HIGHER DONOR PAO2/FIO2 RATIO APPEARS TO BE ASSOCIATED WITH INCREASED INCIDENCE OF PRIMARY GRAFT DYSFUNCTION IN LUNG TRANSPLANT RECIPIENTS

Abstract OBJECTIVES Primary graft dysfunction (PGD) remains a major post-transplant complication and is associated with increased morbidity and mortality. Mechanisms evoking PGD are not completely clear, but inflammation plays a central role. We investigated the association between PGD and inflammatory proteins present in immediate postoperative bronchoalveolar lavage. METHODS All double-lung recipients transplanted at our institution from 2002 to 2018 were included in our study. We retrospectively selected 80 consecutive lung transplant recipients with different PGD grades (n = 20 for each PGD grades 0–1 to 2–3). In bronchoalveolar lavage performed within the first 24 h after donor aortic cross-clamping following lung transplantation, concentrations of 30 cytokines, chemokines and growth factors were assessed by enzyme-linked immunosorbent assay (ELISA) and correlated with donor and recipient demographics and outcomes. For analysis, 2 groups were defined: ‘mild’ PGD (grade 0–1) and ‘severe’ PGD (grades 2–3). RESULTS Significant differences between mild and severe PGD were found in 8 biomarkers [interleukin (IL)-6, IL-10, IL-13, eotaxin, granulocyte colony-stimulating factor, interferon γ, macrophage inflammatory protein 1α, surfactant protein D (SP-D); P < 0.05]. Increased IL-10 and IL-13, but none of the other proteins, were associated with short-term outcome (longer time to extubation; P = 0.005 and P < 0.0001; increased intensive care unit stay; P = 0.012 and P < 0.0001; and hospital stay; P = 0.041 and P = 0.002). There were no significant differences in donor and recipient characteristics between the groups. CONCLUSIONS Expression profiles of key inflammatory mediators in bronchoalveolar lavage fluid differed significantly between lung transplant recipients with severe versus mild PGD and correlated with clinical outcome variables. Further research should focus on the early mechanisms leading to PGD.

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Quantitative analysis of adipose tissue on chest CT to predict primary graft dysfunction in lung transplant recipients: a novel optimal biomarker approach

Medical Imaging 2018: Computer-Aided Diagnosis ◽

10.1117/12.2294050 ◽

2018 ◽

Author(s):

Yubing Tong ◽

Jayaram K. Udupa ◽

Chuang Wang ◽

Caiyun Wu ◽

Gargi Pednekar ◽

...

Keyword(s):

Adipose Tissue ◽

Quantitative Analysis ◽

Lung Transplant ◽

Chest Ct ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

Lung Transplant Recipients

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Outcomes Among Lung Transplant Recipients with Elevated Left Heart Filling Pressures and Primary Graft Dysfunction

The Journal of Heart and Lung Transplantation ◽

10.1016/j.healun.2018.01.646 ◽

2018 ◽

Vol 37 (4) ◽

pp. S258-S259

Author(s):

S. Elnahas ◽

R. Panchanathan ◽

M. Olson ◽

P. Kang ◽

V. Patel ◽

...

Keyword(s):

Lung Transplant ◽

Left Heart ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

Lung Transplant Recipients

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Early Trends in PaO 2 /Fraction of Inspired Oxygen Ratio Predict Outcome in Lung Transplant Recipients With Severe Primary Graft Dysfunction

CHEST Journal ◽

10.1378/chest.06-2752 ◽

2007 ◽

Vol 132 (3) ◽

pp. 991-997 ◽

Cited By ~ 22

Author(s):

Matthew E. Prekker ◽

Cynthia S. Herrington ◽

Marshall I. Hertz ◽

David M. Radosevich ◽

Peter S. Dahlberg

Keyword(s):

Lung Transplant ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

Fraction Of Inspired Oxygen ◽

Lung Transplant Recipients ◽

Oxygen Ratio ◽

Inspired Oxygen

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506: Primary graft dysfunction does not increase the risk of acute rejection in pediatric lung transplant recipients

The Journal of Heart and Lung Transplantation ◽

10.1016/j.healun.2006.11.530 ◽

2007 ◽

Vol 26 (2) ◽

pp. S242

Author(s):

M.G. Schecter ◽

J.M. Robertson ◽

M.L. Doan ◽

E.D. McKenzie ◽

J.S. Heinle ◽

...

Keyword(s):

Acute Rejection ◽

Lung Transplant ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

Lung Transplant Recipients

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395: Primary Graft Dysfunction (PGD) in Human Lung Transplant Recipients Following T-Cell Depletion with Thymoglobulin or Campath-1H

The Journal of Heart and Lung Transplantation ◽

10.1016/j.healun.2007.11.406 ◽

2008 ◽

Vol 27 (2) ◽

pp. S203

Author(s):

D.J. Kaczorowski ◽

D.B. Zaldonis ◽

Y. Toyoda ◽

C.A. Bermudez ◽

B.G. Hattler ◽

...

Keyword(s):

T Cell ◽

Lung Transplant ◽

Human Lung ◽

Cell Depletion ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

T Cell Depletion ◽

Lung Transplant Recipients

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Protein biomarkers associated with primary graft dysfunction following lung transplantation

AJP Lung Cellular and Molecular Physiology ◽

10.1152/ajplung.00454.2016 ◽

2017 ◽

Vol 312 (4) ◽

pp. L531-L541 ◽

Cited By ~ 12

Author(s):

B. C. S. Hamilton ◽

J. Kukreja ◽

L. B. Ware ◽

M. A. Matthay

Keyword(s):

Lung Transplant ◽

Bronchoalveolar Lavage Fluid ◽

Lavage Fluid ◽

Transplant Recipients ◽

Primary Graft Dysfunction ◽

Graft Dysfunction ◽

Protein Biomarkers ◽

Epithelial Injury ◽

Lung Transplant Recipients ◽

Biologic Factors

Severe primary graft dysfunction affects 15–20% of lung transplant recipients and carries a high mortality risk. In addition to known donor, recipient, and perioperative clinical risk factors, numerous biologic factors are thought to contribute to primary graft dysfunction. Our current understanding of the pathogenesis of lung injury and primary graft dysfunction emphasizes multiple pathways leading to lung endothelial and epithelial injury. Protein biomarkers specific to these pathways can be measured in the plasma, bronchoalveolar lavage fluid, and lung tissue. Clarification of the pathophysiology and timing of primary graft dysfunction could illuminate predictors of dysfunction, allowing for better risk stratification, earlier identification of susceptible recipients, and development of targeted therapies. Here, we review much of what has been learned about the association of protein biomarkers with primary graft dysfunction and evaluate this association at different measurement time points.

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