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1.
BMJ Open ; 12(10): e061332, 2022 10 03.
Article in English | MEDLINE | ID: mdl-36192102

ABSTRACT

OBJECTIVES: Pulmonary disease is a significant cause of morbidity and mortality in adults and children, but most of the world lacks diagnostic imaging for its assessment. Lung ultrasound is a portable, low-cost, and highly accurate imaging modality for assessment of pulmonary pathology including pneumonia, but its deployment is limited secondary to a lack of trained sonographers. In this study, we piloted a low-cost lung teleultrasound system in rural Peru during the COVID-19 pandemic using lung ultrasound volume sweep imaging (VSI) that can be operated by an individual without prior ultrasound training circumventing many obstacles to ultrasound deployment. DESIGN: Pilot study. SETTING: Study activities took place in five health centres in rural Peru. PARTICIPANTS: There were 213 participants presenting to rural health clinics. INTERVENTIONS: Individuals without prior ultrasound experience in rural Peru underwent brief training on how to use the teleultrasound system and perform lung ultrasound VSI. Subsequently, patients attending clinic were scanned by these previously ultrasound-naïve operators with the teleultrasound system. PRIMARY AND SECONDARY OUTCOME MEASURES: Radiologists examined the ultrasound imaging to assess its diagnostic value and identify any pathology. A random subset of 20% of the scans were analysed for inter-reader reliability. RESULTS: Lung VSI teleultrasound examinations underwent detailed analysis by two cardiothoracic attending radiologists. Of the examinations, 202 were rated of diagnostic image quality (94.8%, 95% CI 90.9% to 97.4%). There was 91% agreement between radiologists on lung ultrasound interpretation among a 20% sample of all examinations (κ=0.76, 95% CI 0.53 to 0.98). Radiologists were able to identify sequelae of COVID-19 with the predominant finding being B-lines. CONCLUSION: Lung VSI teleultrasound performed by individuals without prior training allowed diagnostic imaging of the lungs and identification of sequelae of COVID-19 infection. Deployment of lung VSI teleultrasound holds potential as a low-cost means to improve access to imaging around the world.


Subject(s)
COVID-19 , Adult , COVID-19/diagnostic imaging , Child , Humans , Lung/diagnostic imaging , Pandemics , Peru/epidemiology , Pilot Projects , Reproducibility of Results , Ultrasonography/methods
2.
BMJ Open ; 12(6): e059110, 2022 06 13.
Article in English | MEDLINE | ID: mdl-35697456

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 hospital in Sao Paulo, Brazil. PARTICIPANTS: 749 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. RESULTS: There 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, SpO2, FVC, CXR and CT, accurately detected pulmonary lesions by the joint data of CXR, mMRC scale, SpO2 and FVC (sensitivity, 0.85±0.08; specificity, 0.70±0.06; F1-score, 0.79±0.06 and area under the curve, 0.80±0.07). CONCLUSION: A 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.


Subject(s)
COVID-19 , Adolescent , Adult , Brazil/epidemiology , COVID-19/diagnosis , Humans , Lung/diagnostic imaging , Prospective Studies , SARS-CoV-2 , Survivors
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