3 research outputs found
Additional file 3: Figure S2. of Chronic hypersensitivity pneumonitis: identification of key prognostic determinants using automated CT analysis
Brief description of data: Survival curves comparing poor-outcome (defined using an FVC threshold >50% predicted) chronic hypersensitivity pneumonitis patients and idiopathic pulmonary fibrosis patients using Kaplan Meier curve analysis. (PNG 80 kb
Additional file 1 of A formula for predicting emphysema extent in combined idiopathic pulmonary fibrosis and emphysema
Supplementary Material
Residual Lung Abnormalities Following COVID-19 Hospitalization:Interim Analysis of the UKILD Post-COVID Study
RationaleShared symptoms and genetic architecture between COVID-19 and lung fibrosis suggests SARS-CoV-2 infection may lead to progressive lung damage.ObjectivesThe UKILD Post-COVID study interim analysis was planned to estimate the prevalence of residual lung abnormalities in people hospitalized with COVID-19 based on risk strata.MethodsThe Post-HOSPitalisation COVID Study (PHOSP-COVID) was used for capture of routine and research follow-up within 240 days from discharge. Thoracic CTs linked by PHOSP-COVID identifiers were scored for percentage of residual lung abnormalities (ground glass opacities and reticulations). Risk factors in linked CT were estimated with Bayesian binomial regression and risk strata were generated. Numbers within strata were used to estimate post-hospitalization prevalence using Bayesian binomial distributions. Sensitivity analysis was restricted to participants with protocol driven research follow-up.Measurements and main resultsThe interim cohort comprised 3700 people. Of 209 subjects with linked CTs (median 119 days, interquartile range 83-155), 166 people (79.4%) had >10% involvement of residual lung abnormalities. Risk factors included abnormal chest X-ray (RR 1路21 95%CrI 1路05; 1路40), percent predicted DLcoConclusionsResidual lung abnormalities were estimated in up to 11% of people discharged following COVID-19 related hospitalization. Health services should monitor at-risk individuals to elucidate long-term functional implications. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)