Research Article

Evaluation of Pneumonia Severity and Lung Computed Tomography Findings in Covid-19 Patients

Volume: 15 Number: 3 July 1, 2024
EN

Evaluation of Pneumonia Severity and Lung Computed Tomography Findings in Covid-19 Patients

Abstract

Purpose: Early recognition of corona virus disease 2019 (COVID-19) cases is the key to reducing mortality. In this study, we aimed to describe the relationship between the clinical, laboratory, and lung computed tomography (LCT) characteristics of patients with COVID-19 pneumonia and determine the severity of pneumonia in these patients. Methods: The pneumonia severity index (PSI) score system, LCT images, and laboratory parameters at the time of first presentation to the emergency department were examined to assess the severity of COVID-19 pneumonia in 225 adult patients. Results: In this study, a significant relationship was found between COVID-19-associated mortality and male gender (p=0.045), advanced age (p<0.001), a high neutrophil count in peripheral blood (p<0.001), a low eosinophil count (p<0.001), 5-49% lung involvement on LCT (p<0.001), and PSI Groups IV and V (p<0.001). Conclusion: Using the multivariate logistic regression analysis, we determined the most significant factors for mortality as advanced age, low eosinophil and lymphocyte counts, increased lactate and ferritin levels, and PSI Group V.

Keywords

References

  1. 1. Loeffelholz MJ, Tang Y-W. Laboratory diagnosis of emerging human coronavirus infections–the state of the art. EMi, 2020;9(1):747-56. DOI: 10.1080/22221751.2020.1745095
  2. 2. Xu X-W, Wu X-X, Jiang X-G, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series. BMJ. 2020;368. DOI: 10.1136/bmj.m606
  3. 3. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239-42. DOI: 10.1001/jama.2020.2648
  4. 4. Pan L, Mu M, Yang P, et al. Clinical characteristics of COVID-19 patients with digestive symptoms in Hubei, China: a descriptive, cross-sectional, multicenter study. The AJG. 2020;115. DOI: 10.14309/ajg.0000000000000620
  5. 5. Li K, Wu J, Wu F, et al. The clinical and chest CT features associated with severe and critical COVID-19 pneumonia. Invest Radiol. 2020. DOI: 10.1097/RLI.0000000000000672
  6. 6. Liu R, Han H, Liu F, et al. Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020. CCA. 2020;505:172-5. DOI: 10.1016/j.cca.2020.03.009
  7. 7. Control CfD, Prevention. Research use only real-time RT-PCR protocol for identification of 2019-nCoV. 2020.
  8. 8. Wang S, Kang B, Ma J, et al. A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19). ESR. 2021;31:6096-104. DOI: 10.1007/s00330-021-07715-1

Details

Primary Language

English

Subjects

Infectious Diseases , ​Internal Diseases

Journal Section

Research Article

Publication Date

July 1, 2024

Submission Date

September 19, 2023

Acceptance Date

December 13, 2023

Published in Issue

Year 2024 Volume: 15 Number: 3

EndNote
Cihanbeylerden M, Şafak Ç, Tek C, Savran M (July 1, 2024) Evaluation of Pneumonia Severity and Lung Computed Tomography Findings in Covid-19 Patients. Acıbadem Üniversitesi Sağlık Bilimleri Dergisi 15 3 194–203.

Cited By