Subphenotypes in patients with acute respiratory distress syndrome treated with high-flow oxygen

Other authors

Institut Català de la Salut

[Blot PL, Chousterman BG] Département d’anesthésie Réanimation, Hôpital Lariboisière, Paris, France. INSERM UMRS-942 MASCOT, Hôpital Lariboisière, Paris, France. [Santafè M] Servei de Medicina Intensiva, Parc Taulí Hospital Universitari, Institut de Recerca Part Taulí (I3PT-CERCA), Sabadell, Spain. [Cartailler J] INSERM UMRS-942 MASCOT, Hôpital Lariboisière, Paris, France. [Pacheco A] Servei de Medicina Intensiva, Vall d’Hebron Hospital Universitari, Barcelona, Spain. [Magret M] Servei de Medicina Intensiva, Hospital Universitari Joan XXIII, Tarragona, Spain

Vall d'Hebron Barcelona Hospital Campus

Publication date

2023-11-16T13:40:15Z

2023-11-16T13:40:15Z

2023-11-01



Abstract

Acute respiratory distress syndrome; Biomarkers; High-flow nasal oxygen


Síndrome de dificultat respiratòria aguda; Biomarcadors; Oxigen nasal d'alt flux


Síndrome de dificultad respiratoria aguda; Biomarcadores; Oxígeno nasal de alto flujo


Background Acute respiratory distress syndrome (ARDS) subphenotypes differ in outcomes and treatment responses. Subphenotypes in high-flow nasal oxygen (HFNO)-treated ARDS patients have not been investigated. Objectives To identify biological subphenotypes in HFNO-treated ARDS patients. Methods Secondary analysis of a prospective multicenter observational study including ARDS patients supported with HFNO. Plasma inflammation markers (interleukin [IL]-6, IL-8, and IL-33 and soluble suppression of tumorigenicity-2 [sST2]) and lung epithelial (receptor for advanced glycation end products [RAGE] and surfactant protein D [SP-D]) and endothelial (angiopoietin-2 [Ang-2]) injury were measured. These biomarkers and bicarbonate were used in K-means cluster analysis to identify subphenotypes. Logistic regression was performed on biomarker combinations to predict clustering. We chose the model with the best AUROC and the lowest number of variables. This model was used to describe the HAIS (High-flow ARDS Inflammatory Subphenotype) score. Results Among 41 HFNO patients, two subphenotypes were identified. Hyperinflammatory subphenotype (n = 17) showed higher biomarker levels than hypoinflammatory (n = 24). Despite similar baseline characteristics, the hyperinflammatory subphenotype had higher 60-day mortality (47 vs 8.3% p = 0.014) and longer ICU length of stay (22.0 days [18.0–30.0] vs 39.5 [25.5–60.0], p = 0.034). The HAIS score, based on IL-8 and sST2, accurately distinguished subphenotypes (AUROC 0.96 [95%CI: 0.90–1.00]). A HAIS score ≥ 7.45 was predictor of hyperinflammatory subphenotype. Conclusion ARDS patients treated with HFNO exhibit two biological subphenotypes that have similar clinical characteristics, but hyperinflammatory patients have worse outcomes. The HAIS score may identify patients with hyperinflammatory subphenotype and might be used for enrichment strategies in future clinical trials.


The princeps study was supported, in part, by a grant from Instituto de Salud Carlos III-Fondo Europeo de Desarrollo Regional (FEDER) (PI14/01420) and a grant from Federación Española del Enfermo Crítico (FEEC) 2015. No specific support was done for this re-analysis.

Document Type

Article


Published version

Language

English

Publisher

BMC

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Attribution 4.0 International

http://creativecommons.org/licenses/by/4.0/

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