Predictive Formula for COVID-19 Consolidation: Clinical-HRCT Relationship

Muhammad Abdullah Mehar, Rehan Afsar, Waqar Mehmood Dar, Abid Ali

Abstract


Background:
COVID-19 pneumonia kills thousands of patients daily, requiring early detection and early intervention. Healthcare systems struggle with the overwhelming number of patients, necessitating an automated method for lung disease measurement in the early stages.
Objective:
To find the relationship between pulmonary HRCT findings and different clinical signs and symptoms of COVID-19 patients.
Methodology:
The study examined 113 COVID-19 patients in four months using a retrospective and cross-sectional approach. Three radiologists independently reviewed HRCT. Data was collected from both genders and age groups. Statistical analysis, such as cross tabulation, logistic regression, Chi-square, and Fisher’s exact test, was conducted using SPSS V23 software.
Results:
The study found 70% of patients were over 45 years old, with males being more susceptible to COVID-19. The study examined the relationship between fever, cough, fatigue, myalgia, anosmia, and ageusia with GGOs, consolidation, lung nodules, air bronchogram, crazy paving sign, and pleural effusion using crosstabulation and logistic regression. Results showed significant correlations between these symptoms and consolidation, with 83.2 % accuracy predicted.
Conclusion:
In conclusion, the current study revealed that ground glass opacities and consolidation are typical findings in COVID-19. Significant relationships were found between the primary clinical signs & symptoms and pulmonary HRCT findings. For the prediction of consolidation, the binary logistic regression model is exceptionally good from a clinical aspect.


Keywords


HRCTHRCT; Covid 19; Consolidation; GGO’s; Regression.

Full Text:

PDF

References


Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. 2020;395(10223):507-13.

Organization WH. Novel Coronavirus (2019-nCoV): situation report, 11. 2020.

Wu JT, Leung K, Leung GMJTL. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study. 2020;395(10225):689-97.

Mo P, Xing Y, Xiao Y, Deng L, Zhao Q, Wang H, et al. Clinical Characteristics of Refractory Coronavirus Disease 2019 in Wuhan, China. 2021;73(11):e4208-e13.

Vasireddy D, Vanaparthy R, Mohan G, Malayala SV, Atluri PJJoCMR. Review of COVID-19 variants and COVID-19 vaccine efficacy: what the clinician should know? 2021;13(6):317.

McBride O, Murphy J, Shevlin M, Gibson‐Miller J, Hartman TK, Hyland P, et al. Monitoring the psychological, social, and economic impact of the COVID‐19 pandemic in the population: Context, design and conduct of the longitudinal COVID‐19 psychological research consortium (C19PRC) study. 2021;30(1):e1861.

Kanne JPJR. Chest CT findings in 2019 novel coronavirus (2019-nCoV) infections from Wuhan, China: key points for the radiologist. Radiological Society of North America; 2020. p. 16-7.

Wong HYF, Lam HYS, Fong AH-T, Leung ST, Chin TW-Y, Lo CSY, et al. Frequency and distribution of chest radiographic findings in patients positive for COVID-19. 2020;296(2): E72-E8.

Bai HX, Hsieh B, Xiong Z, Halsey K, Choi JW, Tran TML, et al. Performance of radiologists in differentiating COVID-19 from non-COVID-19 viral pneumonia at chest CT. 2020;296(2): E46-E54.

Pan Y, Guan HJEr. Imaging changes in patients with 2019-nCov. 2020;30(7):3612-3.

Ng M-Y, Lee EY, Yang J, Yang F, Li X, Wang H, et al. Imaging profile of the COVID-19 infection: radiologic findings and literature review. 2020;2(1):e200034.

Arslan S, Delice O, Kahraman M, Yilmaz S, Aslan MJAoC, Medicine A. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in Turkey. 2021:483-7.

Waris A, Atta U, Ali M, Asmat A, Baset AJNm, infections n. COVID-19 outbreak: current scenario of Pakistan. 2020; 35:100681.

Axiaq A, Almohtadi A, Massias SA, Ngemoh D, Harky AJCOiPM. The role of computed tomography scan in the diagnosis of COVID-19 pneumonia. 2021;27(3):163-8.

Wang Y, Dong C, Hu Y, Li C, Ren Q, Zhang X, et al. Temporal changes of CT findings in 90 patients with COVID-19 pneumonia: a longitudinal study. 2020;296(2):E55-E64.

Ye Z, Zhang Y, Wang Y, Huang Z, Song BJEr. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. 2020;30:4381-9.

Sohail SJPjoms. Rational and practical use of imaging in COVID-19 pneumonia. 2020;36(COVID19-S4): S130.

Khaliq M, Raja R, Khan N, Hanif HJC. An analysis of high-resolution computed tomography chest manifestations of COVID-19 patients in Pakistan. 2020;12(7).

Lamberghini F, Testai FDJTJotADA. COVID-2019 fundamentals. 2021;152(5):354-63.

Yang X, Yu Y, Xu J, Shu H, Liu H, Wu Y, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. 2020;8(5):475-81.

Liu K, Fang Y-Y, Deng Y, Liu W, Wang M-F, Ma J-P, et al. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. 2020;133(09):1025-31.

Zhang J-j, Dong X, Cao Y-y, Yuan Y-d, Yang Y-b, Yan Y-q, et al. Clinical characteristics of 140 patients infected with SARS‐CoV‐2 in Wuhan, China. 2020;75(7):1730-41.

Fang Y, Zhang H, Xu Y, Xie J, Pang P, Ji WJR. CT manifestations of two cases of 2019 novel coronavirus (2019-nCoV) pneumonia. 2020;295(1):208-9.

Covid C, Pan F, Ye T, Sun P, Gui S, Liang B, et al. Time course of lung changes at chest CT during recovery. vol; 2019.

Kanne JP, Little BP, Chung JH, Elicker BM, Ketai LHJR. Essentials for radiologists on COVID-19: an update—radiology scientific expert panel. Radiological Society of North America; 2020. p. E113-E4.

Control CfD, Prevention. CDC 2019-novel coronavirus (2019-nCoV) real-time RT-PCR diagnostic panel. 2020.

Han R, Huang L, Jiang H, Dong J, Peng H, Zhang DJAAJR. Early clinical and CT manifestations of coronavirus disease 2019 (COVID-19) pneumonia. 2020;215(2):338-43.

Wu J, Wu X, Zeng W, Guo D, Fang Z, Chen L, et al. Chest CT findings in patients with coronavirus disease 2019 and its relationship with clinical features. 2020;55(5):257.

Parry AH, Wani AH, Shah NN, Yaseen M, Jehangir MJB, Open. Chest CT features of coronavirus disease-19 (COVID-19) pneumonia: which findings on initial CT can predict an adverse short-term outcome? 2020; 2:20200016.




DOI: http://dx.doi.org/10.36162/hjr.v9i3.585

Refbacks

  • There are currently no refbacks.