Utility of biomarkers in predicting the severity and mortality of coronavirus disease 2019 infection: A retrospective observational study

Sapna S Deshpande; Namrata Mestri; Mohasin J Halgale; Pradnya M Chimankar

doi:10.4103/jcrsm.jcrsm_72_21

ORIGINAL ARTICLE

Year : 2022 | Volume : 8 | Issue : 1 | Page : 64-68

Utility of biomarkers in predicting the severity and mortality of coronavirus disease 2019 infection: A retrospective observational study

Sapna S Deshpande¹, Namrata Mestri¹, Mohasin J Halgale², Pradnya M Chimankar¹
¹ Department of Pathology, Dr. D.Y. Patil Medical College, Kolhapur, Maharashtra, India
² Department of Pathology, R.C.S.M. Government Medical College, Kolhapur, Maharashtra, India

Date of Submission	22-Sep-2021
Date of Decision	07-Jan-2022
Date of Acceptance	11-Jan-2022
Date of Web Publication	8-Jul-2022

Correspondence Address:
Mohasin J Halgale
816/3, Plot No. 6, Karande Mala, Devane Colony, Opp. Sriram Residency, Kolhapur - 416 003, Maharashtra
India

Source of Support: None, Conflict of Interest: None

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DOI: 10.4103/jcrsm.jcrsm_72_21

Abstract

Context: The clinical course of Coronavirus Disease 2019 (COVID-19) infection is variable and subjective. Hence, there is a dire need for objective interpretation of severity. The utilization of biomarkers categorizes these patients into nonsevere, severe, or critical categories.
Aim: This study aims to assess the role of different biomarkers in predicting the severity and mortality of COVID 19.
Materials and Methods: Case records of 247 patients of a designated COVID center in Kolhapur, Maharashtra, India, were included in this observational study. Biomarkers such as total leukocyte count, C-reactive protein, lactate dehydrogenase, D-Dimer, interleukin-6 (IL-6), procalcitonin, and serum ferritin were studied in different categories of severity of the disease.
Results: The median serum ferritin levels among nonsevere cases, severe, and critical cases were 187.95 ng/mL (interquartile range [IQR] = 93.05 ng/mL to 382.50 ng/mL), 230 ng/mL (156 ng/mL to 670 ng/mL), and 412.33 ng/mL (234 ng/mL to 689 ng/mL), respectively and this difference was statistically significant (P < 0.001). The average values of IL-6 were significantly higher (P < 0.001) among the patients who died (19.12 pg/mL) when compared to those which were alive (3.74 pg/mL). Based on the receiver operating characteristic analysis, the interpretation of the severity of the disease was excellent through the evaluation of levels of serum ferritin (Area under curve = 0.755 [95% confidence interval = 0.635–0.875; P = 0.001]).
Conclusions: Serum ferritin among the biomarker panel studied was the best test that predicted the severity of COVID-19 infection. The IL-6 levels were significantly higher among the patient who succumbed when compared to those who survived the disease.

Keywords: Coronavirus disease 2019, IL-6, serum ferritin, severity

How to cite this article:
Deshpande SS, Mestri N, Halgale MJ, Chimankar PM. Utility of biomarkers in predicting the severity and mortality of coronavirus disease 2019 infection: A retrospective observational study. J Curr Res Sci Med 2022;8:64-8

How to cite this URL:
Deshpande SS, Mestri N, Halgale MJ, Chimankar PM. Utility of biomarkers in predicting the severity and mortality of coronavirus disease 2019 infection: A retrospective observational study. J Curr Res Sci Med [serial online] 2022 [cited 2023 May 30];8:64-8. Available from: https://www.jcrsmed.org/text.asp?2022/8/1/64/347051

Introduction

In December 2019, the world witnessed a pandemic of unknown viral pneumonia, with Wuhan city in China as the epicenter.^[1] The etiological agent of this disease was initially named severe acute respiratory syndrome coronavirus 2. However, in February 2020, the World Health Organization (WHO) renamed it Coronavirus Disease 2019 (COVID-19).^[2] COVID-19 infection is transmitted mainly through the respiratory tract with a very high transmission speed and infectivity. Most of the patients infected with this virus are asymptomatic, while others present with fever, myalgia, and mild upper respiratory symptoms in the initial phase. In the second phase of the disease, there is a worsening of the symptoms. Finally, severe lung inflammation leads to acute respiratory distress syndrome (ARDS) in the third phase.^[3],[4] Evidence suggests that the clinical course of COVID-19 is variable, and the symptoms are subjective.^[2],[4] Thus there is a dire need for objective interpretation of severity. The utilization of biomarkers categorizes these patients into nonsevere, severe, or critical categories. Thus, it enables earlier and prompt intervention in COVID-19 patients. This study aims to assess the role of different biomarkers in predicting the severity and mortality of COVID-19.

