CT-Scan of Chest among Severe Covid-19 Patients: Experienced from Dedicated Hospital in Dhaka City

Authors

  • Md Zakirul Islam Assistant Professor, Department of Medicine, Kurmitola General Hospital, Dhaka, Bangladesh
  • Mohammad Enayet Hussain Associate Professor, Department of Neurology, National Institute of Neurosciences & Hospital, Dhaka, Bangladesh
  • Anjuman Ara Assistant Professor, Department of Obstetrics & Gynaecology, TMSS Medical College, Bogura, Bangladesh
  • Md Saheduzzaman Assistant Professor and Head, Department of Microbiology, Ad-din Akij Medical College, Khulna, Bangladesh
  • Rafiqul Islam Associate Professor, Department of Pharmacology, National Institute of Neurosciences & Hospital, Dhaka, Bangladesh
  • ASM Rezaul Karim Senior Consultant (Medicine), Nilphamary Sadar Hospital, Nilphamary, Bangladesh
  • Quazi Deen Mohammad Director & Professor of Neurology, National Institute of Neurosciences & Hospital, Dhaka, Bangladesh

DOI:

https://doi.org/10.3329/jninb.v8i1.59930

Keywords:

High Resolution CT-Scan; chest; Covid19 diseases; first wave of pandemic

Abstract

Background: High resolution Computed Tomography scan (HR CT-scan) of chest imaging among COVID-19 patients is very useful.

Objective: The purpose of the present study was to see the high resolution computed tomography (CT) findings observed among the coronavirus disease 2019 (COVID-19) patients presented with severe pneumonia.

Methodology: This retrospective study was performed in the Department of Radiology & Imaging at Kurmitola General Hospital, Dhaka, Bangladesh from April 2020 up to May 2020. As this was a retrospective study, verbal or written consent was not obtained from all potential participants or guardians. The available demographic data as well as the medical history of all data were collected and were thoroughly reviewed from the record book. These patients were RT-PCR confirmed severe cases of COVID-19 patients presented with pneumonia and were admitted in Kurmitola General Hospital, Dhaka, Bangladesh and all these patients underwent HRCT chest.

Result: A total number of 155 covid19 patients HRCT scan were evaluated. The mean age with SD of the study population was 58.03±14.08 years. The involvement of both lung was found in 32(20.6%) cases. Fibrosis of lungs and thickening of pleura were found in 38(24.5%) cases and 33(21.3%) cases respectively. Presence of pneumonitis and bronchiectasis were detected in 77(49.7%) cases and 5(3.2%) cases respectively. The most common form was the presence of only ground glass opacities (40.6%).

Conclusion: In conclusion the bilateral ground glass opacities and fibrosis of lungs with pneumonitis are most common findings of severe Covid-19 patients.

Journal of National Institute of Neurosciences Bangladesh, January 2022; 8(1):33-37

Downloads

Download data is not yet available.
Abstract
2
PDF
2

Downloads

Published

2022-05-27

How to Cite

Islam, M. Z. ., Hussain, M. E., Ara, A. ., Saheduzzaman, M., Islam, R. ., Karim, A. R. ., & Mohammad, Q. D. . (2022). CT-Scan of Chest among Severe Covid-19 Patients: Experienced from Dedicated Hospital in Dhaka City. Journal of National Institute of Neurosciences Bangladesh, 8(1), 33–37. https://doi.org/10.3329/jninb.v8i1.59930

Issue

Vol. 8 No. 1 (2022)

Section

Original Research Articles

License

Copyright (c) 2022 Md Zakirul Islam, Mohammad Enayet Hussain, Anjuman Ara, Md Saheduzzaman, Rafiqul Islam, ASM Rezaul Karim, Quazi Deen Mohammad

Creative Commons License

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

Copyright on any research article in the Journal of National Institute of Neurosciences Bangladesh is retained by the author(s).

The authors grant the National Institute of Neurosciences Bangladesh a license to publish the article and identify itself as the original publisher.

Articles in the Journal of National Institute of Neurosciences Bangladesh are Open Access articles published under the Creative Commons CC BY-NC License (https://creativecommons.org/licenses/by-nc/4.0/)

This license permits use, distribution and reproduction in any medium, provided the original work is properly cited, and it is not used for commercial purposes.