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ORIGINAL ARTICLE
Year : 2021 | Volume
: 46
| Issue : 3 | Page : 143-150
Laboratory tests: a rapid tool for grading corona virus disease 2019 patients into different severity groups
Mariam K Youssef MD 1, Sara F Samaan2, Sara I.A. Taha1
1 Department of Clinical Pathology, Faculty of Medicine, Ain-Shams University, Cairo, Egypt
2 Department of Internal Medicine, Faculty of Medicine, Ain-Shams University, Cairo, Egypt
Correspondence Address:
Mariam K Youssef
Department of Clinical Pathology, Faculty of Medicine, Ain-Shams University, Cairo
Egypt
Source of Support: None, Conflict of Interest: None
CheckDOI: 10.4103/ejh.ejh_27_21
Background The lack of awareness of COVID-19 severity in the early stages of the disease has led to a dramatic increase in the number of patients worldwide. A cost-effective, easily acquired biomarker is needed to classify disease severity at early stages.
Objective The objective of this paper is to explore the role of basic laboratory tests in the classification of COVID-19 patients into different severity groups.
Methods Socio-demographic data, including age and gender together with laboratory investigations, including complete blood count, CRP, serum D-dimer, ferritin, LDH, and liver function tests were collected during the period from November 2020 to January 2021 from the medical records of 100 adult COVID-19 patients admitted at the Quarantine Hospitals of Ain-Shams University.
Results The present study included 100 COVID-19 patients (51 females and 49 males) with a mean age of 57±15.74 years. They were 27 mild, 40 moderate, and 33 severe. The disease severity could not be linked to a specific gender; however, the severity increased with advanced age. CBC results showed no significant differences in total leucocytic counts, hemoglobin levels, or platelet counts; however, the absolute lymphocyte counts decreased significantly as the disease worsened. Also, in more severe disease, there was a highly significant increase in ferritin, D-dimer, LDH, and CRP levels with no significant differences in ferritin and LDH levels between moderate and severe groups. On the other hand, AST and ALT levels showed no significant differences between the three groups. Significant negative correlations were found between absolute lymphocyte count and ferritin, D-dimer, and CRP levels. By ROC curve, a cut-off point for absolute lymphocyte count of less than or equal to 1.5×103/cmm, D-dimer of greater than 0.78 mg/l, and CRP of greater than 56 mg/l were used to differentiate mild and moderate cases, and a cut-off point for absolute lymphocyte count of less than or equal to 1.06×03/cmm, D-dimer of greater than 1.58 mg/l, and CRP of greater than 78 mg/l were used to differentiate moderate and severe cases. Furthermore, the kappa statistic test found a moderate degree of agreement between the existing guideline for disease typing, and absolute lymphocyte count, D-dimer, and CRP levels.
Conclusion This study suggested that incorporation of laboratory variables including absolute lymphocyte count, D-dimer, and CRP into the existing guideline for disease typing, may be of value for quick cost-effective identification of potentially critically ill patients at an early stage of the disease.
Keywords: classification, corona virus disease 2019, laboratory tests, severity
Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) causing corona virus disease 2019 (COVID-19) has rapidly evolved from an epidemic outbreak in Wuhan, China into a pandemic spreading all over the world [1]. COVID-19 has a wide range of presentations varying from no or mild symptoms such as fever, dry cough, body aches, abdominal pain, and diarrhea to severe acute respiratory distress, metabolic acidosis, septic shock, coagulation dysfunction, and organ failure such as liver, kidney, and heart failure that could eventually end into death [2].
The classification of disease severity in COVID-19 is very important for the grading treatment of patients. In particular, with the relatively limited medical resources together with the outgrowing demand for intensive care, it is necessary to conduct grading severity and treatment, thereby prioritize the allocation of rescue resources and prevent the occurrence of over or under treatment [3].
Currently, the clinical condition of the patient together with pulmonary imaging is the main basis of disease classification. Although many blood tests are available for guiding treatment decisions and predicting prognosis in a time and cost-effective manner, none of the indicators in blood tests were included in the classification criteria of COVID-19 [3]. Therefore, the role of laboratory evaluation in the classification and grading of COVID-19 patients should be explored.
MethodsStudy design and participants
In this retrospective cohort study, the clinical data of 100 adult patients with laboratory-confirmed COVID-19 infection using reverse transcription-polymerase chain reaction (RT-PCR) were collected from the Quarantine Hospitals of the Ain-Shams University on admission from November 2020 to January 2021.
The study was carried out in compliance with the ethical guidelines established by the Research Ethics Committee (REC) of the Ain-Shams University, Faculty of Medicine, and was approved by the same committee.
