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CT Quantification of COVID-19 Pneumonia at Admission Can Predict Progression to Critical Illness: A Retrospective Multicenter Cohort Study.
Pang, Baoguo; Li, Haijun; Liu, Qin; Wu, Penghui; Xia, Tingting; Zhang, Xiaoxian; Le, Wenjun; Li, Jianyu; Lai, Lihua; Ou, Changxing; Ma, Jianjuan; Liu, Shuai; Zhou, Fuling; Wang, Xinlu; Xie, Jiaxing; Zhang, Qingling; Jiang, Min; Liu, Yumei; Zeng, Qingsi.
  • Pang B; Department of Radiology, Huangpi District Hospital of Traditional Chinese Medicine, Wuhan, China.
  • Li H; Department of Radiology, Han Kou Hospital of Wuhan, Wuhan, China.
  • Liu Q; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Wu P; Pulmonary and Critical Care Medicine, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Xia T; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Zhang X; Pulmonary and Critical Care Medicine, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Le W; Department of Respiratory, First Affiliated Hospital of Guangxi University of Science and Technology, Liuzhou, China.
  • Li J; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Lai L; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Ou C; Pulmonary and Critical Care Medicine, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Ma J; Department of Pediatric Hematology, Affiliated Hospital of Guizhou Medical University, Guiyang, China.
  • Liu S; Department of Hematology, Dawu County People's Hospital, Wuhan, China.
  • Zhou F; Department of Hematology, Zhongnan Hospital of Wuhan University, Wuhan, China.
  • Wang X; Department of Nuclear Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Xie J; National Clinical Research Center for Respiratory Disease, State Key Laboratory of Respiratory Diseases, Department of Allergy and Clinical Immunology, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Zhang Q; Pulmonary and Critical Care Medicine, National Clinical Research Center for Respiratory Disease, National Center for Respiratory Medicine, State Key Laboratory of Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou
  • Jiang M; Department of Pediatrics, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
  • Liu Y; Department of Respiratory, Hankou Hospital of Wuhan, Wuhan, China.
  • Zeng Q; Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Front Med (Lausanne) ; 8: 689568, 2021.
Artículo en Inglés | MEDLINE | ID: covidwho-1295660
ABSTRACT

Objective:

Early identification of coronavirus disease 2019 (COVID-19) patients with worse outcomes may benefit clinical management of patients. We aimed to quantify pneumonia findings on CT at admission to predict progression to critical illness in COVID-19 patients.

Methods:

This retrospective study included laboratory-confirmed adult patients with COVID-19. All patients underwent a thin-section chest computed tomography (CT) scans showing evidence of pneumonia. CT images with severe moving artifacts were excluded from analysis. Patients' clinical and laboratory data were collected from medical records. Three quantitative CT features of pneumonia lesions were automatically calculated using a care.ai Intelligent Multi-disciplinary Imaging Diagnosis Platform Intelligent Evaluation System of Chest CT for COVID-19, denoting the percentage of pneumonia volume (PPV), ground-glass opacity volume (PGV), and consolidation volume (PCV). According to Chinese COVID-19 guidelines (trial version 7), patients were divided into noncritical and critical groups. Critical illness was defined as a composite of admission to the intensive care unit, respiratory failure requiring mechanical ventilation, shock, or death. The performance of PPV, PGV, and PCV in discrimination of critical illness was assessed. The correlations between PPV and laboratory variables were assessed by Pearson correlation analysis.

Results:

A total of 140 patients were included, with mean age of 58.6 years, and 85 (60.7%) were male. Thirty-two (22.9%) patients were critical. Using a cutoff value of 22.6%, the PPV had the highest performance in predicting critical illness, with an area under the curve of 0.868, sensitivity of 81.3%, and specificity of 80.6%. The PPV had moderately positive correlation with neutrophil (%) (r = 0.535, p < 0.001), erythrocyte sedimentation rate (r = 0.567, p < 0.001), d-Dimer (r = 0.444, p < 0.001), high-sensitivity C-reactive protein (r = 0.495, p < 0.001), aspartate aminotransferase (r = 0.410, p < 0.001), lactate dehydrogenase (r = 0.644, p < 0.001), and urea nitrogen (r = 0.439, p < 0.001), whereas the PPV had moderately negative correlation with lymphocyte (%) (r = -0.535, p < 0.001).

Conclusions:

Pneumonia volume quantified on initial CT can non-invasively predict the progression to critical illness in advance, which serve as a prognostic marker of COVID-19.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio de cohorte / Estudios diagnósticos / Estudio experimental / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Idioma: Inglés Revista: Front Med (Lausanne) Año: 2021 Tipo del documento: Artículo País de afiliación: Fmed.2021.689568

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Tipo de estudio: Estudio de cohorte / Estudios diagnósticos / Estudio experimental / Estudio observacional / Estudio pronóstico / Ensayo controlado aleatorizado Idioma: Inglés Revista: Front Med (Lausanne) Año: 2021 Tipo del documento: Artículo País de afiliación: Fmed.2021.689568