A prospective study on the role of lung ultrasound in monitoring patients with COVID-19 pneumonia in intensive care unit to assess severity of lung involvement
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background: COVID-19, caused by SARS-CoV-2, can progress to severe pneumonia and acute respiratory distress syndrome. Lung ultrasound (LUS) offers a rapid, bedside, radiation-free method for detecting typical lung changes and assessing severity when computed tomography (CT) or radiography is less feasible. Aims and Objectives: This study aimed to evaluate the role of LUS in monitoring and assessing the severity of COVID-19 pneumonia. Materials and Methods: This prospective study was conducted on 70 patients at the Rajiv Gandhi Government General Hospital between March 2021 and April 2022. LUS was performed using a 12-zone protocol with curvilinear and linear probes, scored using the LUS score (LUSS) system. Baseline CT and LUS were performed within 24 h, and LUS was repeated every 3 days, grading each zone 0–3 to classify lung involvement severity. Results: Most patients were male (70%) and showed moderate disease severity on both CT (62.9%) and LUSS (67.1%). Clinical improvement was noted in 82.9% of patients, 74.3% were discharged, and 17.1% died. LUS showed an absence of pleural fluid, universal presence of >2 B-lines, and high prevalence of pleural irregularities and confluent B-lines, which decreased over time, whereas small subpleural consolidations remained frequent. CT severity showed a strong association with LUSS severity (P=0.0005) and clinical outcomes (P=0.003), with most deaths occurring in the CT-severe and LUSS-severe groups. Gender was not significantly associated with disease severity or outcomes. Total LUSS demonstrated strong positive correlations with neutrophil-to-lymphocyte ratio (r=0.732) and C-reactive protein (r=0.704). Conclusion: CT and LUS together help assess COVID-19 pneumonia, with LUS offering a simple, noninvasive tool for monitoring progression and detecting long-term residual changes.
Institution: Stanley Medical College
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $200
OpenAlex ID: W7147284045
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