Data collection
For all participants who agreed to be included in the study, socio-demographic data, including age and gender together with laboratory investigations, including complete blood count, CRP, serum D-dimer, ferritin, LDH, and liver function tests were collected from patients’ medical records and analyzed.
Definitions
According to the Ain Shams University Hospitals Consensus Statement on Management of Adult COVID-19 Patients, the patients were classified into three categories based on the severity of their disease.
Mild cases: asymptomatic with abnormal laboratory findings or symptomatic with no chest CT findings of COVID-19 pneumonia and no oxygen desaturation.
Moderate cases: symptomatic with clinical signs of non-severe pneumonia (e.g. fever, dyspnea, cough) and chest CT findings of COVID-19 pneumonia and/or abnormal laboratory findings with no oxygen desaturation.
Severe cases: clinical signs of severe pneumonia (e.g. respiratory rate greater than 30 breaths/min.; severe respiratory distress; or SpO2 less than 93% on room air) and chest CT findings of COVID-19 pneumonia.
Statistical analysis
The collected data were processed and coded before being analyzed using the IBM SPSS program (Statistical Package for Social Sciences) for Windows Version 20.0. Qualitative data were presented using frequencies and related percentages. Quantitative data were presented using means and standard deviations. An independent samples t-test or Mann–Whitney U test was used to compare the difference in parametric variables between two independent means of two groups. ANOVA or Kruskal–Wallis test was performed to compare quantitative variables among three categories. The chi-squared or Fisher’s exact test was performed for qualitative variables analysis. Pearson correlation coefficients were used to assess the association between two normally distributed variables. When a variable was not normally distributed, a Spearman correlation test was performed. Receiver operating characteristic (ROC) curve was used to set cut-off points between different studied groups. Cohen’s κ statistic was used to measure interrater reliability, it varies from 0 to 1 [0=agreement equivalent to chance, 0.1–0.20=slight agreement, 0.21–0.40=fair agreement, 0.41–0.60=moderate agreement, 0.61–0.80=substantial agreement, 0.81–0.99=near perfect agreement, 1=perfect agreement] [4]. In all tests, a P value of 0.05 or less and 0.01 or less was considered significant and highly significant, respectively.
ResultsThe present study included 100 patients with COVID-19 infection. They were 51 (51%) females and 49 (49%) males and their ages ranged from 15 to 94 years with a mean age of 57±15.74 years. According to their disease severity on admission to the hospital, they were classified into three groups as follows: mild (n=27), moderate (n=40), and severe (n=33). There were 12 (44.4%) females and 15 (55.6%) males in the mild group, 21 (52.5%) females and 19 (47.5%) males in the moderate group, 18 (54.5%) females, and 15 (45.5%) males in the severe group. The mean age was 50.93±19.95 years in the mild group, 56.10±13.46 years in the moderate group, and 63.06±12.33 years in the severe group. Meanwhile, the disease severity could not be linked to a specific gender, the severity increased with advanced age (P value = 0.01) ([Table 1]).
Table 1 Comparison between the three studied groups according to demographic dataOn comparing laboratory parameters in the three different groups, baseline CBC results showed no significant differences in total leucocytic counts (P value = 0.875), hemoglobin levels (P value = 0.393), or platelet counts (P value = 0.899). However, the absolute lymphocyte counts decreased significantly as the disease worsened (P value = 0.000) ([Table 2], [Figure 1]a).
Table 2 Comparison between the three studied groups according to baseline CBC
Figure 1 Comparison of laboratory parameters between the three studied groups.Also, in more severe disease there was a highly significant increase in ferritin (P value = 0.000) ([Figure 1]b), D-dimer (P value =0.000) ([Figure 1]c), LDH (P value = 0.005) ([Figure 1]d), and CRP (P value = 0.000) ([Figure 1]e) levels, with no significant differences in ferritin (P value = 0.065) and LDH (P value = 0.217) levels between moderate and severe groups. On the other hand, AST and ALT levels showed no significant differences between the three groups (P values=0.646 and 0.786, respectively) ([Table 3]).
Table 3 Comparison between the three studied groups according to other laboratory testsSignificant negative correlations ([Table 4]) were found between the baseline absolute lymphocyte count and ferritin (P value= 0.003) ([Figure 2]a), D-dimer (P value = 0.002) ([Figure 2]b), and CRP (P value = 0.007) ([Figure 2]c) levels.
