# Optimizing Donor Management in Lung Transplantation

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2020 · $393,750

## Abstract

Project Summary
End-stage lung disease (ESLD) affects over 1 million patients in the U.S. and has an estimated annual economic
impact exceeding $ 50 billion. Lung transplantation (LT), the only curative therapy for ESLD, improves survival
as well as quality of life. Scarcity of donor organs remains the predominant barrier towards wider application of
LT. Despite this discrepancy, only 20% of brain dead donors are considered for LT.
Two predominant factors account for the low lung utilization rates in donors. Firstly, though the International
Society for Heart and Lung Transplantation has proposed guidelines for lung donor assessment, these
recommendations are fairly broad and are variably implemented, leading to significant heterogeneity in
assessment of organs for potential transplantation. Unfortunately, there are no validated instruments available
to inform donor lung utilization, thereby hampering optimization of a limited resource. Secondly, the impact of
donor quality on early graft function after LT is unknown. Severe primary graft dysfunction (PGD) after LT leads
to significant morbidity and mortality and lowers long-term survival. Donor factors associated with severe PGD
remain inadequately understood and lead to further uncertainty in the decision to accept organs.
In this proposal we will address both the principal reasons for low lung utilization rates nationally.
Aim 1: To develop and validate a predictive model for lung utilization in brain dead donors. With the
access to large, prospectively maintained database providing detailed donor level information for donors whose
lungs were accepted or declined for LT, we will use multivariable analyses to create a predictive model for
likelihood of lung utilization from a brain dead donor. A nomogram will be developed and validated in independent
cohorts from other organ procurement organizations (OPOs) and presented as an electronic app.
Aim 2: To understand the impact of donor factors on early outcomes in lung transplant recipients. We
will evaluate lung donors at three collaborating OPOs with well-maintained databases. Detailed information on
90-day outcomes in recipients will be obtained from institutional and national registry data. We will develop
multivariable models to understand the impact of donor clinical and CT scan imaging characteristics on the risk
of early graft dysfunction and 90-day mortality after LT. The models will be externally validated and will be used
to generate a donor score that can predict lung performance after transplant.
By developing a tool to guide donor selection for LT and by delineating donor characteristics that impact early
outcomes in LT recipients, we will address two critical questions for any clinician evaluating a donor offer: Can
we accept these lungs? Will they function adequately? Our findings will be easily incorporated into routine donor
care and will guide LT clinicians and policymakers in optimal management of a scarce resource. The models
...

## Key facts

- **NIH application ID:** 9971977
- **Project number:** 1R01HL146856-01A1
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Varun Puri
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $393,750
- **Award type:** 1
- **Project period:** 2020-07-01 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971977

## Citation

> US National Institutes of Health, RePORTER application 9971977, Optimizing Donor Management in Lung Transplantation (1R01HL146856-01A1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9971977. Licensed CC0.

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