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 Table of Contents  
ORIGINAL ARTICLE
Year : 2022  |  Volume : 9  |  Issue : 2  |  Page : 47-51

Role of chest radiography in COVID-19: A retrospective observational study in a tertiary care hospital in Southern India


Department of Pulmonary Medicine, NRI Institute of Medical Sciences, Visakhapatnam, Andhra Pradesh, India

Date of Submission27-Jan-2022
Date of Acceptance18-Jun-2022
Date of Web Publication8-Nov-2022

Correspondence Address:
Badusha Mohammad
Department of Pulmonary Medicine, NRI Institute of Medical Sciences, Anil Neerukonda Hospital, Sangivalasa, Andhra Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/RID.RID_11_22

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  Abstract 


OBJECTIVES: The objective of this study is to evaluate the clinical profile of coronavirus disease-2019 (COVID-19) patients admitted to our hospital and to correlate their chest radiographic patterns with disease severity.
MATERIALS AND METHODS: We retrospectively reviewed 500 patients with COVID-19 confirmed by reverse transcription-polymerase chain reaction who had abnormal baseline chest X-rays (CXRs) at the time of hospital admission. CXRs were characterized based on the site and nature of the lesions. Disease severity was determined using the Radiographic Assessment of Lung Edema (RALE) score.
RESULTS: Significant associations were found between (1) the lesion site and patient outcome (P < 0.00001): patients with diffuse and basal infiltrates had high intensive care unit (ICU) admission rates (55.5% and 40%) and mortality rates (30.5% and 20%); (2) the nature of the lesion and patient outcome: patients with ground-glass opacities and consolidation had high mortality (20% and 18%, respectively); and (3) the RALE score and patient outcome: patients with a RALE score >15 had higher ICU admission and mortality rates.
CONCLUSIONS: The CXR distribution patterns helped to triage patients and predict outcomes.

Keywords: Chest X-ray, coronavirus disease-2019, Radiographic Assessment of Lung Edema score


How to cite this article:
Mohammad B, Nandimandalam N, Yerramsetti S, Penumetcha S, Bathula BP. Role of chest radiography in COVID-19: A retrospective observational study in a tertiary care hospital in Southern India. Radiol Infect Dis 2022;9:47-51

How to cite this URL:
Mohammad B, Nandimandalam N, Yerramsetti S, Penumetcha S, Bathula BP. Role of chest radiography in COVID-19: A retrospective observational study in a tertiary care hospital in Southern India. Radiol Infect Dis [serial online] 2022 [cited 2022 Dec 4];9:47-51. Available from: http://www.ridiseases.org/text.asp?2022/9/2/47/360501




  Introduction Top


Coronavirus disease-2019 (COVID-19) is caused by infection with a novel coronavirus. It often results in disease of the lower respiratory tract and can be fatal.[1] Chest X-ray (CXR) is the first-line imaging used in the management of COVID-19 patients.[2],[3],[4] In severe acute respiratory syndrome, CXR radiographic scores were used to determine disease severity, and they were well correlated with the degree of hypoxia.[5] The Radiographic Assessment of Lung Edema (RALE) score has been used to measure the severity of acute respiratory distress syndrome.[6] Our study aimed to correlate the CXR findings with disease severity in COVID-19 patients.


  Materials and Methods Top


Patient selection and inclusion criteria

This was a retrospective cross-sectional study of 500 patients with COVID-19 confirmed by reverse transcription-polymerase chain reaction (RT-PCR) and who had abnormal baseline CXRs at the time of admission. The study was approved by the Institutional Ethics Committee. All participants provided informed consent. The CXR findings were correlated with the following outcomes: the need for admission to the intensive care unit (ICU) or ward, the RALE score, and mortality.

Inclusion criteria

(1) Patients with RT-PCR-confirmed COVID-19; (2) age >18 years; and (3) patients who had CXR abnormalities at the time of admission. Exclusion criteria: (1) patients who did not consent to inclusion in the study; and (2) patients with comorbidities. The ICU admission criteria were any one of the following:[7] (1) hemodynamically unstable; (2) SpO2 <90% without supplemental oxygen; (3) respiratory rate >30/min; and (4) severely increased inflammatory markers (C-reactive protein >50 mg/L and D-dimer >1000 ng/ml). The COVID-19 ward admission criteria were any one of the following:[7] (1) hemodynamically stable; (2) SpO2 >90% but <94%; (3) respiratory rate >24 but <30/min; and (4) increased inflammatory markers (10–50 mg/L C-reactive protein and 500–1000 ng/ml D-dimer).

Study period

The retrospective study period was 1 year, from July 1, 2020, to June 30, 2021. The study took place at Anil Neerukonda Hospital, a COVID-19 referral center in Visakhapatnam, Andhra Pradesh, India.

Image acquisition and analysis

CXR-posteroanterior or CXR-anterior-posterior images were acquired using an AGFA × 30. The CXR findings were described by (1) unilateral or bilateral involvement of the lung; (2) the site of the lesion: opacities in lateral aspects of the CXR indicated peripheral distribution, opacities in the lung base indicated basal distribution, opacities in the lung base together with a lateral distribution indicated peripheral plus basal distribution, and involvement of all lung fields indicated diffuse distribution; and (3) the nature of the lesions, classified as consolidation, ground-glass opacities (GGOs), nodular, or reticulonodular.[8]

Radiographic scoring

To quantify the extent of infection, a severity score was calculated by adapting and simplifying the RALE score proposed by Warren et al.[9] After the RALE scoring, each CXR was given a score between 0 and 48.

Radiographic Assessment of Lung Edema score

A significant association was observed between the extent of lung involvement and the RALE score (P < 0.00001). Patients with higher RALE scores (>15) had bilateral lung involvement [Table 3]. Similarly, a significant association was found between the lesion site and the RALE score. Because the RALE score is based on the number of lung quadrants involved, patients with diffuse lesions had higher RALE scores (83.3%). By contrast, the majority of patients with peripheral lesions had lower RALE scores (85.7%) [Table 4].
Table 3: Association between Radiographic Assessment of Lung Edema score and lung involvement (n = 500)

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Table 4: Comparison of the Radiographic Assessment of Lung Edema score and the lesion distribution (n=500)

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Compared with the initial X-rays, the RALE score improved in subsequent X-rays after the patient had received appropriate treatment. Improvement was more prominent in patients with peripheral lung involvement compared with those who had diffuse lung lesions (85.7% vs. 69.4%) [Table 5].
Table 5: Site of lesions and the Radiographic Assessment of Lung Edema score based on the subsequent chest X-ray

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A comparison of the RALE score from the first and subsequent X-rays was found to be statistically significant (P < 0.00001), thus establishing its importance for patient prognosis. Sixty-three percent of patients (155/245) with an initial RALE score >15 improved with treatment, whereas none of the patients with a RALE score <15 deteriorated [Table 6].
Table 6: X-ray versus Radiographic Assessment of Lung Edema score

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Statistical analysis

The patient data were tabulated in Microsoft Excel and analyzed using IBM SPSS version 21 (IBM Corp., Aramark, USA). Descriptive analyses were conducted to obtain percentages, and inferential analyses were conducted using the Chi-square test to quantify the association between the variables.


  Results Top


Patient characteristics

A total of 500 patients were included in the study (305 men and 195 women). The median age was 53.8 years. A total of 184 patients survived in the ICU, whereas 270 survived in the ward. There were 86 fatalities.

