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A pattern categorization of CT findings to predict outcome of COVID-19 pneumonia
Chao Jin; Yan Wang; Carol C. Wu; Huifang Zhao; Ting Liang; Zhe Liu; Zhijie Jian; Runqing Li; Zekun Wang; Fen Li; Jie Zhou; Shubo Cai; Yang Liu; Hao Li; Zhongyi Li; Yukun Liang; Heping Zhou; Xibin Wang; Zhuanqin Ren; Jian Yang.
Afiliação
  • Chao Jin; First Affiliated Hospital of Xi'an Jiaotong University
  • Yan Wang; First Affiliated Hospital of Xi'an Jiaotong University
  • Carol C. Wu; University of Texas M.D. Anderson Cancer Center
  • Huifang Zhao; First Affiliated Hospital of Xi'an Jiaotong University
  • Ting Liang; First Affiliated Hospital of Xi'an Jiaotong University
  • Zhe Liu; First Affiliated Hospital of Xi'an Jiaotong University
  • Zhijie Jian; First Affiliated Hospital of Xi'an Jiaotong University
  • Runqing Li; First Affiliated Hospital of Xi'an Jiaotong University
  • Zekun Wang; the Eighth Hospital of Xi'an
  • Fen Li; the Eighth Hospital of Xi'an
  • Jie Zhou; Xi'an Chest Hospital
  • Shubo Cai; Xi'an Chest Hospital
  • Yang Liu; First Affiliated Hospital of Xi'an Jiaotong University
  • Hao Li; First Affiliated Hospital of Xi'an Jiaotong University
  • Zhongyi Li; Wuhan No.9 Hospital
  • Yukun Liang; Ankang Center Hospital
  • Heping Zhou; Ankang Center Hospital
  • Xibin Wang; Hanzhong Center Hospital
  • Zhuanqin Ren; Baoji Center Hospital
  • Jian Yang; The First Affiliated Hospital of Xi'an Jiaotong University
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20107409
ABSTRACT
AbstractsO_ST_ABSPurposeC_ST_ABSAs global healthcare system is overwhelmed by novel coronavirus disease (COVID-19), early identification of risks of adverse outcomes becomes the key to optimize management and improve survival. This study aimed to provide a CT-based pattern categorization to predict outcome of COVID-19 pneumonia. Methods165 patients with COVID-19 (91 men, 4-89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern0 (negative), Pattern1 (bronchopneumonia), Pattern2 (organizing pneumonia), Pattern3 (progressive organizing pneumonia) and Pattern4 (diffuse alveolar damage). Clinical findings were compared across different categories. Time-dependent progression of CT patterns and correlations with clinical outcomes, i.e. discharge or adverse outcome (admission to ICU, requiring mechanical ventilation, or death), with pulmonary sequelae (complete absorption or residuals) on CT after discharge were analyzed. ResultsOf 94 patients with outcome, 81(86.2%) were discharged, 3(3.2%) were admitted to ICU, 4(4.3%) required mechanical ventilation, 6(6.4%) died. 31(38.3%) had complete absorption at median day 37 after symptom-onset. Significant differences between pattern-categories were found in age, disease-severity, comorbidity and laboratory results (all P<0.05). Remarkable evolution was observed in Pattern0-2 and Pattern3-4 within 3 and 2 weeks after symptom-onset, respectively; most of patterns remained thereafter. After controlling for age, CT pattern significantly correlated with adverse outcomes (Pattern4 vs. Pattern0-3 [reference]; hazard-ratio[95%CI], 18.90[1.91-186.60], P=0.012). CT pattern (Pattern3-4 vs. Pattern0-2 [reference]; 0.26[0.08-0.88], P=0.030) and C-reactive protein (>10 vs. [≤]10mg/L [reference]; 0.31[0.13-0.72], P=0.006) were risk-factors associated with pulmonary residuals. ConclusionCT pattern categorization allied with clinical characteristics within 2 weeks after symptom-onset would facilitate early prognostic stratification in COVID-19 pneumonia.
Licença
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Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
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