Chronic lung lesions in COVID-19 survivors: predictive clinical model.

ABSTRACT:

Objective

This study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection.

Design

This prospective cohort study included COVID-19 survivors hospitalised between 30 March 2020 and 31 August 2020 followed-up 6 months after hospital discharge. The pulmonary function was assessed using the modified Medical Research Council (mMRC) dyspnoea scale, oximetry (SpO₂), spirometry (forced vital capacity (FVC)) and chest X-ray (CXR) during an in-person consultation. Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO₂, FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT.

Setting

A tertiary hospit

SUBMITTER: Carvalho CRR 

PROVIDER: S-EPMC9195157 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature