Open Access Peer-reviewed Research Article

Prediction of mortality in adult COVID-19 patients using chest CT severity scoring systems: A comparative analysis of different scores

Article Sidebar

ROC curves
Download PDF
Submitted   Dec 12, 2023
Published   Feb 22, 2024
Issue    Vol 5 No 1 (2023)
DOI   10.25082/AGPM.2023.01.002

Views

819

Downloads

328

Citations

PlumX Metrics

Main Article Content

Didier Ndyanabo Ndabahweje
Department of Medical Imaging, Faculty of Medicine, University of Goma, Goma, Democratic Republic of the Congo
Olivier Mukuku corresponding author
Institut Supérieur des Techniques Médicales de Lubumbashi, Lubumbashi, Democratic Republic of the Congo
Charles Kangitsi Kahindo
1. Department of Internal Medicine, Faculty of Medicine, University of Goma, Goma, Democratic Republic of the Congo; 2. Clinique Internationale de Médecine Avancé au Kivu, Goma, Democratic Republic of the Congo
Michel Lelo Tshikwela
Department of Medical Imagery, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Gertrude Luyeye Mvila
Department of Medical Imagery, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Antoine Molua Aundu
Department of Medical Imagery, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Jean Tshibola Mukaya
Department of Medical Imagery, Faculty of Medicine, University of Kinshasa, Kinshasa, Democratic Republic of the Congo
Stanis Okitotsho Wembonyama
Department of Pediatrics, Faculty of Medicine, University of Lubumbashi, Lubumbashi, Democratic Republic of the Congo
Zacharie Kibendelwa Tsongo
Department of Internal Medicine, Faculty of Medicine, University of Kisangani, Kisangani, Democratic Republic of the Congo

Abstract

Purpose: To compare the accuracy of mortality prediction of four CT severity scoring systems for COVID-19: CT severity score three levels, CT severity score, Total severity score, and Chest CT score.
Methods: This was a retrospective study of 278 patients hospitalized with COVID-19 confirmed by a positive polymerase chain reaction (PCR) and in whom a CT scan was performed to assess the severity of lung involvement. This assessment was performed using four different scoring systems, including the CT severity score three levels, the CT severity score, the Total severity score, and the Chest CT score.
Results: A total of 278 COVID-19 patients had chest CT scans, of whom 59 (21.22%) died and 219 (78.78%) survived. The ROC curves showed outstanding performance for the four chest CT severity scoring systems: 0.9580 for the CT severity score; 0.9532 for the CT severity score three levels; 0.9474 for the Total severity score; and 0.9327 for the Chest CT score. The comparison of these four ROC curves revealed no statistically significant difference between the four scoring systems (X2 = 3.89; p = 0.2740).
Conclusion: The four chest CT severity scoring systems used predicted mortality in COVID-19 patients with excellent agreement and outstanding performance.

Keywords
COVID-19, prognosis, mortality, ROC curve, computed tomography, CT severity score

Article Details

How to Cite
Ndabahweje, D. N., Mukuku, O., Kahindo, C. K., Tshikwela, M. L., Mvila, G. L., Aundu, A. M., Mukaya, J. T., Wembonyama, S. O., & Tsongo, Z. K. (2024). Prediction of mortality in adult COVID-19 patients using chest CT severity scoring systems: A comparative analysis of different scores. Advances in General Practice of Medicine, 5(1), 81-89. https://doi.org/10.25082/AGPM.2023.01.002
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

