BACKGROUND:

Variability in presentation of children with coronavirus disease 2019 (COVID-19) is a challenge in emergency departments (EDs) in terms of early recognition, which has an effect on disease control and prevention. We describe a cohort of 170 children with COVID-19 and differences with the published cohorts.

METHODS:

Retrospective chart reviews on children (0–18 years) evaluated in 17 Italian pediatric EDs.

RESULTS:

In our cohort (median age of 45 months; interquartile range of 4 months–10.7 years), we found a high number of patients <1 year with COVID-19 disease. The exposure happened mainly (59%) outside family clusters; 22% had comorbidities. Children were more frequently asymptomatic (17%) or with mild diseases (63%). Common symptoms were cough (43%) and difficulty feeding (35%). Chest computed tomography, chest radiograph, and point-of-care lung ultrasound were used in 2%, 36%, and 8% of cases, respectively. Forty-three percent of patients were admitted because of their clinical conditions. The minimal use of computed tomography and chest radiograph may have led to a reduced identification of moderate cases, which may have been clinically classified as mild cases.

CONCLUSIONS:

Italian children evaluated in the ED infrequently have notable disease symptoms. For pediatrics, COVID-19 may have rare but serious and life-threatening presentations but, in the majority of cases, represents an organizational burden for the ED. These data should not lower the attention to and preparedness for COVID-19 disease because children may represent a source of viral transmission. A clinically driven classification, instead of a radiologic, could be more valuable in predicting patient needs and better allocating resources.

What’s Known on This Subject:

In early reports on children with coronavirus disease 2019, it was described that most of the virologically confirmed cases happened in family clusters with moderate or critical infections. The current classification of disease relies on the radiologic diagnosis of pneumonia.

What This Study Adds:

Our cohort had younger patients, mainly exposed to nonrelatives. Patients required few diagnostic resources. A clinically driven classification could be more helpful when dealing with pediatric coronavirus 2019, which, apart from rare presentations (multisystem inflammatory syndrome), represents an organizational burden.

The current outbreak of a new type of coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) originated in China in December 2019 and then spread to other countries. Italy is currently experiencing an epidemic of coronavirus disease 2019 (COVID-19), which emerged in the Lombardy region and rapidly escalated.1 

In early reports on Chinese children with COVID-19,24  it was observed that 43% to 64% of virologically confirmed cases had moderate or critical infections, with 2 deaths, whereas asymptomatic and mild cases ranged from 35% to 56%. However, the currently available disease classification relies on a pneumonia diagnosis through radiologic imaging, routinely including computed tomography (CT) scans in the pediatric patient2,4  similar to adult patients. In Italian data, published on May 4, 2020, it was reported that 1.9% of total cases occurred in children (0–18 years), with 2 deaths.5 

The variability of presentation poses a challenge for early recognition of patients with suspected COVID-19 in emergency departments (EDs), which are currently playing a role in disease control and prevention through adequate flow management and resource allocation.

In this case series, we describe the clinical features, severity of disease, and employed diagnostic resources of a cohort of ED pediatric patients with confirmed SARS-CoV-2 infection and compare our cohort to the data available from the major pediatric case series published to date.24 

We retrospectively investigated characteristics of children who tested positive for the SARS-CoV-2 infection (nasal or nasopharyngeal swab), evaluated to 1 of the 17 EDs of our research group between March 3, 2020, and May 2, 2020. Up until the end of March, the decision to test a patient was based on the definition of suspected COVID-19, which included influenza-like illness or fever, close contacts with a proven COVID-19 patient, or recent travel through areas with documented transmission of SARS-CoV-2 (areas where the epidemic started).1  By April, the decision to test a patient was based mainly on clinical criteria (presence of influenzalike illness or gastroenteritis, skin rash, or vasculitis).

Clinical, laboratory, and imaging data were anonymized and retrieved from electronic records and, then, collected by using Research Electronic Data Capture.6  Clinical data included demographics, presence of comorbidities, symptoms at presentation, and diagnostic imaging performed during the ED assessment. Patient outcomes were registered on the basis of the discharge evaluation or after the completion of an ICU stay. Patient outcomes were checked before report completion (May 5). Disease severity was defined adopting the available classification proposed by Dong et al2  (Table 1), although, as further discussed below, its criteria may lead to an overestimation of the severity of the cases with subclinical characteristics and chest CT visible lung lesions.