Chest X-ray findings

All patients underwent CXR at the time of presentation. Consolidation (250/500) was the most common CXR pattern, followed by GGOs (175/500) and reticulonodular (60/500) and nodular patterns (15/500). Regarding the site of lesions, the peripheral plus basal distribution (235/500) was most common, followed by diffuse (180/500), basal (50/500), and peripheral (35/500) distributions [Table 1] and [Table 2].
Table 1: Association between lesion site and patient outcomes (n=500)

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Table 2: Association between nature of X-ray lesions and patient outcomes (n=500)

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A significant association was found between lesion site and patient outcome (P < 0.00001) [Table 1] and [Figure 1]a, [Figure 1]b, [Figure 1]c. Patients with diffuse lesions on the CXR had increased rates of mortality (30.5%) and ICU admission (55.5%). A significant association was also found between the nature of the lung lesions and the outcome (P < 0.00002) [Table 2] and [Figure 2]a, [Figure 2]b, [Figure 2]c, [Figure 2]d, [Figure 2]e. Patients with GGOs had the highest rates of ICU admission (45.7%) and mortality (20%).
Figure 1: (a) Peripheral distribution of opacities; Yellow arrow – peripheral, Outcome: Patient survived; (b) Peripheral plus basal opacities with central sparing; Yellow arrow – peripheral, Red arrow – basal, Outcome: Patient survived; (c) Basal distribution of opacities, Red arrow – basal, nature of lesion: GGOs, Outcome: Patient died. GGOs: Ground-glass opacities

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Figure 2: (a) Red arrow – reticular strands, Yellow arrow – nodules, Outcome: Patient survived; (b) Nodular with basal distribution; Yellow arrow – basal nodule, Outcome: Patient survived; (c) Right multilobar consolidation; Yellow arrow – Opacity with air bronchogram, Outcome: Patient survived; (d) Bilateral diffuse GGOs predominant on right side, Outcome: Patient died; (e) Reticular pattern with consolidation (predominantly reticular); Red arrow – reticular, Yellow arrow – consolidation. Outcome: Patient survived

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Prognostic value of chest X-ray

The mortality of patients significantly depended on the extent of lung involvement. In patients with bilateral involvement of the lung, there was high mortality (19.04%), which was two-fold greater than in patients with unilateral lung involvement (9.09%). Similarly, more than three times as many patients with bilateral lung lesions required ICU admission compared with those with unilateral lesions (43% vs. 12.7%) [Table 7].
Table 7: Association between lung involvement and patient outcome (n = 500)

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Regarding the final outcome, 414 of the 500 patients recovered, and 86 died. The median age of our study population was 53.8 years. Of the 86 deaths, 56 were >53.8 years and 30 were <53.8 years [Table 8].
Table 8: Outcome of the 500 patients included in the study

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  Discussion Top


The burden of the COVID-19 pandemic on health-care institutions has highlighted the need for a simple tool such as CXR to help prioritize patient management and predict outcomes.[5] CXR plays an important role in the management of COVID-19 patients owing to its availability and ease of use, especially in countries with a large population and a high COVID-19 burden, such as India.

Cozzi et al. found that the sensitivity of chest radiography makes it a reasonable tool for guiding patient management.[6] Here, we found that CXR patterns helped to triage patients and predict prognosis. This finding was based on our observation that patients with bilateral involvement with diffuse GGOs had a worse prognosis and a greater need for ICU admission. By contrast, patients with peripheral and nodular or reticulonodular lesions had a better prognosis, and most were treated in wards [Table 1] and [Table 2].

Patients with chest radiographs showing diffuse or basal distributions had higher RALE scores than patients with CXRs showing peripheral or peripheral plus basal distributions [Table 4].

We also observed that the results of a subsequent CXR correlated well with the improvement of lesions. A decrease in the RALE score is a sign of improvement because the RALE score takes into account the number of lung quadrants with lesions. Subsequent CXRs after treatment showed a 31% increase in the number of patients with a RALE score <15 (RALE score <15: 51% on admission vs. 82% posttreatment).