Table 4 Correlation of absolute lymphocyte count with other laboratory tests in all studied cases
Figure 2 Correlation of absolute lymphocyte count with ferritin, D.dimer and CRP in all studied cases.By ROC curve, a cut-off point for absolute lymphocyte count of less than or equal to 1.5×03/cmm, D-dimer of greater than 0.78 mg/l, and CRP of greater than 56 mg/l, were used to differentiate mild and moderate cases, and a cut-off point for absolute lymphocyte count of less than or equal to 1.06×03/cmm, D-dimer of greater than 1.58 mg/l and CRP of greater than 78 mg/l, were used to differentiate moderate and severe cases ([Table 5] and [Table 6], [Figure 3] and [Figure 4]).
Table 5 ROC curve between mild and moderate groups regarding absolute lymphocyte count, D.dimer and CRP at baseline
Table 6 ROC curve between moderate and severe groups regarding absolute lymphocyte count, D.dimer and CRP at baseline
Figure 3 Receiver operating characteristic (ROC) curve of absolute lymphocyte count, D.dimer and CRP at baseline as predictors of mild to moderate groups.
Figure 4 ROC curve of absolute lymphocyte count, D.dimer, and CRP at baseline as predictors of moderate to severe groups.Furthermore, in order to verify the degree of consistency between the existing guideline in disease typing and the different laboratory variables related to the disease severity, we performed a kappa statistic test which found a moderate agreement between the existing guideline and; absolute lymphocyte count (P value<0.001), D-dimer (P value <0.001), and CRP (P value<0.001) levels ([Table 7]).
Table 7 Consistency between existing guideline and lymphocyte, D.dimer and CRP based disease classification Discussion Coronavirus disease 2019 is a major infectious disease that threatens people’s life due to its high incidence and high infectivity [5]. Although the majority of patients with coronavirus infection have been classified as mild cases that can recover shortly after the appropriate clinical intervention, the moderate type patients especially the elderly or the ones with co-morbidities can rapidly worsen and become severe with increasing rate of hospitalization and ICU admission, indicating high mortality rate [3].
The lack of awareness of disease severity in the early stages of COVID-19 coupled with the high infectivity of the virus has led to a dramatic increase in the number of patients with relatively high fatality rates worldwide. Rapid early identification of potential critical patients is important in the management of this disease to prioritize healthcare resources, which are under strain in practically all parts of the world. A cost-effective, easily acquired biomarker is needed to classify disease severity at early stages [6].
Currently, the grading of COVID-19 patients into different severity groups is dependent mainly on the clinical condition of the patient together with pulmonary imaging. In this study, we aimed to explore the role of basic laboratory tests in the classification of COVID-19 patients into different severity groups.
Our study included 100 COVID-19 patients (51 females and 49 males) recruited from Ain-Shams Quarantine Hospitals. Their ages ranged from 15 to 94 years with a mean age of 57±15.74 years. Based on the severity of their disease, they were classified into mild (n=27), moderate (n=40), and severe (n=33) cases according to the Ain-Shams University Hospitals Consensus Statement on Management of Adult COVID-19 Patients. We found a significant increase in disease severity with advanced age; however, the disease severity could not be linked to a specific gender. Similarly, Shang and coworkers found a significant increase in disease severity with advanced age, but contrary to us, they reported more severe disease in male patients.
In terms of laboratory tests, the main characteristics of COVID‐19 were normal or decreased the total number of white blood cells, decreased lymphocyte count, increased serum ferritin, increased D-dimer, increased CRP, and elevated liver function tests in some patients [5].
Regarding complete blood count in COVID-19, peripheral blood leukocyte and lymphocyte counts are found to be normal or slightly reduced during the incubation period ranging from 1 to 14 days, and during the early phase of the disease, when non-specific symptoms are present,. Approximately 7 to 14 days from the onset of the initial symptoms, there is a surge in the clinical manifestations of the disease coinciding with a pronounced systemic increase of inflammatory mediators and cytokines characterized as a “cytokine storm”; at this point, significant lymphopenia becomes evident [1]. Several factors may contribute to COVID-19 associated lymphopenia; (a) it has been shown that lymphocytes express the coronavirus receptor ACE2 on their surface; thus, the virus may directly infect lymphocytes ultimately leading to their lysis, (b) furthermore, the cytokine storm is characterized by markedly increased levels of interleukins which may promote lymphocyte apoptosis, (c) also, substantial cytokine activation may be also associated with atrophy of lymphoid organs, including the spleen, further impairing lymphocyte turnover, and (d) the severe type of COVID-19 patients had elevated blood lactic acid levels, which might suppress the proliferation of lymphocytes [3]. Lymphopenia has been recognized in many studies as an effective and reliable indicator of the severity and hospitalization in COVID-19 patients [1],[3]. In our studied patients, the absolute lymphocyte count decreased significantly with the increase in disease severity (P value: 0.000). In addition, by drawing a ROC curve, a cut-off point of less than or equal to 1.5×03/cmm is used to differentiate mild and moderate cases (AUC: 0.722, sensitivity: 80%, specificity: 62.96%, PPV: 76.2, NPV: 68.0), and a cut-off point of less than or equal to 1.06×03/cmm is used to differentiate moderate and severe cases (AUC: 0.692, sensitivity: 72.73%, specificity: 65.00%, PPV: 63.2, NPV: 74.3). In our study, no significant difference was found between the different severity groups and the total leucocytic count, hemoglobin level, and platelet count. In contrast to our study, Shang and colleagues have found a significant correlation between leucopenia and thrombocytopenia and disease severity in their studied patients, where they found a platelet optimal working point of 177×109/l to differentiate severe and non-severe patients. However, similar to us, they found that hemoglobin levels were not influenced by the severity of the disease.
