Skip to main content
Journal cover image

Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation.

Publication ,  Journal Article
Eddy, RL; Mummy, D; Zhang, S; Dai, H; Bechtel, A; Schmidt, A; Frizzell, B; Gerayeli, FV; Leipsic, JA; Leung, JM; Driehuys, B; Que, LG ...
Published in: Eur Respir J
February 8, 2024

BACKGROUND: Long COVID impacts ∼10% of people diagnosed with COVID-19, yet the pathophysiology driving ongoing symptoms is poorly understood. We hypothesised that 129Xe magnetic resonance imaging (MRI) could identify unique pulmonary phenotypic subgroups of long COVID, therefore we evaluated ventilation and gas exchange measurements with cluster analysis to generate imaging-based phenotypes. METHODS: COVID-negative controls and participants who previously tested positive for COVID-19 underwent 129XeMRI ∼14-months post-acute infection across three centres. Long COVID was defined as persistent dyspnea, chest tightness, cough, fatigue, nausea and/or loss of taste/smell at MRI; participants reporting no symptoms were considered fully-recovered. 129XeMRI ventilation defect percent (VDP) and membrane (Mem)/Gas, red blood cell (RBC)/Mem and RBC/Gas ratios were used in k-means clustering for long COVID, and measurements were compared using ANOVA with post-hoc Bonferroni correction. RESULTS: We evaluated 135 participants across three centres: 28 COVID-negative (40±16yrs), 34 fully-recovered (42±14yrs) and 73 long COVID (49±13yrs). RBC/Mem (p=0.03) and FEV1 (p=0.04) were different between long- and COVID-negative; FEV1 and all other pulmonary function tests (PFTs) were within normal ranges. Four unique long COVID clusters were identified compared with recovered and COVID-negative. Cluster1 was the youngest with normal MRI and mild gas-trapping; Cluster2 was the oldest, characterised by reduced RBC/Mem but normal PFTs; Cluster3 had mildly increased Mem/Gas with normal PFTs; and Cluster4 had markedly increased Mem/Gas with concomitant reduction in RBC/Mem and restrictive PFT pattern. CONCLUSION: We identified four 129XeMRI long COVID phenotypes with distinct characteristics. 129XeMRI can dissect pathophysiologic heterogeneity of long COVID to enable personalised patient care.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Eur Respir J

DOI

EISSN

1399-3003

Publication Date

February 8, 2024

Volume

63

Issue

3

Location

England

Related Subject Headings

  • Respiratory System
  • 3201 Cardiovascular medicine and haematology
  • 11 Medical and Health Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Eddy, R. L., Mummy, D., Zhang, S., Dai, H., Bechtel, A., Schmidt, A., … Niedbalski, P. J. (2024). Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation. Eur Respir J, 63(3). https://doi.org/10.1183/13993003.02301-2023
Eddy, Rachel L., David Mummy, Shuo Zhang, Haoran Dai, Aryil Bechtel, Alexandra Schmidt, Bradie Frizzell, et al. “Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation.Eur Respir J 63, no. 3 (February 8, 2024). https://doi.org/10.1183/13993003.02301-2023.
Eddy RL, Mummy D, Zhang S, Dai H, Bechtel A, Schmidt A, et al. Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation. Eur Respir J. 2024 Feb 8;63(3).
Eddy, Rachel L., et al. “Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation.Eur Respir J, vol. 63, no. 3, Feb. 2024. Pubmed, doi:10.1183/13993003.02301-2023.
Eddy RL, Mummy D, Zhang S, Dai H, Bechtel A, Schmidt A, Frizzell B, Gerayeli FV, Leipsic JA, Leung JM, Driehuys B, Que LG, Castro M, Sin DD, Niedbalski PJ. Cluster Analysis to Identify Long COVID Phenotypes Using 129Xe Magnetic Resonance Imaging: A Multi-centre Evaluation. Eur Respir J. 2024 Feb 8;63(3).
Journal cover image

Published In

Eur Respir J

DOI

EISSN

1399-3003

Publication Date

February 8, 2024

Volume

63

Issue

3

Location

England

Related Subject Headings

  • Respiratory System
  • 3201 Cardiovascular medicine and haematology
  • 11 Medical and Health Sciences