Materials and Methods

Subjects

This was a retrospective observational study. Case records of patients admitted to the designated COVID center in Kolhapur, Maharashtra, India, was reviewed. Institutional Ethical Committee approval was obtained (IEC no. DYPMCK/442/2021). Records of 280 patients admitted from August 2020 to September 2020 were enrolled. Due to the nonavailability of some biomarker data, we had excluded 37 cases from the analysis. Hence, a total of 247 case records with reverse transcriptase-polymerase chain reaction (RT-PCR) positive for the nucleic acid of COVID-19 were included in the study. Asymptomatic patients and patients with RT-PCR negative were excluded. Due to the variability of biomarkers in the age group <18 years, they were excluded from the study.

Verbal consent was taken from the individuals included in the study. Written consent was waived due to the existing infectiousness of the disease. The necessary permissions were taken from the records in-charge of the institution to collect the data.

Definitions

Definitions for the categorization of COVID-19 were adapted using the WHO guidelines.^[5] Critical COVID 19 was defined by the presence of ARDS, sepsis, septic shock, or other conditions that would normally require the provision of life-sustaining therapies such as mechanical ventilation (invasive or noninvasive) or vasopressor therapy. Severe COVID-19 infection was defined by the presence of oxygen saturation <90% on room air, respiratory rate >30 breaths/min in adults, signs of severe respiratory distress (accessory muscle use, inability to complete full sentences, etc.). Nonsevere COVID-19-infected patients were those patients who were not categorized into severe and critical COVID-19 infection.

Research methods

Age, sex, comorbidities, clinical symptoms, vital signs and laboratory indices, results of routine blood tests, liver and kidney function test bleeding time, clotting time and biomarkers like total leukocyte count (TLC), C-reactive protein (CRP), lactate dehydrogenase (LDH), D-Dimer, interleukin-6 (IL-6), procalcitonin (PCT), and serum ferritin were retrospectively reviewed and documented. Based on the above three categories of critical, severe, and nonsevere, we cross-tabulated various biomarkers. The outcome of the patients, i.e., alive or dead was noted and differences of these biomarkers among the two groups were compared. For receiver operating characteristic (ROC) analysis, the severity was classified into nonsevere and severe to critical categories.

Statistical analysis

The data were collected, compiled, and analyzed using a statistical package for social sciences (SPSS, IBM, Version 20.0). The qualitative variables were expressed in terms of percentages. The normality of the data was tested using the Kolmogorov–Smirnov test. The quantitative variables were expressed in terms of mean and standard deviations for normal data and terms of median and interquartile range in nonnormal data. The difference between means of more than two groups was tested using the Wilcoxon rank-sum test. The difference between the two proportions was analyzed using Chi-square or Fisher's exact test. Predictive analysis for different blood parameters was done using ROC analysis. All analysis was two-tailed and the significance level was set at 0.05.

Results

A total of 243 patients with COVID 19 infection were evaluated in the present study. The demographic data of the present sample is shown in [Table 1]. The mean age of the cases was 53.85 ± 15.44 years with male preponderance. About 11.52% had diabetes, 16.87% had hypertension and 2.47% had ischemic heart disease.{Table 1}

The distribution of various markers based on the severity of the disease is elaborated in [Table 2]. The median serum ferritin levels among nonsevere cases, severe, and critical cases were 187.95 ng/mL (IQR = 93.05 ng/mL to 382.50 ng/mL), 230 ng/mL (156 ng/mL to 670 ng/mL) and 412.33 ng/mL (234 ng/mL to 689 ng/mL) respectively and this difference was statistically significant (P < 0.001). The average values of other markers such as LDH, CRP, D-Dimer, IL-6, procalcitonin, and total leukocyte count were highest in severe cases, followed by moderate cases and least in mild cases.{Table 2}

The distribution of various markers based on mortality is illustrated in [Table 3]. The average values of IL-6 were significantly higher among the patients who died (19.12 pg/mL) when compared to those who were alive (3.74 pg/mL). Other markers did not yield statistically significant differences in the present sample.{Table 3}