It has been suggested that ferritin levels may be predictive of an imminent inflammatory reaction in COVID-19 and is associated with a viral spread in the human body. Hyperferritinemia activates macrophages to secrete cytokines, causing a cytokine storm; a sign of disease severity. This cytokine storm can be assessed by evaluating the serum ferritin levels. Ideally, serum ferritin levels might be a crucial factor influencing the severity of COVID-19 [7]. In our study, serum ferritin was significantly higher in the mild group of patients compared to the moderate group (P value: 0.000) with no significant difference in serum ferritin levels between the moderate and severe groups. Similarly, LDH was significantly higher in the mild group of patients compared to the moderate group (P value: 0.005) with no significant difference between the moderate and severe groups. Like our study, Brugu and coworkers found that ferritin level was significantly elevated as the disease severity increased. Also, Shang and colleagues reported higher LDH in the more severe COVID-19 patients.
Coagulation disorders are relatively frequently encountered among COVID-19 patients, especially among those with severe disease. The D-dimer dynamics can reflect disease severity and elevated D-dimer level is associated with adverse patients’ outcomes [1]. D-dimer levels in our studied patients increased significantly as the disease severity increased (P value: 0.000); and by drawing a ROC curve, a cut-off point of greater than 0.78 mg/l is used to differentiate mild and moderate cases (AUC: 0.902, sensitivity: 80%, specificity: 92.59%, PPV: 94.1, NPV: 75.8), and a cut-off point of greater than 1.58 mg/l is used to differentiate moderate and severe cases (AUC: 0.634, sensitivity: 60.61%, specificity: 72.5%, PPV: 64.5, NPV: 69).
CRP is a useful inflammatory marker that plays an important role in host resistance to invading pathogens and inflammation. CRP was highly correlated to the acute lung injury in COVID-19 infected patients. Also, higher CRP has been linked to unfavorable aspects of COVID‐19 diseases, such as cardiac injury, ARDS development, and death. Therefore, the detection of CRP levels in COVID‐19 patients is of great value in assessing the severity of their condition [5]. Our study showed that CRP increased significantly with the increase in disease severity (P value: 0.000), and by ROC curve analysis, a cut-off point of greater than 56 mg/l is used to differentiate mild and moderate cases (AUC: 0.794, sensitivity: 70%, specificity: 77.78%, PPV: 82.4, NPV:63.6), and a cut-off point of greater than 78 mg/l is used to differentiate moderate and severe cases (AUC: 0.644, sensitivity: 78.79, specificity: 52.5, PPV: 57.8, NPV: 75). Shang and colleagues reported a CRP optimal working point of greater than 38.5 mg/l to differentiate between severe and non-severe COVID-19 patients. Elevated serum liver aminotransferases in the context of COVID-19 could indicate a liver injury and/or multi-organ damage [8]. However, we could not find a significant increase in liver enzymes with the increase in disease severity in our patients.Finally, in order to verify the degree of consistency between the existing guideline used in disease typing and the different laboratory variables that were found to be significantly related to the disease severity in our study, we performed a kappa statistic test which found a moderate degree of agreement between the existing guideline and; absolute lymphocyte count (P value<0.001), D-dimer (P value <0.001) and CRP (P value <0.001) levels. One limitation in our study is the heterogeneity in the studied group of patients with a variable prevalence of co-morbidities that may have an impact on their disease condition and laboratory results. Further studies on a larger number of COVID-19 patients and their further division into more homogenous subgroups, are still required to improve the sensitivity and specificity of laboratory variables for proper disease typing. Also, prospective studies are required to discover the impact of disease dynamics on the different laboratory parameters.
In conclusion, our study suggested that incorporation of laboratory variables including; absolute lymphocyte count, D-dimer, and CRP into the existing guideline for disease typing, may be of value for quick cost-effective identification of potentially critically ill patients at an early stage of the disease for proper therapeutic intervention to allocate medical resources and avoid over or under treatment.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References
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