a pattern categorization of ct findings to predict outcome of covid 19 pneumonia CORD-Papers-2021-10-25 (Version 1)

Title: A Pattern Categorization of CT Findings to Predict Outcome of COVID-19 Pneumonia
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: One hundred and sixty-five patients with COVID-19 (91 men, 489 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 02 and Pattern 34 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 03 [reference]; hazard-ratio [95% CI], 18.90 [1.91186.60], P = 0.012]. CT pattern [Pattern 34 vs. Pattern 02 [reference]; 0.26 [0.080.88], P = 0.030] and C-reactive protein [>10 vs. 10 mg/L [reference]; 0.31 [0.130.72], 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.
Published: 9/18/2020
Journal: Front Public Health
DOI: 10.3389/fpubh.2020.567672
DOI_URL: http://doi.org/10.3389/fpubh.2020.567672
Author Name: Jin, Chao
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jin_chao
Author Name: Tian, Cong
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tian_cong
Author Name: Wang, Yan
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_yan
Author Name: Wu, Carol C
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wu_carol_c
Author Name: Zhao, Huifang
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zhao_huifang
Author Name: Liang, Ting
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liang_ting
Author Name: Liu, Zhe
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_zhe
Author Name: Jian, Zhijie
Author link: https://covid19-data.nist.gov/pid/rest/local/author/jian_zhijie
Author Name: Li, Runqing
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_runqing
Author Name: Wang, Zekun
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_zekun
Author Name: Li, Fen
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_fen
Author Name: Zhou, Jie
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zhou_jie
Author Name: Cai, Shubo
Author link: https://covid19-data.nist.gov/pid/rest/local/author/cai_shubo
Author Name: Liu, Yang
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_yang
Author Name: Li, Hao
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_hao
Author Name: Li, Zhongyi
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_zhongyi
Author Name: Liang, Yukun
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liang_yukun
Author Name: Zhou, Heping
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zhou_heping
Author Name: Wang, Xibin
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_xibin
Author Name: Ren, Zhuanqin
Author link: https://covid19-data.nist.gov/pid/rest/local/author/ren_zhuanqin
Author Name: Yang, Jian
Author link: https://covid19-data.nist.gov/pid/rest/local/author/yang_jian
sha: 895127ea70efc939b88c0a84b888338dddaec5a6
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Medline; PMC
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 33072703
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/33072703
pmcid: PMC7531052
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7531052
url: https://doi.org/10.3389/fpubh.2020.567672 https://www.ncbi.nlm.nih.gov/pubmed/33072703/
has_full_text: TRUE
Keywords Extracted from Text Content: patients coronavirus men alveolar C-reactive pattern-categories 18.90 [1.91-186.60 Pattern 3-4 COVID-19 pulmonary troponin I Hubei province COVID-19 (11) CJ chest CT twophenotype Wuhan 19.1.7 Patients lobes Lung lobar tissue USA ZLi IL H1N1 upper thoracic OP lungs HZho, XW cardiovascular fibrin Xi'an Jiaotong SC, YL, lung lobes human participants SARS-CoV-2 HL OP-like Axial D-dimer three-phenotype Shaanxi province COVID-19 Axial CT interlobular septal 5,704 quick-test People's Republic Hanzhong patient pleural lobar H1N1 pneumonia ≥65 coronavirus lymphadenopathy intraalveolar edema oxygen HZha, TL lesions tube creatine bronchovascular bundles bronchial ZR lung woman peripheral pulmonary CT cellular infiltrates leukocyte COVID-19 (16) GGO Coronavirus body hyaline membrane woman COVID-19 barotrauma alveolar five-phenotype lobe lung zones DAD patients Xi'an C-reactive lymphocyte DAD Ankang patients neutrophil H COVID-19 patients influenza A pulmonary https://www.frontiersin.org/articles/10.3389/fpubh participants
