Document resource
Background Persistent pulmonary dysfunction is common after COVID-19, yet traditional assessments using carbon monoxide diffusing capacity (DLCO) alone may miss alveolar-capillary impairment.Objective To determine whether combining nitric oxide (DLNO 5s) and carbon monoxide (DLCO5s) diffusing capacities enhances detection of post-COVID-19 lung impairment and whether summed z-scores outperform individual measures in classifying affected individuals.Design and methods We conducted an individual participant data meta-analysis using hierarchical mixed-effects modelling. The dataset included 572 COVID-19 survivors and 72 matched controls from six European centres. Lung function metrics—including spirometry, total lung capacity, DLNO 5s and DLCO5s—were standardised into z-scores. Logistic models were compared using Bayesian Information Criterion and Leave-One-Out Information Criterion. Classification accuracy was assessed with Matthews Correlation Coefficient (MCC) and net reclassification improvement (NRI). Principal Component Analysis examined score structures, and dyspnoea severity was correlated with z-scores. Assessments were conducted 32–575 days post-infection (median=130 days).Results The number of days between SARS-CoV-2 diagnosis and testing did not affect any of the measured z‐scores. Summed DLNO 5s + DLCO5s z-scores consistently outperformed individual metrics. The combined model improved MCC by 0.06 (95% CI 0.01 to 0.11) and NRI by 37% (95% CI 13 to 62%) over DLCO5s alone. The top model (summed DLNO5s + DLCO5s z-scores model) explained 10% of fixed and 59% of random variance. DLCO5s alone failed to identify reduced membrane diffusion in approximately 16% of cases. Dyspnoea severity was significantly associated with all diffusion indices (p<0.001), though combined scores showed no stronger correlation than single predictors.Conclusion Summed DLNO 5s + DLCO5s z-scores enhance classification of post-COVID-19 pulmonary impairment beyond DLCO5s alone. The NO-CO double diffusion approach offers improved diagnostic discrimination between previously infected individuals and controls and aligns with symptom severity. These findings support broader clinical integration of combined diffusion metrics in post-COVID assessment.