TABLE 1

Severity of Disease Classification Based on Associated Signs and Symptoms

Leading Signs and SymptomsAsymptomaticMildModerateSevereaCriticalb
Cough − +c 
Fever − ± 
Fatigue − NR NR 
Myalgia − NR NR 
Sore throat − NR NR 
Runny nose − NR NR NR 
Sneezing − NR NR NR 
Congestion of the pharynx − NR NR NR 
Chest auscultatory findings − − ± 
Nausea − +d NR NR NR 
Vomiting − +d NR NR NR 
Abdominal pain − +d NR NR NR 
Diarrhea − +d NR NR 
Wheezing − − ± NR NR 
Dyspnea − − NR 
Hypoxemia − − − 
Central cyanosis − − − 
Acute respiratory distress syndrome − − − − 
Respiratory failure − − − − 
Shock − − − − 
Encephalopathy − − − − 
Myocardial injury or heart failure − − − − 
Coagulation dysfunction − − − − 
Acute kidney injury − − − − 
Chest imaging − − +e 
SARS-CoV-2 PCR 
Leading Signs and SymptomsAsymptomaticMildModerateSevereaCriticalb
Cough − +c 
Fever − ± 
Fatigue − NR NR 
Myalgia − NR NR 
Sore throat − NR NR 
Runny nose − NR NR NR 
Sneezing − NR NR NR 
Congestion of the pharynx − NR NR NR 
Chest auscultatory findings − − ± 
Nausea − +d NR NR NR 
Vomiting − +d NR NR NR 
Abdominal pain − +d NR NR NR 
Diarrhea − +d NR NR 
Wheezing − − ± NR NR 
Dyspnea − − NR 
Hypoxemia − − − 
Central cyanosis − − − 
Acute respiratory distress syndrome − − − − 
Respiratory failure − − − − 
Shock − − − − 
Encephalopathy − − − − 
Myocardial injury or heart failure − − − − 
Coagulation dysfunction − − − − 
Acute kidney injury − − − − 
Chest imaging − − +e 
SARS-CoV-2 PCR 

NR indicates not reported in the classification of Dong et al.2  + indicates the presence of a symptom, whereas − indicates the absence; ± indicates that symptom may come with other symptoms or not be present. PCR, polymerase chain reaction.

a

Mild or moderate clinical patterns and any manifestations suggesting rapid disease progression (ie, tachypnoea, hypoxemia with oxygen saturation <92%, neurologic deterioration, dehydration, myocardial injury, coagulation dysfunction, or rhabdomyolysis).

b

Quick progression of disease with respiratory failure with need for mechanical ventilation (ie, acute respiratory distress syndrome or persistent hypoxia), septic shock, or multiple organ failure.

c

Mostly dry cough, followed by productive cough.

d

Some cases may have only digestive symptoms such as nausea, vomiting, abdominal pain and diarrhea.

e

Pneumonia is the leading criteria to classify a patient into the moderate severity of disease. Some cases may have no clinical signs and symptoms, but chest CT shows lung lesions, which are subclinical.

We compared our results with available data from the 3 previously published Chinese cohorts.24 

Statistical analysis of categorical variables, reported as absolute numbers and percentages, was provided by using a two-tailed χ2 or Fisher exact test, when required, with confidence intervals (CIs) of 95% and significance levels at 0.05. The distributions of continuous variables were described by using mean values and SDs or medians and interquartile ranges. Data were aggregated and compared with data reported by the Chinese pediatric cohorts24  by using MATLAB R2019b (MathWorks, Natick, MA). Details on the research strategy and inclusion criteria for the Chinese studies are described in Supplemental Table 7. This study was approved by the institutional review board of the leading research site.

We included 170 Italian children with confirmed COVID-19 (Italian Cohort: CONFIDENCE). A part of this cohort consisting of 100 patients was succinctly described in a preliminary report.7  Here, we provide a full description of all patients included in the Coronavirus Infection in Pediatric Emergency Department cohort before the current lockdown expired on May 3, providing more clinical data and information on the management of patients.

Epidemiological characteristics are detailed in Table 2. Outcomes are reported in Supplemental Table 8. The median age was 45 months, and the interquartile range was 4 months to 10.7 years). Boys were 56% of cases. The sex distribution was similar to the other studies. There were 38 (22%) patients with comorbidities. Seventy (41%) patients had familial relatives with SARS-CoV-2 infection, whereas patient contact with other suspected cases was observed in 72 (42%) patients (not associated with family clustering); 21 (12%) traveled to areas with documented SARS-CoV-2 transmission. Seven (4%) patients were infected from an unknown source and were tested because of presenting symptoms.

