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Volatile organic compound profiling to explore primary graft dysfunction after lung transplantation.
Stefanuto, Pierre-Hugues; Romano, Rosalba; Rees, Christiaan A; Nasir, Mavra; Thakuria, Louit; Simon, Andre; Reed, Anna K; Marczin, Nandor; Hill, Jane E.
Afiliación
  • Stefanuto PH; Thayer School of Engineering, Dartmouth College, Hanover, NH, USA.
  • Romano R; Organic and Biological Analytical Chemistry Group, Liège University, Liège, Belgium.
  • Rees CA; Department of Surgery and Cancer, Section of Anaesthetics, Imperial College of London, London, UK.
  • Nasir M; Harefield Hospital, Royal Brompton and Harefield NHS Foundation Trust, Harefield, UK.
  • Thakuria L; Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
  • Simon A; Geisel School of Medicine, Dartmouth College, Hanover, NH, USA.
  • Reed AK; Harefield Hospital, Royal Brompton and Harefield NHS Foundation Trust, Harefield, UK.
  • Marczin N; Harefield Hospital, Royal Brompton and Harefield NHS Foundation Trust, Harefield, UK.
  • Hill JE; Harefield Hospital, Royal Brompton and Harefield NHS Foundation Trust, Harefield, UK.
Sci Rep ; 12(1): 2053, 2022 02 08.
Article en En | MEDLINE | ID: mdl-35136125
ABSTRACT
Primary graft dysfunction (PGD) is a major determinant of morbidity and mortality following lung transplantation. Delineating basic mechanisms and molecular signatures of PGD remain a fundamental challenge. This pilot study examines if the pulmonary volatile organic compound (VOC) spectrum relate to PGD and postoperative outcomes. The VOC profiles of 58 bronchoalveolar lavage fluid (BALF) and blind bronchial aspirate samples from 35 transplant patients were extracted using solid-phase-microextraction and analyzed with comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. The support vector machine algorithm was used to identify VOCs that could differentiate patients with severe from lower grade PGD. Using 20 statistically significant VOCs from the sample headspace collected immediately after transplantation (< 6 h), severe PGD was differentiable from low PGD with an AUROC of 0.90 and an accuracy of 0.83 on test set samples. The model was somewhat effective for later time points with an AUROC of 0.80. Three major chemical classes in the model were dominated by alkylated hydrocarbons, linear hydrocarbons, and aldehydes in severe PGD samples. These VOCs may have important clinical and mechanistic implications, therefore large-scale study and potential translation to breath analysis is recommended.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Líquido del Lavado Bronquioalveolar / Trasplante de Pulmón / Lesión Pulmonar / Disfunción Primaria del Injerto / Compuestos Orgánicos Volátiles Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Líquido del Lavado Bronquioalveolar / Trasplante de Pulmón / Lesión Pulmonar / Disfunción Primaria del Injerto / Compuestos Orgánicos Volátiles Tipo de estudio: Prognostic_studies Límite: Adult / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
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