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. 2022 Mar 8;12(1):4040.
doi: 10.1038/s41598-022-07944-4.

Reduced levels of pulmonary surfactant in COVID-19 ARDS

Affiliations

Reduced levels of pulmonary surfactant in COVID-19 ARDS

Peter Schousboe et al. Sci Rep. .

Abstract

To provide novel data on surfactant levels in adult COVID-19 patients, we collected bronchoalveolar lavage fluid less than 72 h after intubation and used Fourier Transform Infrared Spectroscopy to measure levels of dipalmitoylphosphatidylcholine (DPPC). A total of eleven COVID-19 patients with moderate-to-severe ARDS (CARDS) and 15 healthy controls were included. CARDS patients had lower DPPC levels than healthy controls. Moreover, a principal component analysis was able to separate patient groups into distinguishable subgroups. Our findings indicate markedly impaired pulmonary surfactant levels in COVID-19 patients, justifying further studies and clinical trials of exogenous surfactant.

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Conflict of interest statement

DPCC analysis was part of a public–private partnership between the Department of Paediatrics, Holbaek Hospital, Region Zealand, Denmark and SIME Diagnostics Ltd. HV, NS, PV and PS reported being consultants and shareholders of SIME Diagnostics Ltd. TB reports personal fees and nonfinancial support from Bristol-Myers Squibb and Gilead. The rest of the authors have no conflicts of interest.

Figures

Figure 1
Figure 1
Dipalmitoylphosphatidylcholine (DPPC) levels (nmol/ml) measured in bronchoalveolar lavage fluid (BALF) in 15 healthy controls (M, 15; mean age, 23; SD, 2 years), in four patients with non-COVID-19 ARDS (M/F, 3/1; mean age, 68.5; SD, 3.9 years) and in 11 patients with CARDS (M/F, 10/1; mean age, 65.5; SD, 10.6 years). Boxplots depicts mean values with hinges corresponding to first and third quartile (the 25th and 75th percentiles). Lower and upper whiskers extend to smallest and highest value, respectively. Mann–Whitney U-test: P < 0.0001. CARDS, COVID-19 associated ARDS; DPPC, dipalmitoylphosphatidylcholine; NS, non-significant. ****P < 0.0001.
Figure 2
Figure 2
A principal component analysis (PCA) score plot with projection of the data onto the span of the principal components (PC). The spectral matrices were decomposed into two principal components (PCs) by applying singular value decomposition, resulting in a score plot of the first and second PC. Each PC is a linear combination of the wavenumbers of spectra. Before applying PCA, the spectra were baseline corrected (Whittaker smoother) and subsequently normalized by applying standard normal variate methods to avoid intensity variations in the spectra due to the deposition. Two parameters, lambda (λ = 105) and penalty (P = 10–3) are involved related to the smoothness of the fit and the penalty imposed to the points giving positive residuals in the fit.

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