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Quantitative Computed Tomography Lung COVID Scores with Laboratory Markers: Utilization to Predict Rapid Progression and Monitor Longitudinal Changes in Patients with Coronavirus 2019 (COVID-19) Pneumonia.
Kang, Da Hyun; Kim, Grace Hyun J; Park, Sa-Beom; Lee, Song-I; Koh, Jeong Suk; Brown, Matthew S; Abtin, Fereidoun; McNitt-Gray, Michael F; Goldin, Jonathan G; Lee, Jeong Seok.
Affiliation
  • Kang DH; Department of Internal Medicine, College of Medicine, Chungnam National University, Daejeon 35015, Republic of Korea.
  • Kim GHJ; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA.
  • Park SB; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA.
  • Lee SI; Center of Biohealth Convergence and Open Sharing System, Hongik University, Seoul 04401, Republic of Korea.
  • Koh JS; Department of Internal Medicine, College of Medicine, Chungnam National University, Daejeon 35015, Republic of Korea.
  • Brown MS; Department of Internal Medicine, College of Medicine, Chungnam National University, Daejeon 35015, Republic of Korea.
  • Abtin F; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA.
  • McNitt-Gray MF; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA.
  • Goldin JG; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA.
  • Lee JS; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA.
Biomedicines ; 12(1)2024 Jan 06.
Article in En | MEDLINE | ID: mdl-38255225
ABSTRACT
Coronavirus disease 2019 (COVID-19), is an ongoing issue in certain populations, presenting rapidly worsening pneumonia and persistent symptoms. This study aimed to test the predictability of rapid progression using radiographic scores and laboratory markers and present longitudinal changes. This retrospective study included 218 COVID-19 pneumonia patients admitted at the Chungnam National University Hospital. Rapid progression was defined as respiratory failure requiring mechanical ventilation within one week of hospitalization. Quantitative COVID (QCOVID) scores were derived from high-resolution computed tomography (CT) analyses (1) ground glass opacity (QGGO), (2) mixed diseases (QMD), and (3) consolidation (QCON), and the sum, quantitative total lung diseases (QTLD). Laboratory data, including inflammatory markers, were obtained from electronic medical records. Rapid progression was observed in 9.6% of patients. All QCOVID scores predicted rapid progression, with QMD showing the best predictability (AUC = 0.813). In multivariate analyses, the QMD score and interleukin(IL)-6 level were important predictors for rapid progression (AUC = 0.864). With >2 months follow-up CT, remained lung lesions were observed in 21 subjects, even after several weeks of negative reverse transcription polymerase chain reaction test. AI-driven quantitative CT scores in conjugation with laboratory markers can be useful in predicting the rapid progression and monitoring of COVID-19.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Biomedicines Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Biomedicines Year: 2024 Document type: Article