(694) Preservation of Lung Function Despite Covid-19 Infection in a Cohort of Lung Transplant Recipients

PURPOSE: Respiratory viruses contribute to chronic lung allograft dysfunction (CLAD). Limited data is available regarding allograft function following COVID-19. We evaluated the effect of COVID-19 on lung function trajectory in Lung Transplant Recipients (LTR). METHODS: Data was retrospectively collected at our lung transplant (LTx) center on all LTR with confirmed COVID-19 infection between March 2020-Sept 2022. Spirometry was compared pre and post infection. Risk factors for a decline in FEV1 ≥10% were explored with logistic regression. RESULTS: From a cohort of 650 LTR, there were 224 COVID infections in 216 patients. Median age was 60 years, 118 (54%) were male and the majority were bilateral LTR (122, 88%). Median time from LTx to diagnosis was 5.2 years (IQR 2.8-10). At baseline, 187 patients (85%) received > 3 vaccines and 35 (16%) had tixagevimab/ cilgavimab. Anti-viral therapy was given in 190/216 (88%), most commonly remdesevir 93/216 (43%). 42 patients (19%) were hospitalised, 10 (5%) admitted to ICU and direct COVID related mortality was 8/216 (4%). Pre and post lung function was available on 144 patients. Median time from baseline spirometry to COVID-19 was 2.7 months and 2.2 months post COVID-19. There was a small but statistically significant decline in forced expiratory volume in 1 second (FEV1) post COVID-19, with a median drop of 0.05L (2% decline; IQR -5.6-1.8%, p<0.001); (Figure 1). A ≥10% decline in FEV1 occurred in 24/144 patients (17%) and an increase in FEV1 of >10% occurred in 6/151 (3%) of patients. Baseline demographics, lung function, disease severity, vaccination status and treatment type were not associated with a ≥10% decline in FEV1. CONCLUSION: In COVID optimized LTR with subsequent infection, the majority had mild disease. Reassuringly, most had stable lung function 2 months post infection. A small proportion had a decline in FEV1 of >10%, but there were no discernible risk factors to predict the decline.