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Background: During the COVID-19 pandemic, several studies demonstrated the effectiveness of lung ultrasound (LUS) as a frontline tool in diagnosing and managing acute SARS-CoV-2 pneumonia. However, its role in detecting post-COVID-19 lung sequelae remains to be fully determined. This study aims to evaluate the diagnostic accuracy of LUS in identifying lung parenchymal damage, particularly fibrotic-like changes, following COVID-19 pneumonia, comparing its performance to that of CT. Methods: Relevant studies published before July 2024 were identified through a comprehensive search of PubMed, Embase, and Cochrane library. The search terms were combinations of the relevant medical subject heading (MeSH) terms, key words and word variants for “lung”, “post-COVID”, “long-COVID”, and “ultrasound”. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver-operating characteristic (SROC) curve were used to examine the accuracy of CEUS. The selected works used different thresholds for the detection and counting of B-lines by ultrasound. This led to dividing our analysis into two models, the first based on the lower thresholds for detection of B-lines found in the works, and the second on data obtained using a higher detection threshold. Results: In terms of the diagnostic accuracy of LUS in detecting residual fibrotic-like changes in patients post-COVID-19 infection, a low-threshold model displayed a pooled sensitivity of 0.98 [95% confidence interval (CI): 0.95–0.99] and a pooled specificity of 0.54 (95% CI: 0.49–0.59). The DOR was 44.9 (95% CI: 10.8–187.1). The area under the curve (AUC) of SROC was 0.90. In the second analysis, the model with the higher threshold to detect B-lines showed a pooled sensitivity of 0.90 (95% CI: 0.85–0.94) and a pooled specificity of 0.88 (95% CI: 0.84–0.91). The DOR was 50.4 (95% CI: 15.9–159.3). The AUC of SROC was 0.93. Conclusions: In both analyses (even using the high threshold for the detection of B-lines), excellent sensitivity (98% in model 1 and 90% in model 2) is maintained. The specificity has a significant variation between the two models from 54 (model 1) to 87% (model 2). The model with the highest threshold for the detection of B-lines displayed the best diagnostic accuracy, as confirmed by the AUC values of the SROC (0.93).
Background: During the COVID-19 pandemic, several studies demonstrated the effectiveness of lung ultrasound (LUS) as a frontline tool in diagnosing and managing acute SARS-CoV-2 pneumonia. However, its role in detecting post-COVID-19 lung sequelae remains to be fully determined. This study aims to evaluate the diagnostic accuracy of LUS in identifying lung parenchymal damage, particularly fibrotic-like changes, following COVID-19 pneumonia, comparing its performance to that of CT. Methods: Relevant studies published before July 2024 were identified through a comprehensive search of PubMed, Embase, and Cochrane library. The search terms were combinations of the relevant medical subject heading (MeSH) terms, key words and word variants for “lung”, “post-COVID”, “long-COVID”, and “ultrasound”. The pooled sensitivity, specificity, diagnostic odds ratio (DOR), and summary receiver-operating characteristic (SROC) curve were used to examine the accuracy of CEUS. The selected works used different thresholds for the detection and counting of B-lines by ultrasound. This led to dividing our analysis into two models, the first based on the lower thresholds for detection of B-lines found in the works, and the second on data obtained using a higher detection threshold. Results: In terms of the diagnostic accuracy of LUS in detecting residual fibrotic-like changes in patients post-COVID-19 infection, a low-threshold model displayed a pooled sensitivity of 0.98 [95% confidence interval (CI): 0.95–0.99] and a pooled specificity of 0.54 (95% CI: 0.49–0.59). The DOR was 44.9 (95% CI: 10.8–187.1). The area under the curve (AUC) of SROC was 0.90. In the second analysis, the model with the higher threshold to detect B-lines showed a pooled sensitivity of 0.90 (95% CI: 0.85–0.94) and a pooled specificity of 0.88 (95% CI: 0.84–0.91). The DOR was 50.4 (95% CI: 15.9–159.3). The AUC of SROC was 0.93. Conclusions: In both analyses (even using the high threshold for the detection of B-lines), excellent sensitivity (98% in model 1 and 90% in model 2) is maintained. The specificity has a significant variation between the two models from 54 (model 1) to 87% (model 2). The model with the highest threshold for the detection of B-lines displayed the best diagnostic accuracy, as confirmed by the AUC values of the SROC (0.93).
