|Year : 2022 | Volume
| Issue : 2 | Page : 168-172
Correlation of biomarkers and radiological findings among COVID-19 patients: a retrospective study
Subbarao Anil Kumar1, Karthik Shyam2, Shruthi Kulkarni1
1 Department of General Medicine, St Johns Medical College Hospital, Bangalore 560034, Karnataka, India
2 Department of Radiology, St Johns Medical College Hospital, Bangalore 560034, Karnataka, India
|Date of Submission||13-Jan-2022|
|Date of Acceptance||25-Apr-2022|
|Date of Web Publication||17-Jun-2022|
Dr. Shruthi Kulkarni
Department of General Medicine, St Johns Medical College Hospital, Bangalore 560034, Karnataka
Source of Support: None, Conflict of Interest: None
Introduction: The severity of COVID-19 is classified based on clinical, laboratory, and radiology characteristics. Although chest X-ray (CXR) is not sensitive in early stage disease, it can be useful in assessing the rapid progression of lung abnormalities in COVID-19. While CXR findings correlate with the severity of the disease, computed tomography (CT) scans of the chest are widely and repeatedly done. As it exposes the patient to a large dose of radiation and risks the spread of infection to other patients, it is worthwhile to explore the utility of CXR to overcome the above problem, especially in resource-poor settings. Materials and Methods: Inpatients with reverse transcriptase–polymerase chain reaction (RT-PCR)-positive COVID-19 irrespective of severity, admitted in the COVID wards from June to September 2020, were included in a retrospective study. CXR done at admission was scored for radiological severity of COVID-19 by an independent radiologist, unaware of the clinical/laboratory parameters of patients. It was then co-related with clinical severity and standard biomarkers at admission. Results: We studied 400 patients, the mean age (SD) was 53.69 (15.43) years, 268 (67%) were males, the majority of them were symptomatic (95%), 192 (48%) had severe disease, and 238 (59.5%) patients had co-morbidities. Receiver-operating curve (ROC) for CXR severity score showed a threshold of 3.5 to predict severe COVID, which had a positive predictive value of 71% and a negative predictive value of 73%. Using Pearson’s correlation coefficient, CXR severity scores significantly correlated with the clinical severity and standard biomarkers. Conclusion: With the overwhelming number of COVID-19 patients burdening the healthcare system, monitoring of the severity of the disease can be achieved with regular clinical assessment and laboratory parameters with limited radiation exposure, avoiding repeated CT scans, especially in resource-poor settings.
Keywords: Biomarkers, chest X-ray score, COVID-19, severity of COVID-19
|How to cite this article:|
Kumar SA, Shyam K, Kulkarni S. Correlation of biomarkers and radiological findings among COVID-19 patients: a retrospective study. MGM J Med Sci 2022;9:168-72
|How to cite this URL:|
Kumar SA, Shyam K, Kulkarni S. Correlation of biomarkers and radiological findings among COVID-19 patients: a retrospective study. MGM J Med Sci [serial online] 2022 [cited 2022 Jul 6];9:168-72. Available from: http://www.mgmjms.com/text.asp?2022/9/2/168/347689
| Introduction|| |
Chest X-ray (CXR) is the primary imaging modality used in the evaluation of acute respiratory illness. It also plays an important role in the follow-up of an illness during and after treatment., However, CXRs have a low sensitivity in patients diagnosed with COVID-19 pneumonia, which can be strengthened by combining the imaging modality with laboratory and clinical data.,,
The biomarkers represent a candidate for risk stratification models for predicting severe COVID-19 and guiding clinical care. Among all, lymphopenia, C-reactive protein (CRP), lactate dehydrogenase (LDH), and D-dimer represent the most predictive parameters of severe COVID-19. The levels of biomarkers may change according to the severity of COVID-19 infection. This can be used as an adjunct in clinical practice to guide treatment and admission to the intensive care unit (ICU).
There is a wide spectrum of chest imaging abnormalities described in COVID-19 patients ranging from ground glass, focal consolidation, and nodular and interstitial opacities. The different patterns of chest imaging may show during illness.
Although CXR is considered not sensitive for the detection of pulmonary involvement in early stage disease, it can be used in routine ward settings for monitoring the rapid progression of lung abnormalities in COVID-19., The CXR scoring system designed and validated by Borghesi et al. is meant exclusively for a semi-quantitative assessment of severity and progression of pulmonary involvement in hospitalized patients with COVID-19.
