Prediction of impaired lung diffusion capacity in COVID-19 pneumonia survivors.

Abstract

Background: Patients surviving the coronavirus disease 2019 (COVID-19) are reported to explore pulmonary sequelae. It is challenging to provide pulmonary function tests (PFTs) during the pandemic of this contagious diseases because of the difficulty related to infection control risks. This study aims to identify important predictors of lung diffusion capacity impairment in COVID-19 survivors after hospital discharge.

Methods: The retrospective cohort study included 341 patients after COVID-19. The parameters of spirometry, body plethysmography, lung diffusion capacity for carbon monoxide (DLco), and the worst chest computed tomography (CT) scan in the acute phase of COVID-19 (CT_max, %) were assessed. Multivariable logistic regression analysis for exploring risk factors associated with lung diffusion capacity impairment was used. The receiver operating characteristic (ROC) curve of multivariate observation and the area under the curve (AUC) were used to assess the performance of a model.

Results: At the time of the analysis, 64.8% (221/341) patients participated in follow-up visits on 90 days, 23.5% (80/341) on 90-180 days, and 11.7% (40/341) on more than 180 days after the onset of COVID-19 symptoms. The median CT_max was 50% (50% of the lung area was involved in a pathological process according to a semi-quantitative CT score). Abnormal DLco (<80% of predicted) was recorded in 60.4% cases. The predictors such as age, gender, body mass index (BMI), CT_max, and the time interval between the COVID-19 symptoms onset and follow-up PFTs were encapsulated in the logistic regression analysis to explore the prediction of reduced DLco. Backward stepwise regression was applied to eliminate insignificant predictors. It was found that CT_max was important predictor of impaired DLco. AUC value was 0.780 [95% confidential interval (CI): 0.723-0.837, P<0.001]. The sensitivity and specificity in the training group were 80% and 67%, respectively. The odds ratio (OR) showed that CT_max =45% and more in the acute phase of COVID-19 was significantly associated with reduced DLco during 6 months after COVID-19 (OR 1.21, 95% CI: 1.095-1.334; P<0.05).

Conclusions: Pulmonary interstitial damage caused by severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) definitely contributes to reduced DLco after hospital discharge. This indicates that analysis of CT scans during the acute phase of COVID-19 may have prognostic relevance for abnormal DLco.