A Correlative Analysis between CoVID-19 Severity Patient Blood Report and Lung Conditions

The COVID-19 pandemic has impacted individuals worldwide, with each patient experiencing varying symptoms such as fever, body aches, loss of taste, and reduced appetite. Following recovery, many patients report diverse side effects influenced by factors like body composition, infection severity, and pre-existing health conditions. Researchers globally are examining both short- and long-term effects of COVID-19 on various organs to enhance drug quality, safety measures, and preventive protocols. This study investigates the correlation between COVID-19 severity and its side effects through an empirical model. The model evaluates key parameters, including C-reactive protein, cycle threshold value, chest CT scan scores, oxygen levels, hemoglobin, white blood cells, red blood cells, D-dimer, and vitamin D3 and B13 levels, based on historical data and manual analysis of patient reports. Computational tools were developed to estimate these parameters and assess their relationship with COVID-19 severity. Tested on over 100 patients with varying severity levels, the study found strong correlations for CTV, RBC, WBC, D-dimer, D3, and B13 levels. Clinical validation demonstrated 91% accuracy, highlighting the model's potential for real-time application. These findings contribute to a deeper understanding of COVID-19's health impacts and support improved patient care strategies, in comparison to previous work which only focused on image-based research which is more time consuming and cost ineffective.