Comparison of Lung CT Scan Findings in Immunodeficient and Immunocompetent Patients During COVID-19

Background: Concerns asuppbout the consequences of COVID-19 in immunocompromised patients arose during the pandemic due to their higher risk of superinfection and complications. Computed Tomography (CT) scans play a confirmatory role in determining the severity of the disease. Objectives: Given the controversial evidence in this field, we conducted a study to compare lung CT scan findings in immunodeficient and immunocompetent patients with COVID-19. Methods: This cross-sectional study was performed on 1,246 immunodeficient and immunocompetent patients with COVID-19 from 2019 to 2022. During hospitalization and upon arrival at the hospital, all patients underwent lung CT scans, which were evaluated both quantitatively and qualitatively. The severity of lung involvement was graded as minimal, mild, moderate, or severe. All statistical analyses were performed using SPSS software version 22 and STATA version 15.1. Results: In this study, 50% of the patients were female. The mean age was 51 ± 15.4 years, and the mean length of hospitalization was 8.8 ± 5.8 days. Immune system defects were more common in patients over 50 years of age with diabetes, hypertension, malignancy, and renal dysfunction (P < 0.05). There was no significant difference in lung CT scan findings between immunodeficient and immunocompetent patients (P > 0.05). Conclusions: Based on our findings, there is no difference between these two groups of patients in terms of lung CT scan findings. Therefore, it would be beneficial to perform a meta-analysis for more accurate results in the future.

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Journal
Annals of Military and Health Sciences Research
Published
2024-09-10
DOI
https://doi.org/10.5812/amh-148614
Primary Topic
COVID-19 diagnosis using AI
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article
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article

Comparison of Lung CT Scan Findings in Immunodeficient and Immunocompetent Patients During COVID-19

Maryam Tajik Rostami, Sohrab Kolivand, Hermin Mokrian
Annals of Military and Health Sciences Research
COVID-19 diagnosis using AI
article

Comparison of Lung CT Scan Findings in Immunodeficient and Immunocompetent Patients During COVID-19

Maryam Tajik Rostami, Sohrab Kolivand, Hermin Mokrian
article en

Abstract

Background: Concerns asuppbout the consequences of COVID-19 in immunocompromised patients arose during the pandemic due to their higher risk of superinfection and complications. Computed Tomography (CT) scans play a confirmatory role in determining the severity of the disease. Objectives: Given the controversial evidence in this field, we conducted a study to compare lung CT scan findings in immunodeficient and immunocompetent patients with COVID-19. Methods: This cross-sectional study was performed on 1,246 immunodeficient and immunocompetent patients with COVID-19 from 2019 to 2022. During hospitalization and upon arrival at the hospital, all patients underwent lung CT scans, which were evaluated both quantitatively and qualitatively. The severity of lung involvement was graded as minimal, mild, moderate, or severe. All statistical analyses were performed using SPSS software version 22 and STATA version 15.1. Results: In this study, 50% of the patients were female. The mean age was 51 ± 15.4 years, and the mean length of hospitalization was 8.8 ± 5.8 days. Immune system defects were more common in patients over 50 years of age with diabetes, hypertension, malignancy, and renal dysfunction (P < 0.05). There was no significant difference in lung CT scan findings between immunodeficient and immunocompetent patients (P > 0.05). Conclusions: Based on our findings, there is no difference between these two groups of patients in terms of lung CT scan findings. Therefore, it would be beneficial to perform a meta-analysis for more accurate results in the future.

Annals of Military and Health Sciences ResearchVol. 22(3)
Hamedan University of Medical Sciences (IR)
Openalex Percentile: Top 75%
COVID-19 diagnosis using AI
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Comparison of Lung CT Scan Findings in Immunodeficient and Immunocompetent Patients During COVID-19 — Maryam Tajik Rostami, Sohrab Kolivand, et al. · Annals of Military and Health Sciences Research (2024) | TGRS Research Map | TGRS