associations between severe pulmonary function and residual ct abnormalities in rehabilitating CORD-Papers-2022-06-02 (Version 1)

Title: Associations between severe pulmonary function and residual CT abnormalities in rehabilitating COVID-19 patients
Abstract: OBJECTIVE: Coronavirus disease 2019 (COVID-19) spread around the world in 2020. Abnormal pulmonary function and residual CT abnormalities were observed in COVID-19 patients during recovery. Appropriate rehabilitation training is around the corner. The correlation between spirometric impairment and residual CT abnormality remains largely unknown. PATIENTS AND METHODS: A cross-sectional study conducted on the pulmonary function of 101 convalescent COVID-19 patients before discharge. Multivariate analysis was used to establish a scoring system to evaluate the spirometric abnormality based on residual chest CT. RESULTS: Lung consolidation area >25% and severe-type COVID-19 were two independent risk factors for severe pulmonary dysfunction. Besides a scoring system was established. People scoring more than 12 points have more chances (17 times) to get severe pulmonary function impairment before discharge. CONCLUSIONS: For the first time a chest CT characteristics-based grading system was suggested to predict the pulmonary dysfunction of COVID-19 patients during convalescence in this study. This study may provide suggestions for pulmonary rehabilitation.
Published: 2021
Journal: European Review for Medical and Pharmacological Sciences
Author Name: Yu C
Author link: https://covid19-data.nist.gov/pid/rest/local/author/yu_c
Author Name: Hu X Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hu_x_y
Author Name: Zou C
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zou_c
Author Name: Yu F F
Author link: https://covid19-data.nist.gov/pid/rest/local/author/yu_f_f
Author Name: Liu B
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_b
Author Name: Li Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_y
Author Name: Liu Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/liu_y
Author Name: Song L J
Author link: https://covid19-data.nist.gov/pid/rest/local/author/song_l_j
Author Name: Tan L
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tan_l
Author Name: Li Q
Author link: https://covid19-data.nist.gov/pid/rest/local/author/li_q
Author Name: Hu Y C
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hu_y_c
Author Name: He H Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/he_h_y
Author Name: Chen M Y
Author link: https://covid19-data.nist.gov/pid/rest/local/author/chen_m_y
Author Name: Zou Z
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zou_z
license: unk
license_url: [unknown license]
source_x: WHO
source_x_url: https://www.who.int/
who_covidence_id: #covidwho-1576100
has_full_text: FALSE
G_ID: associations_between_severe_pulmonary_function_and_residual_ct_abnormalities_in_rehabilitating