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Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19

AIM: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. MATERIAL AND METHODS: A cross sectional study...

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Autores principales: Rajalingam, Bavaharan, Narayanan, Ethirajan, Nirmalan, Praveen, Muthukrishnan, Kamalanthan, Sundaram, Vivek, Kumaravelu, Saravanan, Gopalan, Mukundhan, Jeyapal, Senthil, Rajalingam, Baskaran, Khanna, Vijay, Dhoss, Praveen, Gopinath
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996691/
https://www.ncbi.nlm.nih.gov/pubmed/33814769
http://dx.doi.org/10.4103/ijri.IJRI_774_20
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author Rajalingam, Bavaharan
Narayanan, Ethirajan
Nirmalan, Praveen
Muthukrishnan, Kamalanthan
Sundaram, Vivek
Kumaravelu, Saravanan
Gopalan, Mukundhan
Jeyapal, Senthil
Rajalingam, Baskaran
Khanna, Vijay
Dhoss, Praveen
Gopinath,
author_facet Rajalingam, Bavaharan
Narayanan, Ethirajan
Nirmalan, Praveen
Muthukrishnan, Kamalanthan
Sundaram, Vivek
Kumaravelu, Saravanan
Gopalan, Mukundhan
Jeyapal, Senthil
Rajalingam, Baskaran
Khanna, Vijay
Dhoss, Praveen
Gopinath,
author_sort Rajalingam, Bavaharan
collection PubMed
description AIM: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. MATERIAL AND METHODS: A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. RESULTS: The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value <0.001). CONCLUSION: HRCT chest and assessment of lung patterns can help triage patients to home quarantine and hospital admission. Early initiation of steroids and anticoagulants based on lung patterns can prevent progression to more severe stages and aid early recovery. HRCT can play a major role to triage and guide management especially as RT PCR testing and results are delayed for the benefit of patients and in a social cause to decrease the spread of the virus
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spelling pubmed-79966912021-04-01 Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19 Rajalingam, Bavaharan Narayanan, Ethirajan Nirmalan, Praveen Muthukrishnan, Kamalanthan Sundaram, Vivek Kumaravelu, Saravanan Gopalan, Mukundhan Jeyapal, Senthil Rajalingam, Baskaran Khanna, Vijay Dhoss, Praveen Gopinath, Indian J Radiol Imaging Original Article AIM: To describe the distribution of lung patterns determined by High Resolution Computed Tomography (HRCT) in COVID patients with mild and moderate lung involvement and outcomes after early identification and management with steroids and anticoagulants. MATERIAL AND METHODS: A cross sectional study of COVID-19 patients with mild and moderate lung involvement presenting at 5 healthcare centres in Trichy district of South TamilNadu in India. Patients underwent HRCT to assess patterns and severity of lung involvement, Inflammatory markers (LDH/Ferritin) and D-Dimer assay and clinical correlation with signs and symptoms. Patients were assessed for oxygen, steroid and anticoagulant therapy, clinical recovery or progression on follow up and details on mortality were collected. The RSNA, Fleischer Society guidelines and CORADS score was used for radiological reporting. New potential classification of patterns of percentage of lung parenchyma involvement in Covid patients is being suggested. RESULTS: The study included 7,340 patients with suspected COVID and 3,963 (53.9%) patients had lung involvement based on HRCT. RT PCR was positive in 74.1% of the CT Positive cases. Crazy Pavement pattern was predominant (n = 2022, 51.0%) and Ground Glass Opacity (GGO) was found in 1,941 (49.0%) patients in the study. Severe lung involvement was more common in the Crazy Pavement pattern. Patients with GGO in moderate lung involvement were significantly more likely to recover faster compared to Crazy Pavement pattern (P value <0.001). CONCLUSION: HRCT chest and assessment of lung patterns can help triage patients to home quarantine and hospital admission. Early initiation of steroids and anticoagulants based on lung patterns can prevent progression to more severe stages and aid early recovery. HRCT can play a major role to triage and guide management especially as RT PCR testing and results are delayed for the benefit of patients and in a social cause to decrease the spread of the virus Wolters Kluwer - Medknow 2021-01 2021-01-23 /pmc/articles/PMC7996691/ /pubmed/33814769 http://dx.doi.org/10.4103/ijri.IJRI_774_20 Text en Copyright: © 2021 Indian Journal of Radiology and Imaging http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Rajalingam, Bavaharan
Narayanan, Ethirajan
Nirmalan, Praveen
Muthukrishnan, Kamalanthan
Sundaram, Vivek
Kumaravelu, Saravanan
Gopalan, Mukundhan
Jeyapal, Senthil
Rajalingam, Baskaran
Khanna, Vijay
Dhoss, Praveen
Gopinath,
Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title_full Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title_fullStr Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title_full_unstemmed Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title_short Pattern recognition of high-resolution computer tomography (HRCT) chest to guide clinical management in patients with mild to moderate COVID-19
title_sort pattern recognition of high-resolution computer tomography (hrct) chest to guide clinical management in patients with mild to moderate covid-19
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996691/
https://www.ncbi.nlm.nih.gov/pubmed/33814769
http://dx.doi.org/10.4103/ijri.IJRI_774_20
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