ROC analysis of various markers for severity of COVID-19 infection is explained in [Figure 1]. Based on the ROC analysis, the evaluation of levels of serum ferritin (Area under curve [AUC] = 0.755 (95% confidence interval [CI] = 0.635–0.875; P = 0.001]) was found to be an excellent test for differentiating nonsevere and severe to critical cases of COVID-19. Other markers such as procalcitonin (AUC = 0.706 [95% CI = 0.597–0.815; P = 0.010]), D-dimer (AUC = 0.697 [95% CI = 0.561–0.834; P = 0.014]) were fair tests to interpret the severity of disease.{Figure 1}

Discussion

Most COVID-19 patients have relatively mild symptoms, but many progress to severe pneumonia and eventually develop ARDS, septic shock, and ultimately multiple organ failure. Over-expression of the cytokines in these patients appeared clinically as short-term progressive aggravation of the disease called “inflammatory storms.”^[6] Therefore, it is of great significance to study the biochemical and inflammatory markers in COVID 19 patients for timely diagnosis, optimal treatment, delaying or halting disease progression, and reducing mortality. With the increase in the number of cases, evidence on IL-6, CRP, LDH, TLC, serum ferritin, D-Dimer, and procalcitonin in predicting the severity of the disease was on the rise. Various authors had highlighted the importance of individual markers in their studies.^{[7],[8],[9],[10]}

The present study analyzed the data of inflammatory markers of COVID 19 infected patients admitted to the hospital. As the severity of the disease increased from nonsevere to critical, the average values of all the markers increased significantly. Zhou et al.,^[11] reported that the median levels of serum ferritin in nonsevere cases were 291.13 ng/ml, and among severe cases, it was 1006.16 ng/ml. Another study conducted by Mehta et al.^[12] was consistent with these study findings. Lin et al.^[10] studied the various biomarkers in predicting the severity of COVID-19 infection and found that the serum ferritin levels were consistently high among severe cases compared to nonsevere cases. Few other studies were in agreement with our study findings.^{[13],[14],[15],[16]} Based on the ROC analysis, serum ferritin (AUC = 0.755 [95% CI = 0.635–0.875; P = 0.001]) was inferred as the best marker differentiating nonsevere and severe to critical cases in the present study. Gong et al.^[17] reported that the average values of serum ferritin levels increased significantly as the severity of the disease increased (AUC = 0.814, P < 0.001). Serum ferritin is one of the important mediators of immune dysregulation. Another study conducted ROC analysis on serum ferritin levels in predicting the severity of pneumonia and found that it was a fair test^[18] (AUC = 0.767; P < 0001). Hyperferritinemia is a condition in which there is significant activation of macrophages via direct immune-suppressive and pro-inflammatory effects. Hyperferritinemia is the basis of cytokine storm and worsening of infections like COVID-19.^[7],[19] Thus, serum ferritin can be used as a marker for the severity of COVID 19 infection and a target for various therapeutic interventions in clinical practice. Among all the markers studied in the present study, IL-6 was the only marker that was significantly increased in the patients with mortality. Similar findings were reported by many other authors in their studies.^{[16],[20],[21],[22],[23],[24],[25]} IL-6 is an acute phase reactant that is released in response to infections and tissue injuries. This marker is closely associated with the viral load of COVID-19 infection.^[26] The primary mechanism postulated its attribution to mortality is the excessive release of cytokines leading to pulmonary injury.^[27]

This study had some limitations. First, it was a retrospective analysis and an observational study. Longitudinal prospective studies should be planned to understand the serial changes of different parameters. Second, it was a single-center study; multicentric studies would have yielded precise results. Nonetheless, this is one of the studies that has considered all the necessary markers and reported the best marker in a tertiary care setup in India.

Conclusions

The average values of various biomarkers studied based on the severity of COVID-19 infection in the present study were highest in critical cases and least in nonsevere cases. Serum ferritin among our biomarker panel studied was the best test that predicted the severity of COVID-19 infection. The IL-6 levels were significantly higher among the patients who succumbed when compared to those who survived the disease. The estimation of serum ferritin among COVID-19 patients seems to be a promising marker to assess the severity at the best. Targeting this marker would aid the clinicians in prognosticating and early prevention of complications of COVID-19 infection.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

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