Development of prognostic models to estimate the probability of lung injury one year after COVID-19-related hospitalization-a prospective study

Abstract

Background: Long-term effects of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) infection still under study. The objectives of this study were to identify persistent pulmonary lesions 1 year after coronavirus disease 2019 (COVID-19) hospitalization and assess whether it is possible to estimate the probability that a patient develops these complications in the future.

Methods: A prospective study of ≥18 years old patients hospitalized for SARS-COV-2 infection who develop persistent respiratory symptoms, lung function abnormalities or have radiological findings 6-8 weeks after hospital discharge. Logistic regression models were used to identify prognostic factors associated with a higher risk of developing respiratory problems. Models performance was assessed in terms of calibration and discrimination.

Results: A total of 233 patients [median age 66 years [interquartile range (IQR): 56, 74]; 138 (59.2%) male] were categorized into two groups based on whether they stayed in the critical care unit (79 cases) or not (154). At the end of follow-up, 179 patients (76.8%) developed persistent respiratory symptoms, and 22 patients (9.4%) showed radiological fibrotic lesions with pulmonary function abnormalities (post-COVID-19 fibrotic pulmonary lesions). Our prognostic models created to predict persistent respiratory symptoms [post-COVID-19 functional status at initial visit (the higher the score, the higher the risk), and history of bronchial asthma] and post-COVID-19 fibrotic pulmonary lesions [female; FVC% (the higher the FVC%, the lower the probability); and critical care unit stay] one year after infection showed good (AUC 0.857; 95% CI: 0.799-0.915) and excellent performance (AUC 0.901; 95% CI: 0.837-0.964), respectively.

Conclusions: Constructed models show good performance in identifying patients at risk of developing lung injury one year after COVID-19-related hospitalization.

Keywords: Post-acute coronavirus disease 2019 syndrome (post-acute COVID-19 syndrome); clinical prediction models; fibrotic pulmonary lesions; radiological findings; respiratory functional test; respiratory symptoms.

Figure 1

Action algorithm based on study design. *, no previous respiratory disease. COVID-19, coronavirus disease 2019; X-ray, radiography; PFT, pulmonary function testing; ABG, arterial blood gas analysis; CCU, critical care unit.

Figure 2

Temporary changes in the percentage of forced expiratory volume in 1 second (A), forced vital capacity (B), diffusion capacity (C), with respect to their theoretical value, and number of patients that obtained the same score on the post-COVID-19 functional scale (D) at baseline and at week 52. Data are expressed as median values and interquartile ranges. Solid red lines represent patients who experienced an increase in the percentage of that specific parameter, whereas dotted blue lines represent the patients who experienced a worsening. COVID-19, coronavirus disease 2019; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity; DLCO, diffusion capacity for carbon monoxide; PCFS, post-COVID-19 functional status scale.

Figure 3

ROC curve and corresponding Area under the curve [AUC (95% confidence interval)] for: (A) risk for persistent symptoms (post-COVID functional status and history of asthma); (B) risk for pulmonary fibrotic changes (forced vital capacity and hospitalization in critical care unit). ROC, receiver operating characteristic; AUC, area under the area; COVID, coronavirus disease.

Figure 4

Clinical scores for both models. PCFS, post-COVID-19 functional status; SE, sensitivity; SP, specificity; PPV, positive predictive value; NPV, negative predictive value; COVID-19, coronavirus disease 2019; FVC, forced vital capacity; CCU, critical care unit.