There is not enough information regarding the association of CXR scoring with clinical and laboratory data. This study explores whether monitoring of COVID-19 disease severity can be achieved with regular clinical assessment, laboratory parameters, and CXRs as and when required with limited exposure to radiation through computed tomography (CT) scans in resource-poor settings.
| Materials and methods|| |
A retrospective study of 400 laboratory-confirmed COVID-19 inpatients was conducted in a tertiary care hospital in south India, to determine the correlation among clinical severity, standard biomarkers, and CXR severity score.
Laboratory-confirmed COVID-19 inpatients admitted in the COVID-19-designated wards in the hospital, irrespective of the severity, were included in the study. COVID-19-confirmed patients with an alternate diagnosis for the CXR findings were excluded from the study. The study was approved by the Institutional Ethics Committee (IEC No.277/2020). Waiver of consent was obtained. The clinical case records of patients admitted to COVID-19 wards were retrieved from the medical records department.
We screened 824 charts over 6 months and selected 400 charts that had all parameters captured. Demographic data, medical history, examination findings, laboratory reports, and COVID-19 severity at admission were recorded. The clinical findings of those patients who presented directly to the emergency were noted, and after verifying the same in the ward, the admission severity of COVID was made. The first CXR done, either at emergency or immediately after admission to the ward, was taken for severity scoring. The severity of COVID-19 was classified as mild, moderate, or severe as per Ministry of Health and Family Welfare Guidelines, Government of India.
The laboratory parameters collected at admission included complete blood count (CBC), CRP, LDH, D-dimer, and ferritin. Laboratory-specific cut-offs were used to label the value as elevated. The CXR of the patients, at admission, was accessed from the Institutional Picture Archiving and Communication System (PACS). The CXR was reported and scored by an independent radiologist unaware of the clinical status/laboratory parameters of patients.
Chest X-ray scoring system
We divided the lung fields into three zones and each zone was labeled A to F. Upper zones were labeled A/D, above the aortic arch; middle zones B/E, below the aortic arch to the hilum; and lower zones C/F, below the hilum to the bases. The zones were scored 0 to 3 based on the abnormality detected: score 0 no abnormality, score 1 interstitial infiltrates, score 2 interstitial and alveolar infiltrates with interstitial predominance, score 3 interstitial and alveolar infiltrates with alveolar predominance. By adding the scores from all zones, a cumulative CXR score was obtained which ranged from 0 to 18.
Descriptive data are represented as percentages and frequencies. Correlation between biomarkers and CXR scoring is analyzed using Pearson’s correlation coefficient. Receiver-operating curve (ROC) is constructed to get a specificity cut-off value for the CXR scoring. P < 0.05 is considered statistically significant. Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 17 for Windows.
| Results|| |
A total of 400 patient-data were analyzed [Table 1]. The overall mean age (SD) of the patients in the study was 53.69 (15.43). Of the 400 patients, 268 (67%) were male, the majority of them were symptomatic (95%), 192 (48%) had severe disease, and 238 (59.5%) patients had co-morbidities. More than half of the patients presented with fever (58%) and cough (52%).
Of the 238 patients with co-morbidities, 121 patients (63%) had severe disease. Overall, diabetes mellitus (45.5%) and hypertension (40.5%) were the most common comorbidities with nearly 50% of them having severe disease.
The majority of them, 230 out of 400 patients (57.5%), had less than 10 days of hospitalization, and 40 (10%) patients stayed up to 30 days in the hospital. Death was reported in 3 patients in the COVID ward and in 65 patients who needed escalation to ICU care from the COVID ward.
We analyzed CRP, LDH, D-dimer, and ferritin as the standard inflammatory biomarkers [Table 2]. Out of the 400 patients, 374 patients had CRP at admission. Overall median CRP with interquartile range (IQR) was 6.83 (1.93–15.56). D-dimer was available in 387 patients. Overall median D-dimer with IQR was 519 (282–901). LDH and ferritin were tested in 347 and 340 patients, respectively.
Out of 400 patients, 394 patients had CXRs done at admission, out of which 112 were normal. The overall median CXR score was 3.0 (0.0–7.0). The CXR scores significantly increased with the disease severity (P-value<0.001).
