AUTHOR=Jin Chao , Tian Cong , Wang Yan , Wu Carol C. , Zhao Huifang , Liang Ting , Liu Zhe , Jian Zhijie , Li Runqing , Wang Zekun , Li Fen , Zhou Jie , Cai Shubo , Liu Yang , Li Hao , Li Zhongyi , Liang Yukun , Zhou Heping , Wang Xibin , Ren Zhuanqin , Yang Jian 

TITLE=A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia

JOURNAL=Frontiers in Public Health

VOLUME=Volume 8 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2020.567672

DOI=10.3389/fpubh.2020.567672

ISSN=2296-2565

ABSTRACT=Background As 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.
Methods 165 patients with COVID-19 (91 men, 4-89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern0 (negative), Pattern1 (bronchopneumonia pattern), Pattern2 (organizing pneumonia pattern), Pattern3 (progressive organizing pneumonia pattern) and Pattern4 (diffuse alveolar damage pattern). 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.
Results Of 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 Pattern 0-2 and Pattern 3-4 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 (Pattern 4 vs. Pattern 0-3 [reference]; hazard-ratio [95%CI], 18.90[1.91-186.60], P=0.012). CT pattern (Pattern 3-4 vs. Pattern 0-2 [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.
Conclusion CT pattern categorization allied with clinical characteristics within 2 weeks after symptom onset would facilitate early prognostic stratification in COVID-19 pneumonia.