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Post-lung transplant surveillance in 2026: current practice, variability, and the need for standardization
Berta Saez-Gimenez1, Jesper M Magnusson2,3, Andrea Zajacova4
1Respiratory Department, Hospital Universitari Vall d'Hebron, Barcelona, Spain.
Lung transplant surveillance lacks a universal standard, leading to varied care and delayed detection of allograft dysfunction. Standardizing surveillance is crucial for improving patient outcomes after lung transplantation.
Area of Science:
- Medicine
- Transplantation
- Pulmonology
Background:
- Post-lung transplant surveillance lacks a universally accepted standard, resulting in heterogeneous care practices.
- Current surveillance methods include physiological testing, imaging, bronchoscopy, laboratory monitoring, and biomarkers, but face limitations and variability.
- This heterogeneity hinders the timely detection of allograft dysfunction and impacts patient outcomes.
Purpose of the Study:
- To synthesize current post-lung transplant surveillance practices across various domains.
- To identify key limitations, sources of variability, and evidence gaps in existing surveillance strategies.
- To highlight areas where established and novel tools support routine use versus investigational application.
Main Methods:
- This study is a narrative review of current post-lung transplant surveillance practices.
- It synthesizes information on organization of care, lung function monitoring, radiological assessment, invasive diagnostics, and laboratory parameters.
- Emerging biomarkers and their evidence base are also summarized.
Main Results:
- Surveillance practices are fragmented, with inconsistent data interpretation and limited integration of novel diagnostics.
- These issues contribute to delayed recognition of graft injury and variable patient outcomes.
- Evidence supporting routine use of certain tools is limited, while others remain investigational.
Conclusions:
- Advancing post-transplant care necessitates consensus-driven minimum surveillance standards.
- Developing trajectory-based interpretation frameworks is essential for consistent data analysis.
- Rational incorporation of validated biomarkers and digital technologies into harmonized follow-up pathways is required.
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