TABLE 2

Epidemiological Characteristics of Italian and Previously Reported Chinese Cohorts

CharacteristicsItalian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Dong et al2  (n = 731)Qiu et al4  (n = 36)P
Age distribution, y, n (%)    8.3 (3.5)a <.001 
 <1 61 (36) 31 (18) 86 (11.8)   
 1–5 29 (17) 40 (23) 137 (18.7)   
 6–10 32 (19) 58 (34) 171 (23.4)   
 >10 48 (28) 42 (25) 337 (46.1)   
Sex, n (%)     .75 
 Female 75 (44) 67 (39) 311 (42.5) 13 (36)  
 Male 95 (56) 104 (61) 420 (57.5) 23 (64)  
Exposure, n (%)      
 Family 70 (41) 154 (90) NA 24 (67) <.001 
 Otherb 72 (42) 2 (1) NA 4 (11) <.001 
 Unknownc 28 (16) 15 (9) NA NR <.001 
 Both family or other NA NR NA 8 (22) — 
 Both family and other 142 (84) NR NA NR — 
 Nonfamily, both other and unknown 100 (59) 17 (10) NA 12 (33) — 
CharacteristicsItalian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Dong et al2  (n = 731)Qiu et al4  (n = 36)P
Age distribution, y, n (%)    8.3 (3.5)a <.001 
 <1 61 (36) 31 (18) 86 (11.8)   
 1–5 29 (17) 40 (23) 137 (18.7)   
 6–10 32 (19) 58 (34) 171 (23.4)   
 >10 48 (28) 42 (25) 337 (46.1)   
Sex, n (%)     .75 
 Female 75 (44) 67 (39) 311 (42.5) 13 (36)  
 Male 95 (56) 104 (61) 420 (57.5) 23 (64)  
Exposure, n (%)      
 Family 70 (41) 154 (90) NA 24 (67) <.001 
 Otherb 72 (42) 2 (1) NA 4 (11) <.001 
 Unknownc 28 (16) 15 (9) NA NR <.001 
 Both family or other NA NR NA 8 (22) — 
 Both family and other 142 (84) NR NA NR — 
 Nonfamily, both other and unknown 100 (59) 17 (10) NA 12 (33) — 

Comorbidities were present in 38 (22%) patients of the Coronavirus Infection in Pediatric Emergency Department cohort and are detailed in the following list: cystic fibrosis (5 of 38; 13%); neurologic (7 of 38; 18%; epileptic encephalopathy [2; 1 of these patients with tracheostomy was the only child requiring intensive care admission and mechanical ventilation], ventriculoperitoneal shunt [1], autism [2], epilepsy, mental retardation, liver transplant 1 y before [1], complex febrile seizure, hypophosphatemic rickets [1]; hematologic (4 of 38; 10%; favism [1], thrombocytopenia [1], severe anemia [2]); syndrome (4 of 38; 10%; Di George [1], CHARGE [coloboma heart defects, choanal atresia, growth retardation, genital abnormalities, ear abnormalities] [1], arthrogryposis [1], undefined syndrome, patient presented with multiple intestinal and genital malformations and chronic renal failure [1]; prematurity (3 of 38; 8%); cardiac (3 of 38; 8%; ventricular septal defect [1], rheumatic heart disease [1], mitral valve disease [1]; immunologic (4 of 38; 10%; ulcerative colitis [1], uveitis and nephritis [1], rheumatoid arthritis [1], Lupus and Whipple disease [1]); oncological (3 of 38; 8%; Wilms tumor [1], extrarenal malignant rhabdoid tumor [1], acute lymphoblastic leukemia [1]; metabolic (2 of 38; 5%; propionic acidemia [1], adrenogenital syndrome [1]; other (3of 38, 8%; Kikuchi histiocytic necrotizing lymphadenitis [1], reduced renal function due to Henoch-Schonlein purpura [1], skeletal dysmorphisms, psychomotor retardation and hydrocephalus [1]. NA, not available; NR, not reported. —, not applicable.

a

Presented as mean (SD).

b

Other includes history of travel or exposure to epidemic areas.

c

Unknown includes an unidentified source of infection or contact with other suspected cases.