References

  1. Zhu N, Zhang D, Wang W, et al. A Novel Coronavirus from Patients with Pneumonia in China, 2019. New England Journal of Medicine. 2020, 382(8): 727-733. https://doi.org/10.1056/nejmoa2001017
  2. Mahase E. Covid-19: WHO declares pandemic because of “alarming levels” of spread, severity, and inaction. BMJ. Published online March 12, 2020: m1036. https://doi.org/10.1136/bmj.m1036
  3. Saeed GA, Gaba W, Shah A, et al. Correlation between Chest CT Severity Scores and the Clinical Parameters of Adult Patients with COVID-19 Pneumonia. La Forgia D, ed. Radiology Research and Practice. 2021, 2021: 1-7. https://doi.org/10.1155/2021/6697677
  4. Dessie ZG, Zewotir T. Mortality-related risk factors of COVID-19: a systematic review and meta-analysis of 42 studies and 423,117 patients. BMC Infectious Diseases. 2021, 21(1). https://doi.org/10.1186/s12879-021-06536-3
  5. Fang Y, Zhang H, Xie J, et al. Sensitivity of Chest CT for COVID-19: Comparison to RT-PCR. Radiology. 2020, 296(2): E115-E117. https://doi.org/10.1148/radiol.2020200432
  6. Corman VM, Landt O, Kaiser M, et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Eurosurveillance. 2020, 25(3). https://doi.org/10.2807/1560-7917.es.2020.25.3.2000045
  7. Xie X, Zhong Z, Zhao W, et al. Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing. Radiology. 2020, 296(2): E41-E45. https://doi.org/10.1148/radiol.2020200343
  8. Liu J, Yu H, Zhang S. The indispensable role of chest CT in the detection of coronavirus disease 2019 (COVID-19). European Journal of Nuclear Medicine and Molecular Imaging. 2020, 47(7): 1638-1639. https://doi.org/10.1007/s00259-020-04795-x
  9. Kanne JP, Little BP, Chung JH, et al. Essentials for Radiologists on COVID-19: An Update—Radiology Scientific Expert Panel. Radiology. 2020, 296(2): E113-E114. https://doi.org/10.1148/radiol.2020200527
  10. Bai HX, Hsieh B, Xiong Z, et al. Performance of Radiologists in Differentiating COVID-19 from Non-COVID-19 Viral Pneumonia at Chest CT. Radiology. 2020, 296(2): E46-E54. https://doi.org/10.1148/radiol.2020200823
  11. Bernheim A, Mei X, Huang M, et al. Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection. Radiology. 2020, 295(3): 200463. https://doi.org/10.1148/radiol.2020200463
  12. Ai T, Yang Z, Hou H, et al. Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases. Radiology. 2020, 296(2): E32-E40. https://doi.org/10.1148/radiol.2020200642
  13. Ndabahweje DN, Kahindo CK, Mukuku O, et al. Knowledge about chest imaging findings in COVID-19 among healthcare workers in Goma, Democratic Republic of the Congo. Journal of the Pan African Thoracic Society. 2023, 0: 1-6. https://doi.org/10.25259/jpats_17_2023
  14. Machnicki S, Patel D, Singh A, et al. The Usefulness of Chest CT Imaging in Patients With Suspected or Diagnosed COVID-19. Chest. 2021, 160(2): 652-670. https://doi.org/10.1016/j.chest.2021.04.004
  15. Liu KC, Xu P, Lv WF, et al. CT manifestations of coronavirus disease-2019: A retrospective analysis of 73 cases by disease severity. European Journal of Radiology. 2020, 126: 108941. https://doi.org/10.1016/j.ejrad.2020.108941
  16. Elmokadem AH, Bayoumi D, Abo-Hedibah SA, et al. Diagnostic performance of chest CT in differentiating COVID-19 from other causes of ground-glass opacities. Egyptian Journal of Radiology and Nuclear Medicine. 2021, 52(1). https://doi.org/10.1186/s43055-020-00398-6
  17. Yang R, Li X, Liu H, et al. Chest CT Severity Score: An Imaging Tool for Assessing Severe COVID-19. Radiology: Cardiothoracic Imaging. 2020, 2(2): e200047. https://doi.org/10.1148/ryct.2020200047
  18. Li K, Fang Y, Li W, et al. CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19). European Radiology. 2020, 30(8): 4407-4416. https://doi.org/10.1007/s00330-020-06817-6
  19. Salaffi F, Carotti M, Tardella M, et al. The role of a chest computed tomography severity score in coronavirus disease 2019 pneumonia. Medicine. 2020, 99(42): e22433. https://doi.org/10.1097/md.0000000000022433
  20. Francone M, Iafrate F, Masci GM, et al. Chest CT score in COVID-19 patients: correlation with disease severity and short-term prognosis. European Radiology. 2020, 30(12): 6808-6817. https://doi.org/10.1007/s00330-020-07033-y
