Poor Prognostic Biochemical Markers Predicting Fatalities Caused by COVID-19: A Retrospective Observational Study From a Developing Country

Background and objectives Infections with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are rapidly spreading, posing a serious threat to the health of people worldwide, resulting in the World Health Organization officially declaring it a pandemic. There are several biochemical markers linked with predicting the severity of coronavirus disease. This study aims to identify the most effective predictive biomarker such as C-reactive protein (CRP), ferritin, lactate dehydrogenase (LDH), procalcitonin (PCT), and D-dimer, among others, in predicting the clinical outcome of the disease. Materials and methods This study was conducted as a retrospective, observational, multi-centric study, including all admitted COVID-19 positive patients only. The disease outcome was followed along with the hospital course of every patient at the time of analysis. Baseline laboratory investigations of all patients were monitored both at admission and discharge. A comparative analysis was done between the survivors (n=263) and non-survivors (n=101). Statistical analysis was conducted using IBM SPSS Statistics for Windows Version 25 (Armonk, NY: IBM Corp.). Results Of 364 patients, 65.7% were in the isolation ward, and 34.3% were in the intensive care unit; 72.3% of patients survived, while 27.7% of patients died. The mean age of the study population was 52.6 ± 15.8 years with female patients significantly younger than male patients (p=0.001) and 50 to 75 years being the most common age group (p=0.121). Among the survivors versus non-survivors of COVID-19, there were significant differences in total leukocyte count (p<0.001), neutrophil count, (p<0.001), lymphocyte count (p<0.001), urea (p<0.001), serum bicarbonate (p=0.001), CRP levels (p<0.001), LDH (p=0.013), and D-dimer (p<0.001) at admission. At discharge, the laboratory values of non-surviving patients showed significant leukocytosis (p<0.001), neutrophilia (p<0.001), lymphocytopenia (p<0.001), decreased monocytes (p<0.001), elevated urea and creatinine (p<0.001), hypernatremia (p<0.001), decreased serum bicarbonate levels (p<0.001), elevated CRP level (p=0.040), LDH (p<0.001), ferritin (p=0.001), and D-dimer (p<0.001). Among the recovered patients, the laboratory investigations at admission were significantly different from those at discharge like increased platelets (p=0.007), lower neutrophil count (p=0.001), higher lymphocyte count (p=0.005), an improved creatinine (p=0.020), higher sodium (p=0.008), increased bicarbonate levels (p<0.001), decreased CRP levels (p<0.001), and a lower LDH (p=0.039). However, the laboratory values of non-surviving patients had shown a lower hemoglobin (p=0.016), increased mean cell volume (p<0.001), significantly increased total leukocyte count (p<0.001), increased urea and creatinine (p<0.001), hypernatremia (p<0.001), increased bicarbonate (p=0.025), elevated D-dimer levels (p=0.043), and elevated PCT (p=0.021) on discharge. Receiver operating characteristic analysis concluded LDH (area under the curve [AUC]: 0.875), D-dimer (AUC: 0.803), and PCT (AUC: 0.769) were superior biomarkers to ferritin (AUC: 0.714) and CRP (AUC: 0.711) in predicting the fatality of COVID-19. Conclusion Inflammatory markers are a useful guide for predicting mortality, and the study results concluded that LDH, PCT, D-dimer, CRP, and ferritin were effective biomarkers.