Clinical findings of the Italian and previously reported Chinese cohorts24  are detailed in Table 3. Ill appearance was observed in 20 (12%) patients, and fever was observed in 82 (48%; range of temperature in febrile patients: 37.5–40.1°C [mean: 38.4° C]). Common symptoms were dry or productive cough (73%; 43%), refusal to feed or difficulty feeding (42%; 35%), and rhinorrhea (34%; 20%). Less common symptoms were apnea, cyanosis, headache, or dehydration. Five patients presented with pulse oximetry ≤94%.

TABLE 3

Clinical Features of Italian and Previously Reported Chinese Cohorts

Signs and SymptomsItalian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Qiu et al4  (n = 36)P
Temperature, °C    .23 
 <37.5 88 (52) 100 (59) 23 (64)  
 37.5–39.0 64 (38) 55 (32) 13 (36)  
 >39.0 18 (10) 16 (9)  
Cough 73 (43) 83 (49) NA .35 
Refusal to feed or difficulty feeding 42 (35) NA NA <.001 
Rhinorrhea 34 (20) 13 (8) NA .001 
Fatigue 25 (15) 13 (8) NA .05 
Vomiting 24 (14) 11 (6) NA 003 
Diarrhea 19 (11) 15 (9) NA .57 
Drowsiness 16 (9) NA NA <.001 
Respiratory distress 14 (8) NA NA <.001 
Abdominal pain 13 (8) NA NA .001 
Nausea 12 (7) NA NA .001 
Skin rash 10 (6) NA NA .007 
Sore throat 10 (6) NA NA .007 
Dehydration 9 (5) NA NA .013 
Headache 8 (5) NA NA .02 
Cyanosis 2 (1) NA NA .76 
Apnea 2 (1) NA NA .76 
Pulse oximetry <92%a 1 (1) 4 (2) NA <.001 
Tachypnea on admission NA 49 (29) NA <.001 
Tachycardia on admission NA 72 (42) NA <.001 
Signs and SymptomsItalian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Qiu et al4  (n = 36)P
Temperature, °C    .23 
 <37.5 88 (52) 100 (59) 23 (64)  
 37.5–39.0 64 (38) 55 (32) 13 (36)  
 >39.0 18 (10) 16 (9)  
Cough 73 (43) 83 (49) NA .35 
Refusal to feed or difficulty feeding 42 (35) NA NA <.001 
Rhinorrhea 34 (20) 13 (8) NA .001 
Fatigue 25 (15) 13 (8) NA .05 
Vomiting 24 (14) 11 (6) NA 003 
Diarrhea 19 (11) 15 (9) NA .57 
Drowsiness 16 (9) NA NA <.001 
Respiratory distress 14 (8) NA NA <.001 
Abdominal pain 13 (8) NA NA .001 
Nausea 12 (7) NA NA .001 
Skin rash 10 (6) NA NA .007 
Sore throat 10 (6) NA NA .007 
Dehydration 9 (5) NA NA .013 
Headache 8 (5) NA NA .02 
Cyanosis 2 (1) NA NA .76 
Apnea 2 (1) NA NA .76 
Pulse oximetry <92%a 1 (1) 4 (2) NA <.001 
Tachypnea on admission NA 49 (29) NA <.001 
Tachycardia on admission NA 72 (42) NA <.001 

Data in Table 3 from Liu et al3  and Qiu et al.4  In Dong et al,2  no respiratory-support data were reported. For temperature, a 3-way statistical comparison was performed. NA, not available, CONFIDENCE, Coronavirus Infection in Pediatric Emergency Departments.

a

The value of blood oxygenation <92% was considered only for the comparison with Lu et al.3 

Thirteen patients (8%) required respiratory support (Supplemental Table 9). Six of these had coexisting conditions (Table 4).

