTRACT
BACKGROUND: The "cytokine storm" (CS) in COVID-19 leads to the worst stage of illness which can be controlled only with timely intervention. There is an urgent need to identify laboratory markers of disease progression for optimum allocation of resources in developing countries like India. METHODS: A cross-sectional study was conducted on 100 COVID-19 positive patients over two months. The cases were sub-classified based on disease severity into mild to moderate (n=61), severe (n=26) and very severe (n=13) and into survivors (n=85) and non-survivors (n=15) based on survivor status. These patients were tested for hematological parameters (total blood lymphocyte counts, NLR, PLR, platelet indices etc.), coagulation markers (D-dimer, fibrin degradation products (FDP), fibrinogen etc.) and biochemical markers (LDH, ferritin, IL-6, procalcitonin, hs-CRP). RESULTS: Statistically significant differences were observed in hematological variables (ANC, NLR and ESR), coagulation parameters (D-dimer, FDP, fibrinogen and thrombin time) and biochemical markers (LDH, ferritin, IL-6, procalcitonin and hs-CRP) with regard to subcategories based of disease severity as well as survivor status. There was strong correlation between NLR, D-dimer, IL-6, procalcitonin and ferritin. IL-6 emerged as the single best marker of disease severity (AUC: 0.997, P=0.00), however procalcitonin, LDH, D-dimer, FDP and NLR could also predict severe disease with a good sensitivity and specificity. CONCLUSION: To conclude, study demonstrates a plethora of biomarkers which could be utilized to accurately identify the hyperinflammation and tissue damage reminiscent of cytokine storm in COVID-19 patients so that timely, safe, and effective therapies can be administered to prevent progression and potentially reduce mortality.
ABSTRACT
Background: COVID-19 is a systemic viral infection with a significant impact on the hematopoietic system, hemostasis as well as immune system. It would be of utmost importance to explore if the most routinely used tests could serve as an aid in determining patient’s clinical status or predicting severity of the disease. Methods: A pro
ABSTRACT
Aims & Objectives: The aims and objectives of present study were to evaluate the various Hematological parameters including Neutrophil- lymphocyte ratio (NLR), Platelet-lymphocyte ratio (PLR) in COVID- 19 patients and controls and to study correlation of these parameters with each other and with disease severity. Patients/Materials & Methods: A prospective cross sectional study was conducted on 506 Covid-19 positive patients and 50 controls over a period of two months (June to July 2020). The cases were subclassified based on disease severity into mild to moderate (n = 337), severe (n = 118) and very severe (n = 51) and into survivors (n = 473) and non survivors (n = 33) based on survivor status. Results: There were statistically significant differences in WBC count, Absolute neutrophil count (ANC), Absolute lymphocyte count (ALC), absolute monocyte count (AMC), NLR, PLR, RDW SD and RDW CV between covid cases vs controls;among the clinical subgroups and among the survivors and non survivors. There was a significant strong positive correlation between various parameters, that is, NLR and MLR (r: 0.852, p = 0), MPV and PDW (r: 0.912, p = 0), MPV and PLCR (r:0.956, p = 0), PDW and PLCR (r:0.893, p = 0). NLR (AUC: 0.676, p = 0) was the best single parameter and NLR + RDW-CV was best combination parameter as per area under curve (0.871) of ROC to distinguish severe from mild to moderate disease. Discussion & Conclusion: Leucocytosis, neutrophilia, lymphopenia and monocytosis were characteristic while NLR and NLR + RDWCV emerged as the most effective single and combination CBC parameters in distinguishing mild to moderate and severe cases respectively.