Evaluating lung transplant referral and listing in chronic respiratory disease: A single-center experience from a tertiary care centre in India

BACKGROUND: Patients with advanced chronic respiratory diseases experience severe functional limitation, limited therapeutic options, and high mortality risk. Lung transplantation (LTx) offers potential survival benefit in carefully selected candidates. However, Indian data describing the severity profile and eligibility of such patients are scarce. This study assessed the proportion and characteristics of patients meeting International Society for Heart and Lung Transplantation (ISHLT) referral and listing criteria, along with disease severity, contraindications, and risk factors. METHODS: This retrospective observational study included adults admitted between January 2020 and October 2023 with interstitial lung disease, chronic obstructive pulmonary disease, bronchiectasis, or pulmonary vascular disease. Eligibility for LTx was evaluated using 2021 ISHLT consensus criteria. Lung Allocation Score was calculated as per OPTN/UNOS guidelines. ISHLT-defined risk factors, substantially increased risk, and absolute contraindications were recorded. RESULTS: Among 401 patients, 105 (26.2%) met referral and 97 (24.2%) listing criteria. Most demonstrated advanced physiological limitation (mean FVC 44.1% predicted; median ECOG 3). ILD was the leading indication among listing-eligible patients (48.6%), followed by COPD (32.4%) and bronchiectasis (18.1%). LAS was highest in ILD (mean 47.8). ISHLT-defined risk factors were present in 90.5% of referral-eligible patients, with 25.7% showing substantially increased risk and 32.4% absolute contraindications. Findings may overestimate eligibility and severity given the inclusion of only hospitalized patients, limiting broader generalizability to ambulatory patients. CONCLUSION: A considerable proportion of hospitalized patients with advanced respiratory disease are LTx-eligible, though many have comorbidities or modifiable risks. Early referral and multidisciplinary optimization are essential to improve candidacy.