Effect of demographic factors on CT findings and prognostic implications of imaging in COVID-19 participants: A multicenter study

Introduction: Studies show that chest computed tomography (CT) findings in patients with COVID-19 may differ among different populations, which could be attributed to demographic differences. The present study is done to provide evidence regarding the effect of demographic factors on imaging findings. Methods: This retrospective study involved 202 participants with COVID-19. The participants underwent CT imaging before hospitalization or on the first day of admission. Two expert radiologists determined each patient’s radiologic signs and symptoms. Results: by comparing dead participants and survivors, airspace consolidation, air Bronchogram, and posterior segment involvement were commonly seen in passing participants. Lung score and mean number of involved segments were higher in passing participants. Participants over 75 were less likely to have lymphadenopathy, septal thickening, and sub-pleural transparent lines. The area under the curve was 0.706 (95% CI: 0.631-0.782), higher among women older than 75. Conclusion: Although demographic features generally do not affect common imaging findings in COVID-19 participants, the prognostic significance of chest CT imaging may differ based on gender and age.

Authors

Institutions

Publication Details

Journal
Journal of Research in Clinical Medicine
Published
2025-12-27
DOI
https://doi.org/10.34172/jrcm.025.34624
Primary Topic
COVID-19 Clinical Research Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effect of demographic factors on CT findings and prognostic implications of imaging in COVID-19 participants: A multicenter study

Ali Akhavi Milani, Zahra Babaei Aghdam, Reza Rikhtegar, Elyad Ekrami et al.
Journal of Research in Clinical Medicine
COVID-19 Clinical Research Studies
article

Effect of demographic factors on CT findings and prognostic implications of imaging in COVID-19 participants: A multicenter study

Ali Akhavi Milani, Zahra Babaei Aghdam, Reza Rikhtegar, Elyad Ekrami, Shahin Hallaj, Ebrahim Farashi, Mohammad Khalafi, Afshin Mohammadi, Mohammad Mirza-Aghazadeh-Attari, Armin Zarrintan, Seyed Ali Mousavi-Aghdas
article en

Abstract

Introduction: Studies show that chest computed tomography (CT) findings in patients with COVID-19 may differ among different populations, which could be attributed to demographic differences. The present study is done to provide evidence regarding the effect of demographic factors on imaging findings. Methods: This retrospective study involved 202 participants with COVID-19. The participants underwent CT imaging before hospitalization or on the first day of admission. Two expert radiologists determined each patient’s radiologic signs and symptoms. Results: by comparing dead participants and survivors, airspace consolidation, air Bronchogram, and posterior segment involvement were commonly seen in passing participants. Lung score and mean number of involved segments were higher in passing participants. Participants over 75 were less likely to have lymphadenopathy, septal thickening, and sub-pleural transparent lines. The area under the curve was 0.706 (95% CI: 0.631-0.782), higher among women older than 75. Conclusion: Although demographic features generally do not affect common imaging findings in COVID-19 participants, the prognostic significance of chest CT imaging may differ based on gender and age.

Journal of Research in Clinical MedicineVol. 13
Cleveland Clinic (US), Viterbo University (US), Johns Hopkins University (US), Tabriz University of Medical Sciences (IR), Urmia University (IR), Alfried Krupp Hospital (DE), Urmia University of Medical Sciences (IR)
Gender equality
Openalex Percentile: Top 29%
COVID-19 Clinical Research Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.