Risk factors for restrictive allograft syndrome (RAS), a severe phenotype of chronic lung allograft dysfunction (CLAD) after lung transplantation, are currently not well known. In this retrospective nested case-control-study, we analyzed 69 patients with RAS and 69 matched non-CLAD controls to identify clinical risk factors for RAS. Patients with RAS demonstrated overall higher blood eosinophils (P = .02), increased bronchoalveolar eosinophils (P < .001) and lymphocytes (P = .03), and higher incidence of infections, particularly Pseudomonas species infection (P = .003), invasive fungal disease (P < .001, mainly due to Aspergillus species), SARS-CoV-2 (P < .001), and cytomegalovirus infection (P = .04), compared with non-CLAD controls. Antihuman leukocyte antigen (anti-HLA) antibodies, especially persistent donor-specific antibodies (P < 0.001), specifically targeting HLA-DQ and HLA-DR loci, and antibody-mediated rejection (P < .001), were strongly associated with later RAS. Histopathologic lung injury patterns on transbronchial biopsy (P < .001), and persistent chest computed tomography opacities in absence of pulmonary dysfunction (P < .001) were identified as early indicators of later RAS. Proactive detection and management of these risk factors could help mitigate future decline in allograft function and reduce progression to clinical RAS. Future studies should explore early treatment strategies targeting these modifiable factors to preserve allograft function and improve long-term outcomes for lung transplant recipients.
Despite the high demand, over 7,500 recovered kidneys annually go unused, with transplant centers showing significant variation in their offer acceptance practices. However, it remains unclear how much of this variation occurs between individual clinicians within the same center and its impact on allocation efficiency and equity. This study quantified the variability in kidney offer acceptance decisions attributable to clinicians versus enters and examined the role of donor quality in acceptance decisions. We analyzed national transplant registry data (Jan. 2016-Dec. 2020) linked to on-call records from 15 transplant centers, creating a clinician-level dataset with 344,678 deceased donor kidney offers. The primary outcome was the variability in offer acceptance attributable to clinicians versus centers, quantified via hierarchical, mixed effects logistic regression models. To complement KDPI as a measure of donor quality, we incorporated Expected Acceptance Probability (EAP), which adjusts for a broader set of donor characteristics and also recipient factors. Both center-level (0.35, 95% CI: 0.15-0.79) and clinician-level variance (0.10, 95% CI: 0.06-0.18) were significant, with heterogeneity in the KDPI-acceptance association among clinicians. These results underscore the need for further research into the mechanisms driving the clinician-level variation and its implications for organ allocation efficacy, equity, and patient outcomes.