TABLE 4

Description of Patients With Respiratory Support

SexAgeComorbidityTemperature, °CED SymptomsOxygen Saturation, %Chest Radiograph FindingsLung UltrasoundRespiratory SupportClassification of DiseaseAdmission
Male 8 d None 38.4 Drowsiness, feeding difficulty, dehydration, and respiratory distress 94 Not performed Interstitial syndrome multiple B-lines Low-flow oxygen Moderate COVID-19 ward 
Female 9 d None 37.8 Drowsiness and feeding difficulty 100 Not performed NP High-flow oxygen Mild NICU 
Male 14 d None 38 Drowsiness and fatigue 98 Normal NP Low-flow oxygen Moderate NICU 
Male 2 mo Ventricular septal defect 38.2 Cough, feeding difficulty, and skin rash NA Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Noninvasive ventilation Moderate NICU 
Female 4 mo None 38 Cough, rhinorrhea, and respiratory distress 96 Normal NP Low-flow oxygen Moderate Pediatric ward 
Male 11 mo Propionic acidemia 36.3 Drowsiness, vomiting, and respiratory distress 91 Normal Interstitial syndrome multiple B-lines Low-flow oxygen Severe Pediatric ward 
Male 4 y None 37.3 Cough, vomiting, and respiratory distress 94 Pneumonia with pleural effusion NP Low-flow oxygen Moderate COVID ward 
Female 6 y, 5 mo CHARGE syndrome, epileptic encephalopathy 38.1 Feeding difficulty, and dehydration 97 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP High-flow oxygen Moderate Sub-ICU 
Male 6 y, 5 mo None 37.2 Fatigue, abdominal pain, and respiratory distress 95 Not performed NP Low-flow oxygen Moderate COVID-19 ward 
Male 7 y None 39.3 Cough, fatigue, diarrhea, skin rash vasculitis, and meningeal signs 99 Scissural thickening NP Low-flow oxygen Mild COVID-19 ward 
Male 12 y, 6 mo Autism 36.5 Cough, nausea, vomiting, and respiratory distress 93 Pneumonia NP High-flow oxygen Moderate COVID-19 ward 
Male 14 y, 5 mo Epileptic encephalopathy (tracheotomy) 36.5 Cough, fatigue, drowsiness, dehydration, and respiratory distress 92 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Mechanical ventilation Critical ICU 
Female 15 y, 5 mo Thrombocytopenia, frequent respiratory tract infection 38.8 Cough, rhinorrhea, and respiratory distress 97 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Low-flow oxygen Moderate COVID-19 ward 
SexAgeComorbidityTemperature, °CED SymptomsOxygen Saturation, %Chest Radiograph FindingsLung UltrasoundRespiratory SupportClassification of DiseaseAdmission
Male 8 d None 38.4 Drowsiness, feeding difficulty, dehydration, and respiratory distress 94 Not performed Interstitial syndrome multiple B-lines Low-flow oxygen Moderate COVID-19 ward 
Female 9 d None 37.8 Drowsiness and feeding difficulty 100 Not performed NP High-flow oxygen Mild NICU 
Male 14 d None 38 Drowsiness and fatigue 98 Normal NP Low-flow oxygen Moderate NICU 
Male 2 mo Ventricular septal defect 38.2 Cough, feeding difficulty, and skin rash NA Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Noninvasive ventilation Moderate NICU 
Female 4 mo None 38 Cough, rhinorrhea, and respiratory distress 96 Normal NP Low-flow oxygen Moderate Pediatric ward 
Male 11 mo Propionic acidemia 36.3 Drowsiness, vomiting, and respiratory distress 91 Normal Interstitial syndrome multiple B-lines Low-flow oxygen Severe Pediatric ward 
Male 4 y None 37.3 Cough, vomiting, and respiratory distress 94 Pneumonia with pleural effusion NP Low-flow oxygen Moderate COVID ward 
Female 6 y, 5 mo CHARGE syndrome, epileptic encephalopathy 38.1 Feeding difficulty, and dehydration 97 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP High-flow oxygen Moderate Sub-ICU 
Male 6 y, 5 mo None 37.2 Fatigue, abdominal pain, and respiratory distress 95 Not performed NP Low-flow oxygen Moderate COVID-19 ward 
Male 7 y None 39.3 Cough, fatigue, diarrhea, skin rash vasculitis, and meningeal signs 99 Scissural thickening NP Low-flow oxygen Mild COVID-19 ward 
Male 12 y, 6 mo Autism 36.5 Cough, nausea, vomiting, and respiratory distress 93 Pneumonia NP High-flow oxygen Moderate COVID-19 ward 
Male 14 y, 5 mo Epileptic encephalopathy (tracheotomy) 36.5 Cough, fatigue, drowsiness, dehydration, and respiratory distress 92 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Mechanical ventilation Critical ICU 
Female 15 y, 5 mo Thrombocytopenia, frequent respiratory tract infection 38.8 Cough, rhinorrhea, and respiratory distress 97 Patchy and ground-glasslike opacity and interstitial changes in the lungs NP Low-flow oxygen Moderate COVID-19 ward 

CHARGE, coloboma, heart defects, choanal atresia, growth retardation, genital abnormalities, ear abnormalities; CONFIDENCE, Coronavirus Infection in Pediatric Emergency Departments; NA, not available; NP, not performed.