The median value of each of the biomarkers significantly correlated with the median CXR score, P < 0.001 for CRP, LDH, and ferritin and P < 0.007 for D-dimer [Table 3]. ROC of CXR score [area under the curve with 95% confidence interval (CI) 0.77 (0.73–0.82)] to differentiate severe disease from mild–moderate disease showed a threshold score of 3.5. The positive predictive value (PPV) at this CXR score was 71% and the negative predictive value (NPV) was 73% [Figure 1]. The median (IQR) D-dimer, LDH, CRP, and ferritin values at the CXR threshold score of 3.5 was 717 (451, 1039), 538.5 (386, 654), 11.8 (5.56, 22.2), and 582 (300, 1330), respectively.
|Figure 1: Sensitivity and specificity of chest X-ray in COVID-19 (threshold score, 3.5; positive predictive value, 0.71 (0.64, 0.78); negative predictive value, 0.73 (0.66, 0.79))|
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| Discussion|| |
The mean age of the study population was around 54 years, similar to other studies., There was a male preponderance, likely because of increased exposure. Ninety-five percent of the total patients were symptomatic, nearly half of them had severe disease (48%), and fever and cough were the most common symptoms as seen in studies done in urban tertiary care centers., Close to 60% had co-morbidities, with most of them having type 2 diabetes mellitus and hypertension. A similar finding was reported by Bhandari et al. and other studies.,, Mean duration of hospital stay increased significantly with the severity of the disease (P-value <0.001). Liu et al. also reported a similar association.
There was a significant association between each of the biomarkers and the clinical severity of the disease with the increasing association as the disease severity progressed (P < 0.001). In a study done by Huang et al. in China, it was found that the mean D-dimer and LDH were significantly higher among those admitted to ICU with severe disease when compared with those admitted to general wards with mild disease (P < 0.05). In a study by Liu et al., CRP, LDH, and D-dimer were elevated in 69 patients who had severe disease and correlated with the disease severity (P < 0.001). In our study, out of the 288 (72%) abnormal CXRs scored for severity of disease, there was a significant correlation between each median biomarker and the median CXR severity score (P-value <0.001). This finding is similar to the results of the study by Monaco et al., where median CXR score had a significant positive correlation with LDH (ρ = 0.308, P < 0.001) and CRP (ρ = 0.367, P < 0.001). Another study done by Gatti et al. showed that CXR severity scores positively correlated with higher CRP levels and LDH. Rorat et al. compared CRP, D-dimer, ferritin, and LDH with CXR severity scores and found a statistically significant association between the inflammatory markers and the severity score, which is similar to the findings in our study. A significant association was found between the severity of disease and median X-ray score, with a higher score indicating a more severe disease. Yasin and Gouda found that patients with a higher mean CXR severity score (6.87 ± 0.71) had a poor outcome which was statistically significant.
The threshold cut-off score of 3.5 on CXR differentiated severe disease from mild–moderate disease with PPV and NPV of 71% and 73%, respectively. Toussie et al. concluded that a CXR severity score of 3 or greater was found to be an independent risk factor for intubation (adjusted odds ratio: 4.7; 95% CI: 1.8, 13; P = 0.002). Kaleemi et al. demonstrated that a CXR severity score of 5–8 was associated with a higher incidence of intubation, which indirectly indicates the severity of the disease.
As CXR is easily accessible, cheap, and has less radiation exposure with a good PPV and significant correlation with severity of disease and biomarkers, it can be used alone to categorize the clinical severity of the patient and for routine monitoring in clinical wards, in a resource-poor setting, in which a CT scan might not be available or affordable. Also, in tertiary care hospitals and ICUs, CXRs can be repeated frequently during the illness to look for progression of the disease, which is not feasible with CT scans.
Our study also shows that all biomarkers equally and significantly correlate with the severity of the disease and CXR score done at admission. Hence, it may be useful to utilize the available biomarker assay for assessing disease severity and prognosis than doing multiple panels in a resource-poor setting. Limitation of the study includes the lack of follow-up of patients for their outcomes and looking for the correlation between biomarkers and CXR score at discharge, even though radiological clearing of abnormalities takes a longer time when compared with clinical improvement and rapid decrease in inflammatory markers with the recovery of inflammation. We need a follow-up study to ascertain the same conclusions for outcomes and use of CXR severity score to predict clinical course in-hospital.
| Conclusion|| |
With the overwhelming number of COVID-19 patients burdening the healthcare system, CXR scores along with a regular assessment of clinical and laboratory parameters can be used for routine monitoring for progression of disease severity, avoiding repeated CT scans, especially in resource-poor settings.
Research quality and ethics statement
All authors of this manuscript declare that this scientific study complies with standard reporting guidelines set forth by the EQUATOR Network. The authors ratify that this study required Institutional Review Board/Ethics Committee review, and hence prior approval was obtained (IRB Min. No. 277/2020 dated October 9, 2020). We also declare that we did not plagiarize the contents of this manuscript and have performed a Plagiarism Check.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]