  21. Wasilewski P, Mruk B, Mazur S, et al. COVID-19 severity scoring systems in radiological imaging – a review. Polish Journal of Radiology. 2020, 85(1): 361-368. https://doi.org/10.5114/pjr.2020.98009
  22. Société Française de Radiologie. SFR e-Bulletin [Internet]. Paris: SFR. La société d’Imagerie Thoracique propose un compte-rendu structuré de scanner thoracique pour les patients suspects de COVID-19 [The French Thoracic Imaging Society proposes a structured chest Computerised Tomography report for patients with suspected COVID-19], 2020.
  23. Revel MP, Parkar AP, et al. COVID-19 patients and the radiology department – advice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI). European Radiology. 2020, 30(9): 4903-4909. https://doi.org/10.1007/s00330-020-06865-y
  24. Ye Z, Zhang Y, Wang Y, et al. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. European Radiology. 2020, 30(8): 4381-4389. https://doi.org/10.1007/s00330-020-06801-0
  25. Hansell DM, Bankier AA, MacMahon H, et al. Fleischner Society: Glossary of Terms for Thoracic Imaging. Radiology. 2008, 246(3): 697-722. https://doi.org/10.1148/radiol.2462070712
  26. Bernheim A, Mei X, Huang M, et al. Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. Radiology. 2020, 295(3): 200463.
  27. Hosmer DW, Lemeshow S, Rodney X. Sturdivant. Assessing the fit of the model. In: Applied logistic regression, 2nd edition. New York: Wiley; 2000. pp. 160–164.
  28. Wang Y, Dong C, Hu Y, et al. Temporal Changes of CT Findings in 90 Patients with COVID-19 Pneumonia: A Longitudinal Study. Radiology. 2020, 296(2): E55-E64. https://doi.org/10.1148/radiol.2020200843
  29. Li K, Wu J, Wu F, et al. The Clinical and Chest CT Features Associated With Severe and Critical COVID-19 Pneumonia. Investigative Radiology. 2020, 55(6): 327-331. https://doi.org/10.1097/rli.0000000000000672
  30. Pan F, Ye T, Sun P, et al. Time Course of Lung Changes at Chest CT during Recovery from Coronavirus Disease 2019 (COVID-19). Radiology. 2020, 295(3): 715-721. https://doi.org/10.1148/radiol.2020200370
  31. Salehi S, Abedi A, Balakrishnan S, et al. Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients. American Journal of Roentgenology. 2020, 215(1): 87-93. https://doi.org/10.2214/ajr.20.23034
  32. Wong HYF, Lam HYS, Fong AHT, et al. Frequency and Distribution of Chest Radiographic Findings in Patients Positive for COVID-19. Radiology. 2020, 296(2): E72-E78. https://doi.org/10.1148/radiol.2020201160
  33. Wong HYF, Lam HYS, Fong AH-T, et al. Frequency and distribution of chest radiographic findings in patients positive for COVID-19. Radiology. 2020, 296(2): 72-78.
  34. Shahzad N, Abid I, Mirza WJ, et al. Rapid assessment of COVID-19 suspected cases: A community based approach for developing countries like Pakistan. Journal of Global Health. 2020, 10(1). https://doi.org/10.7189/jogh.10.010353
  35. Xiong Y, Sun D, Liu Y, et al. Clinical and High-Resolution CT Features of the COVID-19 Infection: Comparison of the Initial and Follow-up Changes. Investigative Radiology. 2020, 55(6): 332-339. https://doi.org/10.1097/rli.0000000000000674
  36. Sohail S. Rational and practical use of imaging in COVID-19 pneumonia. Pakistan Journal of Medical Sciences. 2020, 36(COVID19-S4). https://doi.org/10.12669/pjms.36.covid19-s4.2760
  37. Tian S, Xiong Y, Liu H, et al. Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies. Modern Pathology. 2020, 33(6): 1007-1014. https://doi.org/10.1038/s41379-020-0536-x
  38. Hajiahmadi S, Shayganfar A, Janghorbani M, et al. Chest Computed Tomography Severity Score to Predict Adverse Outcomes of Patients with COVID-19. Infection & Chemotherapy. 2021, 53(2): 308. https://doi.org/10.3947/ic.2021.0024
  39. Almasi Nokiani A, Shahnazari R, Abbasi MA, et al. CT severity score in COVID-19 patients, assessment of performance in triage and outcome prediction: a comparative study of different methods. Egyptian Journal of Radiology and Nuclear Medicine. 2022, 53(1). https://doi.org/10.1186/s43055-022-00781-5