ArticleBMJ open2022
Chronic lung lesions in COVID-19 survivors: predictive clinical model.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Implementation of an interdisciplinary research model at a tertiary University Hospital in São Paulo, Brazil: post-COVID-19 cohort study.Clinics (Sao Paulo, Brazil) · 2026Article
- Article
- Post-COVID-19 respiratory sequelae two years after hospitalization: an ambidirectional study.Lancet regional health. Americas · 2024Article
- Data-driven, cross-disciplinary collaboration: lessons learned at the largest academic health center in Latin America during the COVID-19 pandemic.Frontiers in public health · 2024Article
- Long-term respiratory follow-up of ICU hospitalized COVID-19 patients: Prospective cohort study.PloS one · 2023Article
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to propose a simple, accessible and low-cost predictive clinical model to detect lung lesions due to COVID-19 infection.
designThis 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 (SpO
settingA tertiary hospital in Sao Paulo, Brazil.
participants749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged ≥18 years. PRIMARY OUTCOME MEASURE: A predictive clinical model for lung lesion detection on chest CT.
resultsThere were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. Almost half of them (48%) had significant pulmonary abnormalities, including ground-glass opacities, parenchymal bands, reticulation, traction bronchiectasis and architectural distortion. The machine learning model, including the results of 257 patients with complete data on mMRC, SpO
conclusionA predictive clinical model based on CXR, mMRC, oximetry and spirometry data can accurately screen patients with lung lesions after SARS-CoV-2 infection. Given that these examinations are highly accessible and low cost, this protocol can be automated and implemented in different countries for early detection of COVID-19 sequelae.
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