Background: This study aims to evaluate the use of haematological indices and coagulation profiles as possible low-cost predictors of disease severity and their associations with clinical outcomes in COVID-19-hospitalized patients… Click to show full abstract
Background: This study aims to evaluate the use of haematological indices and coagulation profiles as possible low-cost predictors of disease severity and their associations with clinical outcomes in COVID-19-hospitalized patients in Nigeria. Materials and Methods: We carried out a hospital-based descriptive 3-month observational longitudinal study of 58 COVID-19-positive adult patients admitted at the Lagos University Teaching Hospital, Lagos, Nigeria. We used a structured questionnaire to obtain the participants' relevant sociodemographic and clinical data, including disease severity. Basic haematologic indices, their derivatives, and coagulation profile were obtained from patients' blood samples. Receiver Operating Characteristic (ROC) analysis was used to compare these laboratory-based values with disease severity. A P < 0.05 was considered statistically significant. Results: The mean age of the patients was 54.4 ± 14.8 years. More than half of the participants were males (55.2%, n = 32) and most had at least one comorbidity (79.3%, n = 46). Significantly higher absolute neutrophil count (ANC), neutrophil–lymphocyte ratio (NLR), systemic immune-inflammation index (SII), lower absolute lymphocyte count (ALC) and lymphocyte–monocyte ratio (LMR) were associated with severe disease (P < 0.05). Patients' hemoglobin concentration (P = 0.04), packed cell volume (P < 0.001), and mean cell hemoglobin concentration (P = 0.03) were also significantly associated with outcome. Receiver operating characteristic (ROC) analysis of disease severity was significant for the ANC, ALC, NLR, LMR, and SII. The coagulation profile did not show any significant associations with disease severity and outcomes in this study. Conclusion: Our findings identified haematological indices as possible low-cost predictors of disease severity in COVID-19 in Nigeria.
               
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