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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia

Published on: December 19, 2020

COVID-19 pulmonary phenotypes and longitudinal patterns in the first wave of the pandemic

Davide Chimera¹, Sara Maio², Chiara Romei³

¹Pulmonary Unit, Cardiothoracic and Vascular Department, Pisa University Hospital, Pisa, Italy.

Respiratory Medicine

|January 18, 2025

Insights

Long COVID can cause persistent lung issues. This study identified distinct pulmonary phenotypes and recovery patterns in first-wave COVID-19 patients, with severe cases and comorbidities indicating longer-term lung problems.

Area of Science:

Pulmonology
Infectious Diseases
Epidemiology

Background:

Long-term pulmonary evolution in first-wave COVID-19 patients is understudied.
Understanding post-COVID-19 lung phenotypes is crucial for patient management.

Purpose of the Study:

To identify COVID-19 pulmonary phenotypes.
To analyze longitudinal recovery patterns over 12 months post-hospitalization.
To determine risk factors associated with specific recovery trajectories.

Main Methods:

Latent transition analysis (LTA) applied to spirometry, lung volumes, DLCO, and chest CT data.
Follow-up assessments at 3, 12, and 24 months post-discharge.
Multinomial logistic regression used to identify risk factors.

Main Results:

Three cross-sectional phenotypes (no PS/normal PFTs, PS/normal PFTs, PS/impaired PFTs) identified at 3 and 12 months.
Four longitudinal patterns from 3 to 12 months: full recovery, resolution of PS, persistent PS with normal PFTs, persistent PS with impaired PFTs.
Persistent pulmonary issues (PS and/or impaired PFTs) observed in a significant proportion up to 24 months, linked to hospitalization duration, comorbidities, and disease severity.

Conclusions:

Distinct pulmonary phenotypes and longitudinal recovery patterns exist in first-wave COVID-19 survivors.
Comorbidities and severe acute COVID-19 are associated with poorer long-term pulmonary outcomes.
Long-term monitoring is recommended for high-risk COVID-19 patients.

Read full analysis

Abstract

Background:

The long-term evolution of COVID-19 in patients hospitalized during the pandemic's first wave remains largely unexplored. This study aimed to identify COVID-19 pulmonary phenotypes and their longitudinal patterns over a 12-month follow-up.

Methods:

COVID-19 patients discharged from Pisa University Hospital (Italy) between March-September 2020, were evaluated at T3, T12, and T24 months post-discharge. Assessments included spirometry, lung volumes, DLCO, and chest CT for those with persistent pneumonia signs (PS). Latent transition analysis (LTA) identified COVID-19 phenotypes and longitudinal patterns based on PS and lung function (PFTs). Risk factors for these patterns were evaluated using multinomial logistic regression.

Results:

Of 307 discharged patients, 175, 136, and 33 were followed-up at T3, T12, and T24, respectively. At T12, 21.6 % had impaired DLCO, 4.4 % a restrictive ventilatory pattern, and 31,6 % still had PS, persisting until T24. LTA identified three cross-sectional phenotypes at both T3 and T12 (no PS with normal PFTs; PS with normal PFTs; PS with impaired PFTs), and four longitudinal patterns from T3 to T12: persistence of no PS with normal PFTs (47.9 %); resolution of both PS and PFTs (15.4 %); persistent PS (36.7 %), either with (11 %) or without (25.7 %) impaired PFTs. The last two patterns correlated significantly with longer hospitalization, more comorbidities, and severe COVID-19.

Conclusions:

In our cohort of COVID-19 patients hospitalized during the pandemic's first wave, we observed distinct pulmonary phenotypes and longitudinal recovery patterns. More comorbidities and severe acute disease correlated with worse progression up to 24 months, suggesting long-term monitoring for such patients.

Keywords:

COVID-19 Follow-up Imaging Latent transition analysis Lung function

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