Cargando…
A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531052/ https://www.ncbi.nlm.nih.gov/pubmed/33072703 http://dx.doi.org/10.3389/fpubh.2020.567672 |
_version_ | 1783589686835412992 |
---|---|
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 |
author_facet | 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 |
author_sort | Jin, Chao |
collection | PubMed |
description | 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: One hundred and sixty-five patients with COVID-19 (91 men, 4–89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern 0 (negative), Pattern 1 (bronchopneumonia pattern), Pattern 2 (organizing pneumonia pattern), Pattern 3 (progressive organizing pneumonia pattern), and Pattern 4 (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. ≤ 10 mg/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. |
format | Online Article Text |
id | pubmed-7531052 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75310522020-10-17 A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia 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 Front Public Health Public Health 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: One hundred and sixty-five patients with COVID-19 (91 men, 4–89 years) underwent chest CT were retrospectively enrolled. CT findings were categorized as Pattern 0 (negative), Pattern 1 (bronchopneumonia pattern), Pattern 2 (organizing pneumonia pattern), Pattern 3 (progressive organizing pneumonia pattern), and Pattern 4 (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. ≤ 10 mg/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. Frontiers Media S.A. 2020-09-18 /pmc/articles/PMC7531052/ /pubmed/33072703 http://dx.doi.org/10.3389/fpubh.2020.567672 Text en Copyright © 2020 Jin, Tian, Wang, Wu, Zhao, Liang, Liu, Jian, Li, Wang, Li, Zhou, Cai, Liu, Li, Li, Liang, Zhou, Wang, Ren and Yang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health 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 A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title | A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title_full | A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title_fullStr | A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title_full_unstemmed | A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title_short | A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia |
title_sort | pattern categorization of ct findings to predict outcome of covid-19 pneumonia |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531052/ https://www.ncbi.nlm.nih.gov/pubmed/33072703 http://dx.doi.org/10.3389/fpubh.2020.567672 |
work_keys_str_mv | AT jinchao apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT tiancong apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangyan apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wucarolc apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhaohuifang apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liangting apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liuzhe apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT jianzhijie apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lirunqing apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangzekun apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lifen apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhoujie apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT caishubo apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liuyang apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lihao apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lizhongyi apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liangyukun apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhouheping apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangxibin apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT renzhuanqin apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT yangjian apatterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT jinchao patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT tiancong patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangyan patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wucarolc patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhaohuifang patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liangting patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liuzhe patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT jianzhijie patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lirunqing patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangzekun patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lifen patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhoujie patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT caishubo patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liuyang patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lihao patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT lizhongyi patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT liangyukun patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT zhouheping patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT wangxibin patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT renzhuanqin patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia AT yangjian patterncategorizationofctfindingstopredictoutcomeofcovid19pneumonia |