Extracted Text Content in Record: First 5000 Characters:Background: As global healthcare system is overwhelmed by novel coronavirus disease , 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. Jin et al. CT Pattern Categorization of COVID-19 Conclusion: CT pattern categorization allied with clinical characteristics within 2 weeks after symptom onset would facilitate early prognostic stratification in COVID-19 pneumonia. Since the latter part of December of 2019, an outbreak of respiratory disease caused by severe acute respiratory syndromecoronavirus-2 (SARS-CoV-2) has become a pandemic (1) . As of May 29, 2020, 5,704 ,736 laboratory-confirmed cases and 357,736 deaths have been reported (2) . Numerous studies have revealed the epidemiological, clinical, and radiological characteristics of the novel coronavirus disease (COVID-19) (3) (4) (5) (6) . Despite the fact that more than 80% of infected patients manifest with only mild clinical symptoms (3) , early identifying the risks of an adverse outcome remains the key to optimize management and improve survival. Previous studies found that advanced age and presence of comorbidity (e.g., cardiovascular disease or hypertension) were risk factors associated with an adverse outcome such as admission to intensive care unit (ICU), need for mechanical ventilation, or death (7, 8) . In addition, some laboratory indicators e.g., elevated hypersensitive troponin I, leukocytosis, neutrophilia, lymphopenia, and elevated D-dimer were found to be linked with unfavorable clinical outcomes (7) (8) (9) . Presence of consolidation on computed tomography (CT) was also considered to be predictive of poor outcome in COVID-19 (10) . Despite the above, the identification of early prognostic signs of COVID-19 remains of urgent importance due to the diversity in clinical and imaging findings as well as the severity and rapid progression of disease. It is recognized that CT plays a central role in diagnosis and management of COVID-19 pneumonia (11) (12) (13) . Reported CT findings of COVID-19 pneumonia included the ground glass opacities (GGO), consolidation, septal thickening mainly along the subpleural lungs or bronchovascular bundles or diffusely in the entire lungs (14) . These are highly suggestive of lung organization response to injury from COVID-19 pneumonia, similar to radiological findings in the diffuse alveolar damage (DAD) and organizing pneumonia (OP) (15) . Pathological studies also observed DAD in patients who succumbed to COVID-19 (16) . Previous studies have demonstrated a decreased survival rate of 35-50% in DAD, while most patients with OP had better prognosis (15) . In this regard, a pattern categorization of COVID-19 pneumonia, i.e., DAD and OP patterns may help the prognostic stratification. Based on the prior study regarding influenza A (H1N1) pneumonia (17) , Lee also suggested a pattern categorization of COVID-19, i.e., bronchopneumonia, OP and DAD (18) . A rapid progression of OP-like injury in Severe Acute Respiratory Syndrome (SARS) was considered to be predictive of a protracted clinical course (19) . This may suggest a progressive subtype of OP pattern. Based on the aforementioned knowledge, a CT pattern categorization of COVID-19 pneumonia, i.e., br
Keywords Extracted from PMC Text: HZha, TL 11–13 hyaline membrane five-phenotype HL Hubei province interlobular septal women pulmonary CT upper thoracic CJ GE VCT Hanzhong lungs GE Optima 680 DAD human participants quick-test tube lobar barotrauma COVID-19 (16) Xi'an fibrin cellular infiltrates Patients GE men oxygen troponin I COVID-19 (11) GE LightSpeed 16 lymphadenopathy OP patients 14–58 lung SC, YL, neutrophil coronavirus COVID-19 creatine IL Ankang Xi'an Jiaotong Shaanxi province SARS-CoV-2 lymphocyte alveolar lobes Wuhan 23–25 5,704,736 body ZLi Coronavirus three-phenotype influenza A cardiovascular COVID-19 patients H1N1 pneumonia USA pleural 10–41 DAD patients lobe HZho, XW pulmonary bronchovascular bundles leukocyte lung lobes lecture- D-dimer People's Republic ≥65 GGO OP-like lesions C-reactive chest ZR 7–9 19.1.7 intraalveolar edema chest CT 8–49 H1N1 patient tissue three-phenotype (24).
