Introduction: Lung transplantation remains an important treatment for patients with end stage lung disease. Chronic lung allograft dysfunction (CLAD) remains the greatest limiting factor for long term survival. As the diagnosis of CLAD is based on pulmonary function tests, significant lung injury is required before a diagnosis is feasible, likely when irreversible damage has already occurred. Therefore, research is ongoing for early CLAD recognition, with biomarkers making up a substantial amount of this research. Areas covered: The purpose of this review is to describe available biomarkers, focusing on those which aid in predicting CLAD and distinguishing between different CLAD phenotypes. We describe biomarkers presenting in bronchial alveolar lavage (BAL) as well as circulating in peripheral blood, both of which offer an appealing alternative to lung biopsy. Expert Opinion: Development of CLAD involves complex, multiple immune and non-immune mechanisms. Therefore, evaluation of potential CLAD biomarkers serves a dual purpose: clinically, the goal remains early detection and identification of patients at increased risk. Simultaneously, biomarkers offer insight into the different mechanisms involved in the pathophysiology of CLAD, leading to the development of possible interventions. The ultimate goal is the development of both preventive and early intervention strategies for CLAD to improve the overall survival of our lung transplant recipients.

We investigated the prognostic significance of N-terminal pro-B-type natriuretic peptide (NT-proBNP) in lung transplant candidates, in a retrospective single-center study. Data regarding various baseline characteristics and all-cause mortality were collected for 205 lung transplant candidates placed on waitlist for transplantation from November 2017 to December 2019. Associations of NT-proBNP levels with baseline characteristics and mortality were analyzed. Results showed NT-proBNP values correlated positively with age, forced vital capacity, mean pulmonary artery pressure (MPAP), and pulmonary capillary wedge pressure; and negatively with diffusing lung capacity for carbon monoxide and cardiac index. The optimal cut-off of NT-proBNP for predicting MPAP levels > 35 mmHg was 251 pg/mL; with 58.1% sensitivity, 85.7% specificity, 45.0% positive predictive value, and 91.0% negative predictive value. During a median follow-up period of 2.2 years, 97 patients underwent lung transplantation, 42 died waiting for donation, and 66 were alive and still waiting for transplantations. On multivariate analysis, higher NT-proBNP levels were strongly associated with increased mortality among waitlisted lung transplant candidates (HR 1.49, 95% CI 1.10–2.03, p = 0.01). In conclusion NT-proBNP can predict mortality among waitlisted lung transplant candidates. Lower levels of NT-proBNP can preclude severe pulmonary artery hypertension. Assessment of NT-proBNP may improve risk stratification among lung transplant candidates.

Introduction: Female lung transplant recipients (LTRs) of reproductive age are increasingly considering pregnancy due to advances in post‐transplant management and improved survival. We report our experience with pregnancy in LTRs, with an emphasis on two or more successful full‐term pregnancies in individual transplant recipients.Methods: We conducted a retrospective analysis of pregnancies in LTRs at our transplant center and collected maternal and fetal outcomes.Results: In our patient cohort, eight female LTRs conceived a total of 17 pregnancies, resulting in 13 newborns, 12 at full term, and 11 with a birth weight > 2.5 kg. Three of the LTRs had two or more successful full‐term pregnancies. LTRs required a significant tacrolimus dose increase to maintain target trough levels during pregnancy. Six recipients are currently clinically stable and active, three with lung function comparable to pre‐pregnancy values, and three with evidence of chronic lung allograft dysfunction (CLAD), but stable lung function. Two of the eight LTRs died subsequent to childbirth secondary to chronic respiratory failure due to CLAD, at a mean of 11 years post‐transplantation and a mean of 4.5 years after childbirth.Conclusion: Pregnancy following lung transplantation is feasible and can be achieved with acceptable maternal and newborn outcomes. Importantly, LTRs can successfully have two or more full‐term pregnancies.

Two doses of mRNA SARS-CoV-2 vaccines elicit an attenuated humoral immune response among immunocompromised patients. Our study aimed to assess the immunogenicity of a third dose of the BNT162b2 vaccine among lung transplant recipients (LTRs). We prospectively evaluated the humoral response by measuring anti-spike SARS-CoV-2 and neutralizing antibodies in 139 vaccinated LTRs ~4–6 weeks following the third vaccine dose. The t-cell response was evaluated by IFNγ assay. The primary outcome was the seropositivity rate following the third vaccine dose. Secondary outcomes included: positive neutralizing antibody and cellular immune response rate, adverse events, and COVID-19 infections. Results were compared to a control group of 41 healthcare workers. Among LTRs, 42.4% had a seropositive antibody titer, and 17.2% had a positive t-cell response. Seropositivity was associated with younger age (t = 3.736, p < 0.001), higher GFR (t = 2.355, p = 0.011), and longer duration from transplantation (t = −1.992, p = 0.024). Antibody titer positively correlated with neutralizing antibodies (r = 0.955, p < 0.001). The current study may suggest the enhancement of immunogenicity by using booster doses. Since monoclonal antibodies have limited effectiveness against prevalent sub-variants and LTRs are prone to severe COVID-19 morbidity, vaccination remains crucial for this vulnerable population.

Background/Objectives: Rapid on-site evaluation (ROSE) is a valuable technique in interventional procedures to immediately assess the adequacy and quality of biopsy specimens at the time they are obtained. The integration of artificial intelligence (AI) into ROSE workflows has demonstrated diagnostic accuracy comparable to that of experienced cytologists. However, clinical implementation of AI-based ROSE models is limited by complex and expensive development. In contrast, the use of free or near-free global large language models (LLMs) offers a significant advantage, making diagnostic support more accessible. Assess the diagnostic accuracy of the LLMs ChatGPT and Gemini in evaluating cytological smears during interventional pulmonology procedures. Methods: Retrospective evaluation of the efficacy of LLMs for assessment of cytological smears obtained from adult patients who underwent interventional bronchoscopic and ultrasound-guided biopsies between 2020 and 2025. Images of ROSE-prepared samples were analyzed by ChatGPT-4o, ChatGPT-5, ChatGPT-5 “thinking”, and Gemini 2.5 models. Results: Forty-eight procedures in 47 patients (mean age 65 years) were analyzed; 79% of biopsies were malignant. Using the final histopathology report as reference, cytologists achieved balanced accuracy of 0.75 (Gwet’s AC1 = 0.53, sensitivity 0.71, specificity 0.78). ChatGPT-5 “thinking” showed high concordance (accuracy 0.65, Gwet’s AC1 = 0.81, sensitivity 1.00, specificity 0.30). Gemini reached an accuracy of 0.59 (Gwet’s AC1 = 0.76, sensitivity 0.97, specificity 0.20). Conclusions: To our knowledge, this study is the first to evaluate LLM-assisted ROSE in interventional pulmonology. The results suggest the potential feasibility of integrating this AI technology into the workflow within the pulmonary division. Larger prospective studies are needed to confirm effects on diagnostic yield.