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Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning
PURPOSE: Using computer-aided diagnosis (CAD) methods to analyze the discharge and 6-month follow-up data of COVID-19 Delta variant survivors, evaluate and summarize the recovery and prognosis, and improve people's awareness of this disease. METHODS: This study collected clinical data, SGRQ que...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932267/ https://www.ncbi.nlm.nih.gov/pubmed/36817788 http://dx.doi.org/10.3389/fmed.2023.1103559 |
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author | Huang, Jianliang Lin, Ruikai Bai, Na Su, Zhongrui Zhu, Mingxin Li, Han Chai, Conghai Xia, Mingkai Shu, Ziwei Qiu, Zhaowen Lei, Mingsheng |
author_facet | Huang, Jianliang Lin, Ruikai Bai, Na Su, Zhongrui Zhu, Mingxin Li, Han Chai, Conghai Xia, Mingkai Shu, Ziwei Qiu, Zhaowen Lei, Mingsheng |
author_sort | Huang, Jianliang |
collection | PubMed |
description | PURPOSE: Using computer-aided diagnosis (CAD) methods to analyze the discharge and 6-month follow-up data of COVID-19 Delta variant survivors, evaluate and summarize the recovery and prognosis, and improve people's awareness of this disease. METHODS: This study collected clinical data, SGRQ questionnaire results, and lung CT scans (at both discharge and 6-month follow-up) from 41 COVID-19 Delta variant survivors. Two senior radiologists evaluated the CT scans before in-depth analysis. Deep lung parenchyma enhancing (DLPE) method was used to accurately segment conventional lesions and sub-visual lesions in CT images, and then quantitatively analyze lung injury and recovery. Patient recovery was also measured using the SGRQ questionnaire. The follow-up examination results from this study were combined with those of the original COVID-19 for further comparison. RESULTS: The participants include 13 males (31.7%) and 28 females (68.3%), with an average age of 42.2 ± 17.7 years and an average BMI of 25.2 ± 4.4 kg/m(2). Compared discharged CT and follow-up CT, 48.8% of survivors had pulmonary fibrosis, mainly including irregular lines (34.1%), punctuate calcification (12.2%) and nodules (12.2%). Compared with discharged CT, the ground-glass opacity basically dissipates at follow-up. The mean SGRQ score was 0.041 (0–0.104). The sequelae of survivors mainly included impaired sleep quality (17.1%), memory decline (26.8%), and anxiety (21.9%). After DLPE process, the lesion volume ratio decreased from 0.0018 (0.0003, 0.0353) at discharge to 0.0004 (0, 0.0032) at follow-up, p < 0.05, and the absorption ratio of lesion was 0.7147 (–1.0303, 0.9945). CONCLUSION: The ground-glass opacity of survivors had dissipated when they were discharged from hospital, and a little fibrosis was seen in CT after 6-month, mainly manifested as irregular lines, punctuate calcification and nodules. After DLPE and quantitative calculations, we found that the degree of fibrosis in the lungs of most survivors was mild, which basically did not affect lung function. However, there are a small number of patients with unabsorbed or increased fibrosis. Survivors mainly had non-pulmonary sequelae such as impaired sleep quality and memory decline. Pulmonary prognosis of Delta variant patients was better than original COVID-19, with fewer and milder sequelae. |
format | Online Article Text |
id | pubmed-9932267 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99322672023-02-17 Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning Huang, Jianliang Lin, Ruikai Bai, Na Su, Zhongrui Zhu, Mingxin Li, Han Chai, Conghai Xia, Mingkai Shu, Ziwei Qiu, Zhaowen Lei, Mingsheng Front Med (Lausanne) Medicine PURPOSE: Using computer-aided diagnosis (CAD) methods to analyze the discharge and 6-month follow-up data of COVID-19 Delta variant survivors, evaluate and summarize the recovery and prognosis, and improve people's awareness of this disease. METHODS: This study collected clinical data, SGRQ questionnaire results, and lung CT scans (at both discharge and 6-month follow-up) from 41 COVID-19 Delta variant survivors. Two senior radiologists evaluated the CT scans before in-depth analysis. Deep lung parenchyma enhancing (DLPE) method was used to accurately segment conventional lesions and sub-visual lesions in CT images, and then quantitatively analyze lung injury and recovery. Patient recovery was also measured using the SGRQ questionnaire. The follow-up examination results from this study were combined with those of the original COVID-19 for further comparison. RESULTS: The participants include 13 males (31.7%) and 28 females (68.3%), with an average age of 42.2 ± 17.7 years and an average BMI of 25.2 ± 4.4 kg/m(2). Compared discharged CT and follow-up CT, 48.8% of survivors had pulmonary fibrosis, mainly including irregular lines (34.1%), punctuate calcification (12.2%) and nodules (12.2%). Compared with discharged CT, the ground-glass opacity basically dissipates at follow-up. The mean SGRQ score was 0.041 (0–0.104). The sequelae of survivors mainly included impaired sleep quality (17.1%), memory decline (26.8%), and anxiety (21.9%). After DLPE process, the lesion volume ratio decreased from 0.0018 (0.0003, 0.0353) at discharge to 0.0004 (0, 0.0032) at follow-up, p < 0.05, and the absorption ratio of lesion was 0.7147 (–1.0303, 0.9945). CONCLUSION: The ground-glass opacity of survivors had dissipated when they were discharged from hospital, and a little fibrosis was seen in CT after 6-month, mainly manifested as irregular lines, punctuate calcification and nodules. After DLPE and quantitative calculations, we found that the degree of fibrosis in the lungs of most survivors was mild, which basically did not affect lung function. However, there are a small number of patients with unabsorbed or increased fibrosis. Survivors mainly had non-pulmonary sequelae such as impaired sleep quality and memory decline. Pulmonary prognosis of Delta variant patients was better than original COVID-19, with fewer and milder sequelae. Frontiers Media S.A. 2023-02-02 /pmc/articles/PMC9932267/ /pubmed/36817788 http://dx.doi.org/10.3389/fmed.2023.1103559 Text en Copyright © 2023 Huang, Lin, Bai, Su, Zhu, Li, Chai, Xia, Shu, Qiu and Lei. https://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 | Medicine Huang, Jianliang Lin, Ruikai Bai, Na Su, Zhongrui Zhu, Mingxin Li, Han Chai, Conghai Xia, Mingkai Shu, Ziwei Qiu, Zhaowen Lei, Mingsheng Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title | Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title_full | Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title_fullStr | Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title_full_unstemmed | Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title_short | Six-month follow-up after recovery of COVID-19 Delta variant survivors via CT-based deep learning |
title_sort | six-month follow-up after recovery of covid-19 delta variant survivors via ct-based deep learning |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9932267/ https://www.ncbi.nlm.nih.gov/pubmed/36817788 http://dx.doi.org/10.3389/fmed.2023.1103559 |
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