| ORIGINAL ARTICLE |
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| Year : 2022 | Volume
: 19
| Issue : 4 | Page : 199-203 |
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Role of prognostic markers as a predictor of mortality and short-term prognosis in COVID-19
Ajith Kumar Jayachandran1, Vincy Nelson2, F Thaiba1, Mohammad Easa Shajahan1
1 Department of Emergency Medicine, Travancore Medical College, Kollam, Kerala, India
2 Department of Community Medicine, Travancore Medical College, Kollam, Kerala, India
Correspondence Address:
Dr. Ajith Kumar Jayachandran
Department of Emergency Medicine, Travancore Medical College, Thattamala, Kollam - 691 020, Kerala
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/am.am_68_22
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Introduction: As the world is slowly out of its second wave wrecked by the Delta strain, the world population is now struck once again with a new strain of COVID-19. As the outbreak is spreading, prognostic markers such as C-reactive protein (CRP), D-dimer, and ferritin levels can help the physician in predicting clinical outcomes at an early stage. Materials and Methods: Our study made an analysis of patients presented to the emergency medicine department with positive COVID antigen or reverse transcriptase–polymerase chain reaction (RT-PCR) results. Patient demographic data, clinical profile, and values of D-dimer, CRP, and serum ferritin were obtained. All the patients were subjected to standard treatment according to COVID protocol. Results: Our study population was comprised of 312 patients. Among them, 162 (51.9%) were male, and 150 (48.1%) were female. Our study found that among 45 patients, who had expired, 38 (84.4%) patients had elevated D-dimer values, 45 (100%) patients had elevated CRP values, and 41 (91.1%) patients had elevated ferritin values. P =001, which is statistically significant. Conclusion: Our study found that values of prognostic markers such as D-dimer, CRP, and serum ferritin at the time of presentation can be used as a predictor of mortality and risk stratification and predict the probable need for prolonged hospital and intensive care unit stay. These values also correlate well with the disease severity of the patients. They can also be used to predict the probable need for respiratory support during the course of a stay in the hospital.
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