We also observed an increased rate of ICU admission in patients with GGOs (45.7%) and consolidations (35.2%) compared with those with reticulonodular (25%) and nodular (6.6%) opacities. This trend was also seen in the mortality rates of these groups (20% and 18% vs. 8.3% and 6.6%). A considerable effect of age on mortality was also observed in our study. Patients older than the median (53.8 years) had a higher percentage of mortality compared with those younger than this age. As our study excluded patients with comorbidities, a possible explanation for the increased mortality in patients aged 53 and over is the increased susceptibility to infection and a reduced ability to recover after infection.[10],[11]

Many computed tomography (CT) findings, such as bilateral involvement, peripheral distribution, and lower zone predominance, can also be observed on CXRs.[1],[5],[12],[13] A major limitation of our study was the unavailability of CT images for all patients owing to the pandemic nature of COVID-19 during which there was extensive depletion of health-care resources. Therefore, a comparison between CXR and CT was not explored in our study.[14]


  Conclusions Top


We found that CXR distribution patterns helped to triage COVID-19 patients and aided in patient prognosis.[15] Therefore, based on the initial CXR patterns, additional monitoring and treatment should be conducted for a subgroup of patients. The mortality rate was higher in patients older than 53.8 years (median age) and in those presenting with a diffuse CXR pattern with a RALE score >15. The RALE score can also be used in the emergency setting to help triage patients and select their required level of care, namely ICU or ward. This score can also be used to predict patient prognosis.

Acknowledgment

We thank Katherine Thieltges from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing the English text of a draft of this manuscript.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Martínez Chamorro E, Díez Tascón A, Ibáñez Sanz L, Ossaba Vélez S, Borruel Nacenta S. Radiologic diagnosis of patients with COVID-19. Radiologia (Engl Ed) 2021;63:56-73.  Back to cited text no. 2
    
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Rubin GD, Ryerson CJ, Haramati LB, Sverzellati N, Kanne JP, Raoof S, et al. The role of chest imaging in patient management during the COVID-19 pandemic: A multinational consensus statement from the Fleischner Society. Chest 2020;158:106-16.  Back to cited text no. 3
    
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American College of Radiology. ACR Recommendations for the Use of Chest Radiography and Computed Tomography (CT) for Suspected COVID-19 Infection; March 11, 2020. Available from: https://www.acr.org/Advocacy-and-Economics/ACR-Position-Statements/Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID-19-Infection. [Last accessed on 2022 Jan 12].  Back to cited text no. 4
    
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Cozzi D, Albanesi M, Cavigli E, Moroni C, Bindi A, Luvarà S, et al. Chest X-ray in new Coronavirus Disease 2019 (COVID-19) infection: Findings and correlation with clinical outcome. Radiol Med 2020;125:730-7.  Back to cited text no. 6
    
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Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J. Fleischner Society: Glossary of terms for thoracic imaging. Radiology 2008;246:697-722.  Back to cited text no. 8
    
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Warren MA, Zhao Z, Koyama T, Bastarache JA, Shaver CM, Semler MW, et al. Severity scoring of lung oedema on the chest radiograph is associated with clinical outcomes in ARDS. Thorax 2018;73:840-6.  Back to cited text no. 9
    
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Bonanad C, García-Blas S, Tarazona-Santabalbina F, Sanchis J, Bertomeu-González V, Fácila L, et al. The effect of age on mortality in patients with COVID-19: A meta-analysis with 611,583 subjects. J Am Med Dir Assoc 2020;21:915-8.  Back to cited text no. 10
    
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Ng MY, Lee EY, Yang J, Yang F, Li X, Wang H, et al. Imaging profile of the COVID-19 infection: Radiologic findings and literature review. Radiol Cardiothorac Imaging 2020;2:e200034.  Back to cited text no. 13
    
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Yang W, Sirajuddin A, Zhang X, Liu G, Teng Z, Zhao S, et al. The role of imaging in 2019 novel coronavirus pneumonia (COVID-19). Eur Radiol 2020;30:4874-82.  Back to cited text no. 14
    
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    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8]



 

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