Early Detection and Assessment of Covid-19 - Hashmi, Hafiz Abdul Sattar; Asif, Hafiz Muhammad (Frontiers in Medicine, 2020)
Background: Since Covid-19 global pandemic emerged, developing countries are facing multiple challenges for its diagnosis. We aimed to establish a relationship between sign and symptoms of COVID-19 for early detection and assessment to reduce transmission rate of SARS-Cov-2. Methods: We collected published data on clinical features of Covid-19 retrospectively and categorized into physical and blood biomarkers. Common features were assigned scores by Borg scoring method with slight modifications and incorporated into newly developed Hashmi-Asif Covid-19 assessment Chart. Correlation of sign and symptoms with development of Covid-19 was assessed by Pearson correlation and Spearman Correlation coefficient (rho). Linear regression analysis employed to assess highest correlating features. Frequency of sign and symptoms to develop in Covid-19 was assessed through Chi-square test two tailed with Cra-mer’s V strength. Changes in sign and symptoms were incorporated into chart consisted on four tiers representing disease stages. Results: Data of 10172 Covid-19 laboratory confirmed cases showed correlation with Fever in 43.9% (P=0.000) cases, cough 54.08% and dry mucus 25.68% equally significant (P=0.000), Hyperemic pharyngeal mucus membrane 17.92% (P=0.005), leukopenia 28.11% (P=0.000), lymphopenia 64.35% (P=0.000), thrombopenia 35.49% (P=0.000), elevated Aspartate aminotransferase 50.02% (P=0.000) and Alanine aminotransferase 34.49% (P=0.000). Chart exhibit maximum scoring 39. Normal tier scoring ≤12/39, mild state scored 13-22/39 or star values scoring ≥7/15 on chart means Covid-19 is progressing and quarantine be adopted. Moderate stage showed 23-33 and severe scored 34-39 in chart. Conclusion: Hashmi-Asif Covid-19 Chart holds significance to assess subclinical and clinical stages of Covid-19 to reduce transmission rate.