CT severity Radiological phenotypes (CTS) assessment in COVID-19 pneumonia as ‘inconsistent predictor of disease severity’: A large tertiary care center study in India

Authors

  • Shital Patil Associate Professor& Head, Pulmonary Medicine MIMSR Medical college, Latur, Maharashtra state, India
  • Pravin Bhagat Assistant Professor, Internal Medicine, MIMSR Medical College, Latur India
  • Rajesh Bobade Assistant Professor, Internal Medicine, MIMSR Medical College, Latur India
  • Uttareshvar Dhumal Professor, Radiodiagnosis, MIMSR Medical College, Latur India
  • Laxman Kasture Professor and Head, Radiodiagnosis, MIMSR Medical College, Latur India
  • Gajanan Gondhali Professor, Pulmonary Medicine, MIMSR Medical College, Latur India

DOI:

https://doi.org/10.3329/jom.v25i1.70528

Keywords:

COVID-19 pneumonia, Radiological phenotypes, CT severity, post covid lung fibrosis, Inflammatory marker

Abstract

Introduction: Radiological phenotypes are radiological patterns or observable characteristics of COVID-19 pneumonia. Various phenotypic classifications have been reported in literature. CT severity radiological phenotypes are widely used and universally accepted radiological phenotypic methods. Robust data is available regarding role of HRCT in COVID-19 pneumonia and we have evaluated role of CT severity in assessing natural course of COVID-19 illness during its evolution sand follow-up.

Methods: Prospective, Observational study, included 3000 COVID-19 RT-PCR confirmed cases with lung involvement documented and radiological severity phenotypes categorized on HRCT thorax as mild, moderate and severe as per lung segment involvement bilaterally (scoring tool 0-25 score, mild 1-7, moderate 8-15 and severe 16-25). Radiological CT severity phenotypes were   evaluated in correlation with interventions such as oxygen support and oxygen plus ventilatory support requirement during hospitalization. Age, gender, Comorbidity, laboratory parameters and use of BIPAP/NIV in COVID-19 cases and outcome as with or without lung fibrosis were key observations. Final radiological outcome documented in follow up CT thorax imaging done at six months of discharge from hospital. Statistical analysis is done by using Chi square test. 

Results: In study of 3000 cases, ‘mild, moderate and severe’ radiological CT severity phenotypes were documented as 13.33%, 48.33% & 38.34 % respectively. CT severity has documented significant association with duration of illness at entry point [p<0.00001] Duration of illness (<7 days, 7-14 days and >14 days) plays a crucial role in predicting radiological CT severity phenotypes. CT severity has documented significant association with laboratory parameters at entry point (d-dimer, CRP, IL-6) [p<0.00001] and interventions required in indoor unit. [p<0.00001] Post COVID-19 lung fibrosis or sequelae has significant association with radiological CT severity phenotypes. [p<0.00001] Covariates such as age, gender, diabetes mellitus, IHD, Hypertension, COPD, Obesity has significant association with radiological CT severity phenotypes. [p<0.00001]

Conclusion: Radiological CT severity phenotypic differentiation has documented very crucial role in initial assessment and during triaging of these cases in indoor and outdoor setting. Although CT severity is best predictor of severity it has showed ‘inconstancy’ in predicting disease severity, targeting interventions and predicting early and long-term outcomes in COVID-19 pneumonia.

J MEDICINE 2024; 25: 46-57

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Published

2024-01-04

How to Cite

Patil , S. ., Bhagat, P. ., Bobade, R. ., Dhumal , U. ., Kasture, L. ., & Gondhali , G. . (2024). CT severity Radiological phenotypes (CTS) assessment in COVID-19 pneumonia as ‘inconsistent predictor of disease severity’: A large tertiary care center study in India. Journal of Medicine, 25(1), 46–57. https://doi.org/10.3329/jom.v25i1.70528

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Original Articles