Date of Award

5-1-2022

Degree Type

Dissertation

Degree Name

Master of Medicine (MMed)

First Advisor

Dr. Edward Nganga

Second Advisor

Dr. Samuel Gitau

Third Advisor

Prof. Reena Shah

Department

Imaging and Diagnostic Radiology (East Africa)

Abstract

Background: Imaging with chest computed tomography (CT) has demonstrated a role in stratifying COVID-19 patients into different clinical severity groups thus facilitating appropriate care decisions. In a limited number of settings, the wider applicability and reproducibility of these findings is unclear. Objectives: To determine the association between chest CT severity score and clinical severity of illness in RT-PCR confirmed SARS-CoV2 patients. To evaluate the relationship of CT chest severity score with short term clinical outcome of patients. Methods: CT chest of 172 SARS-CoV2 patients who accessed care at Aga Khan University Hospital Nairobi between 14th March and 31st December 2020 were retrospectively scored for CT severity of disease using a 5-point score for lobar involvement (0:0%; 1,75%). CT was compared with clinical severity of disease. Logistic regression analysis was performed to assess the CT score utility in predicting short term clinical outcome. Results: Majority of the study population were male 127(73.8%) and only 12() presented within 48 hours of symptom onset. The commonest presenting symptoms were cough 118 (68.6%), fever 81 (47.1%) and difficulty breathing 69(40.1%). CT score had fair positive correlation with clinical severity r=0.378. CT score was significantly higher in the severe category versus the moderate category (p Conclusion: Fair positive correlation of CT severity with clinical severity of COVID-19 pneumonia and less than perfect inter-rater agreement on CT severity scoring limits application of CT derived COVID-19 severity score.

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