Dataset Information

Clinical Profile and Determinants of Mortality in Patients with Interstitial Lung Disease Admitted for COVID-19.

ABSTRACT:

Background

Concern has risen about the effects of COVID-19 in interstitial lung disease (ILD) patients. The aim of our study was to determine clinical characteristics and prognostic factors of ILD patients admitted for COVID-19.

Methods

Ancillary analysis of an international, multicenter COVID-19 registry (HOPE: Health Outcome Predictive Evaluation) was performed. The subgroup of ILD patients was selected and compared with the rest of the cohort.

Results

A total of 114 patients with ILDs were evaluated. Mean ± SD age was 72.4 ± 13.6 years, and 65.8% were men. ILD patients were older, had more comorbidities, received more home oxygen therapy and more frequently had respiratory failure upon admission than non-ILD patients (all p < 0.05). In laboratory findings, ILD patients more frequently had elevated LDH, C-reactive protein, and D-dimer levels (all p < 0.05). A multivariate analysis showed that chronic kidney disease and respiratory insufficiency on admission were predictors of ventilatory support, and that older age, kidney disease and elevated LDH were predictors of death.

Conclusions

Our data show that ILD patients admitted for COVID-19 are older, have more comorbidities, more frequently require ventilatory support and have higher mortality than those without ILDs. Older age, kidney disease and LDH were independent predictors of mortality in this population.

SUBMITTER: Mulet A

PROVIDER: S-EPMC10253326 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Publications

Clinical Profile and Determinants of Mortality in Patients with Interstitial Lung Disease Admitted for COVID-19.

Mulet Alba A Núñez-Gil Iván J IJ Carbonell Juan Antonio JA Soriano Joan B JB Viana-Llamas María C MC Raposeiras-Roubin Sergio S Romero Rodolfo R Alfonso-Rodríguez Emilio E Uribarri Aitor A Feltes Gisela G Becerra-Muñoz Victor M VM Santoro Francesco F Pepe Martino M Castro-Mejía Alex F AF Chipayo David D Corbi-Pascual Miguel M López-Pais Javier J Vedia Oscar O Manzone Edoardo E Molina-Romera Germán G Espejo-Paeres Carolina C López-Masjuan Álvaro Á Velicki Lazar L Fernández-Ortiz Antonio A El-Battrawy Ibrahim I Signes-Costa Jaime J On Behalf Of Hope Team

Journal of clinical medicine 20230602 11

<h4>Background</h4>Concern has risen about the effects of COVID-19 in interstitial lung disease (ILD) patients. The aim of our study was to determine clinical characteristics and prognostic factors of ILD patients admitted for COVID-19.<h4>Methods</h4>Ancillary analysis of an international, multicenter COVID-19 registry (HOPE: Health Outcome Predictive Evaluation) was performed. The subgroup of ILD patients was selected and compared with the rest of the cohort.<h4>Results</h4>A total of 114 pati ...[more]

PMID: 37298018

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Project description:Background: We previously identified a 50-gene signature that distinguished two groups of patients with increased risk of COVID-19 and IPF mortality. In this study we aimed to validate our previous findings and to study the source and trajectory of circulating immune cells expressing these 50 genes in patients with COVID19, post-COVID-19 Interstitial Lung Disease (ILD) and Idiopathic Pulmonary Fibrosis (IPF). Methods: Whole blood and Peripheral Blood Mononuclear cells (PBMC) were obtained from 216 hospitalized patients with COVID-19, five patients with post-COVID-19-ILD, six patients with IPF and four controls from the University of South Florida (USF)/Tampa General Hospital (TGH). We measured the expression of the 50-gene signature using the nCounter analysis system (Nanostring), and the levels of Interleukin 6 (IL6), interferon γ-induced protein (IP10), Secreted Phosphoprotein 1 (SPP1) and transforming growth factor beta (TGF-β) in these patients by Luminex and Elisa tests. A 7-gene PCR assay was generated to validate the identification of COVID-19 endotypes. For single-cell RNA sequencing (scRNA-seq) we used Chromium Single Cell Controller (10X Genomics). For analysis of gene expression, we used the Scoring Algorithm of Molecular Subphenotypes (SAMS), Cell Ranger and Seurat packages. For statistical analysis, we used Kaplan-Meier survival curves, CoxPH models, Two-way ANOVA, T-test, Fisher’s exact and the Wilcoxon rank test. Results: We identified the presence of three genomic risk profiles based on the 50-gene signature, and a subset of seven genes, associated with low, intermediate, or high-risk of mortality in COVID-19. These risk groups had significant differences in IL6, IP10, SPP1 and TGFβ-1 levels. By applying scRNA-seq, we discovered a novel subtype of Monocytic-Myeloid-Derived Suppressive cells (M-MDSCs) expressing CD14+HLA DRlowCD163+ and high levels of the 7-gene signature. We denominated these cells as 7Gene-M-MDSC. These cells were not observed in survivors with post-COVID-19-ILD. The 43-gene signature was mostly expressed in naive CD4 T and memory CD4 T cells, Tregs, memory CD8 T GZMB+, memory CD8 T GZMK+ and naive CD8 T cells. While increased expression of genes in the 43 gene signature was seen in T cell subsets from survivors with post-COVID-19 ILD, the expression of these genes remained low in IPF. Conclusion: A 50-gene, high-risk genomic profile in peripheral blood of COVID-19 can accurately predict COVID-19 mortality. This profile is characterized by a simultaneous increase in expression of seven genes originating from 7Gene-M-MDSCs and decreased expression of 43 genes originating primarily in T cell subsets. While increased expression of these 43 genes can be seen in survivors with post-COVID-19 ILD, their expression remains low in IPF.

Dataset Information

Clinical Profile and Determinants of Mortality in Patients with Interstitial Lung Disease Admitted for COVID-19.

Background

Methods

Results

Conclusions

Publications

Clinical Profile and Determinants of Mortality in Patients with Interstitial Lung Disease Admitted for COVID-19.

Similar Datasets

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