Extracted PMC Text Content in Record: First 5000 Characters:Since the latter part of December of 2019, an outbreak of respiratory disease caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has become a pandemic (1). As of May 29, 2020, 5,704,736 laboratory-confirmed cases and 357,736 deaths have been reported (2). Numerous studies have revealed the epidemiological, clinical, and radiological characteristics of the novel coronavirus disease (COVID-19) (3–6). Despite the fact that more than 80% of infected patients manifest with only mild clinical symptoms (3), early identifying the risks of an adverse outcome remains the key to optimize management and improve survival. Previous studies found that advanced age and presence of comorbidity (e.g., cardiovascular disease or hypertension) were risk factors associated with an adverse outcome such as admission to intensive care unit (ICU), need for mechanical ventilation, or death (7, 8). In addition, some laboratory indicators e.g., elevated hypersensitive troponin I, leukocytosis, neutrophilia, lymphopenia, and elevated D-dimer were found to be linked with unfavorable clinical outcomes (7–9). Presence of consolidation on computed tomography (CT) was also considered to be predictive of poor outcome in COVID-19 (10). Despite the above, the identification of early prognostic signs of COVID-19 remains of urgent importance due to the diversity in clinical and imaging findings as well as the severity and rapid progression of disease. It is recognized that CT plays a central role in diagnosis and management of COVID-19 pneumonia (11–13). Reported CT findings of COVID-19 pneumonia included the ground glass opacities (GGO), consolidation, septal thickening mainly along the subpleural lungs or bronchovascular bundles or diffusely in the entire lungs (14). These are highly suggestive of lung organization response to injury from COVID-19 pneumonia, similar to radiological findings in the diffuse alveolar damage (DAD) and organizing pneumonia (OP) (15). Pathological studies also observed DAD in patients who succumbed to COVID-19 (16). Previous studies have demonstrated a decreased survival rate of 35–50% in DAD, while most patients with OP had better prognosis (15). In this regard, a pattern categorization of COVID-19 pneumonia, i.e., DAD and OP patterns may help the prognostic stratification. Based on the prior study regarding influenza A (H1N1) pneumonia (17), Lee also suggested a pattern categorization of COVID-19, i.e., bronchopneumonia, OP and DAD (18). A rapid progression of OP-like injury in Severe Acute Respiratory Syndrome (SARS) was considered to be predictive of a protracted clinical course (19). This may suggest a progressive subtype of OP pattern. Based on the aforementioned knowledge, a CT pattern categorization of COVID-19 pneumonia, i.e., bronchopneumonia, OP, progressive OP and DAD may have potential prognostic implications, e.g., adverse outcome, clinical course with recovery. As healthcare systems in many countries are overwhelmed with COVID-19 patients, improved prediction of the course of the disease based on early findings can assist with improved utilization of limited resources. To this end, this study aimed to investigate the prognostic significance of a CT pattern categorization in conjunction with the clinical indicators on clinical outcome and pulmonary sequelae in COVID-19. The internal review board approved this retrospective study. Written informed consent was waived with approval. Between January 22, and March 16, 2020, 172 laboratory-confirmed COVID-19 patients who underwent chest CT were collected from eight hospitals in China. The cases were from four regions (Xi'an, n = 80; Baoji, n = 10; Ankang, n = 18; Hanzhong, n = 17) in Shaanxi province and Wuhan (n = 47) in Hubei province. A case of COVID-19 was confirmed by a positive result on next-generation sequencing or real-time RT-PCR. The disease type, i.e., uncomplicated illness, mild pneumonia, severe pneumonia, critical illness (acute respiratory distress syndrome, sepsis or septic shock) was evaluated based on the criteria published by World Health Organization (WHO) (20). All the patients were treated based on Diagnosis and Treatment Protocol for Novel Coronavirus Pneumonia (Trial Version 7) issued by National Health Commission of the People's Republic of China, which includes initiation of antivirals, interferon, Chinese herbal medications, supplemental oxygen as needed and hospitalization. The criteria for patient discharge with recovery included: (1) afebrile for >3 days, (2) improved respiratory symptoms, (3) chest imaging shows obvious resolution of inflammation, and (4) two consecutively negative nucleic acid test results (sampling interval ≥1 day) (21). The recommendations for discharged patients included (1) 14 days of isolation management and health monitoring; (2) follow-up hospital visits with a next-generation sequencing or real-time RT-PCR test and chest CT scan to detect whether there exist a positive return and/or
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