Evidence map›Paper›PMID 36167867›Full record

ArticleScientific reports2022

Plasma protein biomarkers for primary graft dysfunction after lung transplantation: a single-center cohort analysis.

Lourdes Chacon-Alberty, Rupa S Kanchi, Shengbin Ye, Camila Hochman-Mendez, Daoud Daoud, Cristian Coarfa, Meng Li, Sandra L Grimm, Maher Baz, Ivan Rosas and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Multi-site cytokine levels are predictive of primary graft dysfunction following lung transplantation.Transplant international : official journal of the European Society for Organ Transplantation · 2026
    Article
  3. Article
  4. Review
  5. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Lourdes Chacon-AlbertyDepartment of Regenerative Medicine Research, Texas Heart Institute, Houston, TX, USA.
Rupa S KanchiDan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
Shengbin YeDepartment of Statistics, Rice University, Houston, TX, USA.
Camila Hochman-MendezDepartment of Regenerative Medicine Research, Texas Heart Institute, Houston, TX, USA.
Daoud DaoudDivision of Cardiopulmonary Transplantation and Mechanical Circulatory Support, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA.
Cristian CoarfaDan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
Meng LiDepartment of Statistics, Rice University, Houston, TX, USA.
Sandra L GrimmMolecular and Cellular Biology Department, Baylor College of Medicine, Houston, TX, USA.
Maher BazDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.
Ivan RosasDepartment of Medicine, Baylor College of Medicine, Houston, TX, USA.
Gabriel LoorDivision of Cardiopulmonary Transplantation and Mechanical Circulatory Support, Michael E DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA. Gabriel.Loor@bcm.edu.
Baylor College of Medicine · USRice University · US

Funding

Tumor BiologyP30CA125123 · NCI · BAYLOR COLLEGE OF MEDICINE · PI Michael M Ittmann · 2007 to 2026
$73.9M
Project 5: Pyolytic conversion of PAHs in contaminated sediments into char to eliminate toxicity and enhance soil fertilityP42ES027725 · NIEHS · BAYLOR COLLEGE OF MEDICINE · PI BHAGAVATULA MOORTHY · 2020 to 2026
$17.8M
Translational Research Support CoreP30ES030285 · NIEHS · BAYLOR COLLEGE OF MEDICINE · PI Casey W Wright · 2019 to 2026
$14.7M
Project 2: Disparities-Aware Classifiers for Maternal and Infant HealthP50MD015496 · NIMHD · BAYLOR COLLEGE OF MEDICINE · PI SYMANSKI, ELAINE · 2020 to 2024
$7.2M
Training Program in Biostatistics for Cancer ResearchT32CA096520 · NCI · RICE UNIVERSITY · PI KIMMEL, MAREK, YUAN, YING · 2003 to 2023
$4.5M
NCI NIH HHS P30 CA125123NCI NIH HHS P30CA125123NCI NIH HHS T32 CA096520NIEHS NIH HHS P30 ES030285NIEHS NIH HHS P42 ES027725NIH HHS T32CA96520NIMHD NIH HHS P50 MD015496NIMHD NIH HHS P50MD015496
6 · The paper itself

Abstract

The clinical use of circulating biomarkers for primary graft dysfunction (PGD) after lung transplantation has been limited. In a prospective single-center cohort, we examined the use of plasma protein biomarkers as indicators of PGD severity and duration after lung transplantation. The study comprised 40 consecutive lung transplant patients who consented to blood sample collection immediately pretransplant and at 6, 24, 48, and 72 h after lung transplant. An expert grader determined the severity and duration of PGD and scored PGD at T0 (6 h after reperfusion), T24, T48, and T72 h post-reperfusion using the 2016 ISHLT consensus guidelines. A bead-based multiplex assay was used to measure 27 plasma proteins including cytokines, growth factors, and chemokines. Enzyme-linked immunoassay was used to measure cell injury markers including M30, M65, soluble receptor of advanced glycation end-products (sRAGE), and plasminogen activator inhibitor-1 (PAI-1). A pairwise comparisons analysis was used to assess differences in protein levels between PGD severity scores (1, 2, and 3) at T0, T24, T48, and T72 h. Sensitivity and temporal analyses were used to explore the association of protein expression patterns and PGD3 at T48-72 h (the most severe, persistent form of PGD). We used the Benjamini-Hochberg method to adjust for multiple testing. Of the 40 patients, 22 (55%) had PGD3 at some point post-transplant from T0 to T72 h; 12 (30%) had PGD3 at T48-72 h. In the pairwise comparison, we identified a robust plasma protein expression signature for PGD severity. In the sensitivity analysis, using a linear model for microarray data, we found that differential perioperative expression of IP-10, MIP1B, RANTES, IL-8, IL-1Ra, G-CSF, and PDGF-BB correlated with PGD3 development at T48-72 h (FDR < 0.1 and p < 0.05). In the temporal analysis, using linear mixed modeling with overlap weighting, we identified unique protein patterns in patients who did or did not develop PGD3 at T48-72 h. Our findings suggest that unique inflammatory protein expression patterns may be informative of PGD severity and duration. PGD biomarker panels may improve early detection of PGD, predict its clinical course, and help monitor treatment efficacy in the current era of lung transplantation.

Indexed as

Lung TransplantationPrimary Graft DysfunctionBecaplerminBiomarkersChemokine CCL5Chemokine CXCL10Cohort StudiesGranulocyte Colony-Stimulating FactorHumansInterleukin 1 Receptor Antagonist ProteinInterleukin-8Plasminogen Activator Inhibitor 1Prospective StudiesRetrospective StudiesBecaplerminBiomarkersChemokine CCL5Chemokine CXCL10Granulocyte Colony-Stimulating FactorInterleukin 1 Receptor Antagonist ProteinInterleukin-8Plasminogen Activator Inhibitor 1

Identifiers

PMID36167867
PMCPMC9515157
OpenAlexW4297326645

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.