Peripheral Blood Gene Expression Changes Predict Mortality and Treatment Response in Acute Covid-19 and Associate with Lung Fibrosis

Tourki, Bochra; Vera, I.; Perrot, C.; Farsaei, Forouzandeh; Arsenault, A.; Juan-Guardela, Brenda; Allen, D.; Jaramillo, R. Restrepo; Bandyopadhyay, D.; Belli, Erol V.; Katlaps, Gundars; Patel, Krishen; Liggett, Stephen B.; Kim, K.; Herazo-Maya, José D.

doi:10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a3929

Cited by 2 publications

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“…If not, a less abundant expression of genes that are directly related with monocytes, might mean a gradual "immune recovery" in post-COVID-19-ILD and probably a favorable long-term course. Contrary to IPF, persistence of monocytes and impaired T cell response might not be the case in post-COVID-19-ILD, as the epithelial injury happened only in the acute phase of infection and is not repetitive (17,18). Studies implementing single-cell RNA-sequencing to compare post-COVID-19-ILD and IPF could hopefully address this unmet need and help clinicians "predict" the long-term outcomes of patients with post-COVID-19-ILD.…”

Section: Editorial On the Research Topic Immune-mediated Lung Injurymentioning

confidence: 99%

Editorial: Immune-mediated lung injury

Karampitsakos,

Spagnolo,

Tzouvelekis

2023

Front. Med.

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Section: Editorial On the Research Topic Immune-mediated Lung Injurymentioning

confidence: 99%

Editorial: Immune-mediated lung injury

Karampitsakos,

Spagnolo,

Tzouvelekis

2023

Front. Med.

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Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model

et al. 2023

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IntroductionPost-acute sequelae of COVID-19 seem to be an emerging global crisis. Machine learning radiographic models have great potential for meticulous evaluation of post-COVID-19 interstitial lung disease (ILD).MethodsIn this multicenter, retrospective study, we included consecutive patients that had been evaluated 3 months following severe acute respiratory syndrome coronavirus 2 infection between 01/02/2021 and 12/5/2022. High-resolution computed tomography was evaluated through Imbio Lung Texture Analysis 2.1.ResultsTwo hundred thirty-two (n = 232) patients were analyzed. FVC% predicted was ≥80, between 60 and 79 and <60 in 74.2% (n = 172), 21.1% (n = 49), and 4.7% (n = 11) of the cohort, respectively. DLCO% predicted was ≥80, between 60 and 79 and <60 in 69.4% (n = 161), 15.5% (n = 36), and 15.1% (n = 35), respectively. Extent of ground glass opacities was ≥30% in 4.3% of patients (n = 10), between 5 and 29% in 48.7% of patients (n = 113) and <5% in 47.0% of patients (n = 109). The extent of reticulation was ≥30%, 5–29% and <5% in 1.3% (n = 3), 24.1% (n = 56), and 74.6% (n = 173) of the cohort, respectively. Patients (n = 13, 5.6%) with fibrotic lung disease and persistent functional impairment at the 6-month follow-up received antifibrotics and presented with an absolute change of +10.3 (p = 0.01) and +14.6 (p = 0.01) in FVC% predicted at 3 and 6 months after the initiation of antifibrotic.ConclusionPost-COVID-19-ILD represents an emerging entity. A substantial minority of patients presents with fibrotic lung disease and might experience benefit from antifibrotic initiation at the time point that fibrotic-like changes are “immature.” Machine learning radiographic models could be of major significance for accurate radiographic evaluation and subsequently for the guidance of therapeutic approaches.

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Peripheral Blood Gene Expression Changes Predict Mortality and Treatment Response in Acute Covid-19 and Associate with Lung Fibrosis

Cited by 2 publications

References 0 publications

Editorial: Immune-mediated lung injury

Editorial: Immune-mediated lung injury

Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model

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