Comparison of Clinical Characteristics Among COVID-19 and Non-COVID-19 Pediatric Pneumonias: A Multicenter Cross-Sectional Study

Abstract

BackgroundThe pandemic of Coronavirus Disease 2019 (COVID-19) brings new challenges for pediatricians, especially in the differentiation with non-COVID-19 pneumonia in the peak season of pneumonia. We aimed to compare the clinical characteristics of pediatric patients with COVID-19 and other respiratory pathogens infected pneumonias.MethodsWe conducted a multi-center, cross-sectional study of pediatric inpatients in China. Based on pathogenic test results, pediatric patients were divided into three groups, including COVID-19 pneumonia group, Non-COVID-19 viral (NCV) pneumonia group and Non-viral (NV) pneumonia group. Their clinical characteristics were compared by Kruskal-Wallis H test or chi-square test.ResultsA total of 636 pediatric pneumonia inpatients, among which 87 in COVID-19 group, 194 in NCV group, and 355 in NV group, were included in analysis. Compared with NCV and NV patients, COVID-19 patients were older (median age 6.33, IQR 2.00-12.00 years), and relatively fewer COVID-19 patients presented fever (63.2%), cough (60.9%), shortness of breath (1.1%), and abnormal pulmonary auscultation (18.4%). The results were verified by the comparison of COVID-19, respiratory syncytial virus (RSV) and influenza A (IFA) pneumonia patients. Approximately 42.5%, 44.8%, and 12.6% of the COVID-19 patients presented simply ground-glass opacity (GGO), simply consolidation, and the both changes on computed tomography (CT) scans, respectively; the proportions were similar as those in NCV and NV group (p>0.05). Only 47.1% of COVID-19 patients had both lungs pneumonia, which was significantly lower than that proportion of nearly 80% in the other two groups. COVID-19 patients presented lower proportions of increased white blood cell count (16.5%) and abnormal procalcitonin (PCT) (10.7%), and a higher proportion of decreased lymphocyte count (44.0%) compared with the other two groups.ConclusionMajority clinical characteristics of pediatric COVID-19 pneumonia patients were milder than non-COVID-19 patients. However, lymphocytopenia remained a prominent feature of COVID-19 pediatric pneumonia.

ECHOPAEDIA: Echography in Paediatric Patients in the Age of Coronavirus Disease 2019: Utility of Lung Ultrasound and Chest X-Ray in Diagnosis of Community-Acquired Pneumonia and Severe Acute Respiratory Syndrome Coronavirus 2 Pneumonia

“…The image acquisition protocol was developed during the COVID-19 pandemic. This is extremely valid considering the excellent correlation between ultrasound and tomodensitometric findings (the current diagnostic gold standard for pneumonia) ( 7 , 18 ). Furthermore, recent works show an excellent correlation between LUS and histopathological changes in SARS-CoV-2 pneumonia ( 25 ).…”

“…High-resolution chest computed tomography (HRCT) is currently considered the gold standard for the identification of lung lesions in coronavirus disease 2019 (COVID-19) patients ( 17 ). However, HRCT is difficult to perform in paediatric clinical settings due not only to the risk of radiation exposure but also in consideration of a milder form of parenchymal damage in COVID-19 pneumonia in children rather than in adults, which often do not require such instrumentation to characterise its extent ( 18 ). Multiple groups have documented that LUS has comparable sensitivity to HRCT in identifying parenchymal damage and monitoring response to treatment in COVID-19 patients.…”

Automatic Classification Between COVID-19 and Non-COVID-19 Pneumonia Using Symptoms, Comorbidities, and Laboratory Findings: The Khorshid COVID Cohort Study

“…For example, Sun et al designed a diagnosis method based on CT-scan image processing and reached 93 and 90% sensitivity and specificity, respectively, to discriminate between COVID and non-COVID pneumonia (25). Considering the prevalence of 14% of COVID-19 (77), it is possible to use Bayes' theorem to predict the true PPV and NPV of the diagnosis method when applied to the population (Equations 11, 12) (78):…”

“…In addition to gender and symptom duration, signs and symptoms, blood biomarkers, and comorbidities were selected. Performance indices of the cross-validated confusion matrix for dataset 1 were as follows: sensitivity of 96% [confidence interval, CI, 95%: 94-98], specificity of 95% [90-99], positive predictive Marateb et alComputer-Aided Diagnosis of COVID-19 value (PPV) of 99% [98-100], negative predictive value (NPV) of 82% [76][77][78][79][80][81][82][83][84][85][86][87][88][89], diagnostic odds ratio (DOR) of 496 245], area under the ROC (AUC) of 0.96 [0.94-0.97], Matthews Correlation Coefficient (MCC) of 0.87 [0.85-0.88], accuracy of 96% [94][95][96][97][98], and Cohen's Kappa of 0.86 [0.81-0.91]. The proposed algorithm showed excellent diagnosis accuracy and class-labeling agreement, and fair discriminant power.…”

“…Computer-Aided Diagnosis of COVID-19 value (PPV) of 99% [98-100], negative predictive value (NPV) of 82% [76][77][78][79][80][81][82][83][84][85][86][87][88][89], diagnostic odds ratio (DOR) of 496 245], area under the ROC (AUC) of 0.96 [0.94-0.97], Matthews Correlation Coefficient (MCC) of 0.87 [0.85-0.88], accuracy of 96% [94][95][96][97][98], and Cohen's Kappa of 0.86 [0.81-0.91]. The proposed algorithm showed excellent diagnosis accuracy and class-labeling agreement, and fair discriminant power.…”