Asthma is one of the most common chronic inflammatory diseases of childhood with a heterogeneous impact on health and quality of life. Mepolizumab is an antagonist of interleukin-5, indicated as an adjunct therapy for severe refractory eosinophilic asthma in adolescents and children aged >6 years old. We present the case of a 9 year-old boy with severe asthma who experienced several asthmatic exacerbations following a SARS-CoV-2 infection, necessitating therapy with short-acting bronchodilators, oral corticosteroids, and hospitalization. We follow the patient using validated questionnaires for the evaluation of asthma control: Children Asthma Control Test, Asthma Control Questionnaire, respiratory function tests, and evaluation of exhaled nitric oxide fraction. After 12 weeks from the start of therapy with mepolizumab, we found significant improvements in lung function, a reduction in the degree of bronchial inflammation, and improvements in quality of life. No asthmatic exacerbations have been reported since the initiation of treatment with mepolizumab. Respiratory infections, such as those related to SARS-CoV-2, represent a significant risk factor for exacerbations in patients with moderate to severe forms of asthma. In our experience, following new episodes of exacerbation, the initiation of treatment with mepolizumab has allowed us to improve asthma control and enhance the quality of life of patients from the first doses. Although mepolizumab showed promise in this child with severe asthma during SARS-CoV-2 infection, the results from this single case cannot be generalized. Further studies are needed to confirm its safety and effectiveness.
Background and Objectives: Recognizing the crucial gaps in our understanding of pediatric pneumonia post-SARS-CoV-2 infection, this study aimed to assess the relationship between Pediatric Pneumonia Ultrasound Scores (PedPne) and inflammatory biomarkers. The primary objective of this study is to evaluate the predictive value of PedPne in comparison with inflammatory biomarkers (IL-6 and dNLR) for the development of pneumonia in pediatric patients following SARS-CoV-2 infection. Materials and Methods: This longitudinal observational study collected data from pediatric patients diagnosed with pneumonia after an acute SARS-CoV2 infection. The study focused on analyzing changes in PedPne scores and inflammatory markers such as IL-6 and dNLR from initial admission to follow-up at 7 days. Statistical analysis involved calculating the sensitivity, specificity, and Area Under the Curve (AUC) for each biomarker, alongside regression analysis to determine their hazard ratios for predicting pneumonia development. Results: The analysis identified significant cutoff values for dNLR at 1.88 (sensitivity 77.0%, specificity 85.7%, AUC 0.802, p < 0.001), IL-6 at 6.1 pg/mL (sensitivity 70.3%, specificity 92.9%, AUC 0.869, p < 0.001), and PedPne score at 3.3 (sensitivity 75.7%, specificity 78.6%, AUC 0.794, p < 0.001). Conversely, NLR showed lower diagnostic performance (AUC 0.485, p = 0.327). Regression analysis further highlighted the strong predictive power of these markers, with IL-6 showing a fourfold increase in pneumonia risk (HR = 4.25, CI: 2.07–9.53, p < 0.001), dNLR indicating more than a twofold increase (HR = 2.53, CI: 1.19–6.97, p = 0.006), and PedPne score associated with more than a doubling of the risk (HR = 2.60, CI: 1.33–5.18, p < 0.001). Conclusions: The study conclusively demonstrated that both PedPne ultrasound scores and specific inflammatory biomarkers such as dNLR and IL-6 are significant predictors of pneumonia development in pediatric patients post-COVID-19 infection. These findings advocate for the integration of these biomarkers in routine clinical assessments to enhance the diagnostic accuracy and management of pneumonia in children following SARS-CoV-2 infection.
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