Clinical predictors of impaired pulmonary diffusing capacity in patients recovering from COVID-19: A secondary...

This study aimed to identify clinical predictors of impaired pulmonary diffusing capacity in patients recovering from coronavirus disease 2019 (COVID-19) using a secondary analysis of multicentre datasets. # Methods This secondary analysis included adults with laboratory-confirmed COVID-19 who underwent pulmonary function testing during the post-acute recovery phase. In total, 572 post-COVID-19 patients were included. Demographic characteristics and pulmonary function parameters were extracted from the datasets. Impaired pulmonary diffusing capacity for carbon monoxide (DLCO) was defined as a DLCO Z-score < -1.645 (below the lower limit of normal) according to Global Lung Function Initiative reference equations. Univariable logistic regression was used as an initial screening step, and variables with p < 0.10, together with clinically relevant variables, were considered for multivariable analysis. # Results Of the 572 post-COVID-19 patients, 145 had impaired DLCO. Baseline characteristics differed significantly between patients with normal and impaired DLCO, particularly in age, sex, forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and total lung capacity (TLC) (p < 0.05). Age, sex, FVC, FEV1, and TLC were significantly associated with impaired DLCO in multivariable analysis. In multivariable logistic regression, age (adjusted OR 1.025; p = 0.002), female sex (adjusted OR 0.379; p < 0.001), and TLC (adjusted OR 0.603; p < 0.001) remained statistically associated with impaired DLCO. The model showed acceptable apparent discrimination in the development dataset (AUC 0.710). # Conclusions Impaired pulmonary diffusing capacity was observed in approximately one-quarter of patients recovering from COVID-19. Older age, sex, and lower total lung capacity were independently associated with impaired DLCO in this secondary analysis. These findings should be interpreted as exploratory associations rather than causal or validated predictive effects.