Imaging findings are collected in Table 5. Three (2%) of the children had a chest CT on admission to the ED, and interstitial abnormalities and opacities were shown in 2 of those children (67%). Chest radiographs were ordered in 62 (36%) cases and revealed unilateral patchy infiltrate with ground-glass abnormalities in 20 (32%) and pneumonia in 14 (23%). In addition, point-of-care lung ultrasound was used in 13 (8%) cases, with 9 of 13 patients <11 months, 1 patient of 2.5 years, and the other 3 patients >10 years. Ultrasound was used as an alternative to a chest radiograph in 11 of 13 cases and as an adjunct tool to further evaluate 2 patients. The first was an 11-month-old patient with severe COVID-19 and a negative chest radiograph result, for whom the ultrasound revealed sonographic interstitial syndrome.8  The second was a 14-year-old patient with respiratory distress and blood oxygenation of 96%, with negative chest radiograph and chest CT results. Ultrasound revealed a right posterior basal consolidation with multiple B-lines. In 11 cases, lung ultrasound revealed sonographic interstitial syndrome9  (Supplementary Fig 1).

TABLE 5

Imaging Findings of Italian Children With COVID-19 Infection, Compared With the Previously Reported Chinese Cohorts

Italian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Qiu et al4  (n = 36)
Chest radiograph, n (%) 62 (36) NA NA 
 Bronchial wall thickening 1 (2) NA NA 
 Interlobal scissural thickening 1 (2) NA NA 
 Interstitial abnormality 20 (32) NA NA 
 Consolidation 14 (23) NA NA 
 Pleural effusion 2 (3)a NA NA 
 Normal 30 (48) NA NA 
Chest CT, n (%) 3 (2) NR 19 (53) 
 Ground-glass opacity 2 (67)b 56 (33) 19 (53) 
 Local patchy shadowing NP 32 (19) NA 
 Bilateral patchy shadowing NP 21 (12) NA 
 Interstitial abnormality 2 (67)b 2 (1) NA 
 Normal 1 (33) NR NR 
Lung ultrasound, n (%) 13 (8) NA NA 
 Sonographic interstitial syndrome8  11 (84)c NA NA 
 Consolidations 5 (38)c NA NA 
 A-patternd 1 (8) NA NA 
 Normal 1 (8) NA NA 
Italian Cohort: CONFIDENCE (n = 170)Lu et al3  (n = 171)Qiu et al4  (n = 36)
Chest radiograph, n (%) 62 (36) NA NA 
 Bronchial wall thickening 1 (2) NA NA 
 Interlobal scissural thickening 1 (2) NA NA 
 Interstitial abnormality 20 (32) NA NA 
 Consolidation 14 (23) NA NA 
 Pleural effusion 2 (3)a NA NA 
 Normal 30 (48) NA NA 
Chest CT, n (%) 3 (2) NR 19 (53) 
 Ground-glass opacity 2 (67)b 56 (33) 19 (53) 
 Local patchy shadowing NP 32 (19) NA 
 Bilateral patchy shadowing NP 21 (12) NA 
 Interstitial abnormality 2 (67)b 2 (1) NA 
 Normal 1 (33) NR NR 
Lung ultrasound, n (%) 13 (8) NA NA 
 Sonographic interstitial syndrome8  11 (84)c NA NA 
 Consolidations 5 (38)c NA NA 
 A-patternd 1 (8) NA NA 
 Normal 1 (8) NA NA 

Data in Table 3 from Liu et al3  and Qiu et al.4  In Dong et al,2  no imaging data were reported. CONFIDENCE, Coronavirus Infection in Pediatric Emergency Department; NA, not available; NP, not performed; NR, not reported.

a

Two patients had multiple chest radiograph findings (consolidation and pleural effusion).

b

Two patients had multiple CT findings (ground-glass opacity and interstitial abnormalities).

c

Five patients had multiple ultrasound findings sonographic (interstitial syndrome and consolidations).

d

The A-pattern is defined as predominant A-lines with normal lung sliding at lung ultrasound. The A-lines are repetitive horizontal echoic lines that arise from the pleural line at regular intervals (skin-pleural line distance). They indicate subpleural air, which completely reflects the ultrasound beam.

In 5 of these patients, who had multiple sonographic findings, a consolidation was reported. All imaging studies were performed during the ED assessment, with attending physicians, physician sonographer, and radiologist unaware of the result of the SARS-CoV-2 swab.

Three patients (7, 7.5, and 9 years old) were diagnosed with multisystem inflammatory syndrome in children (MIS-C) after ED assessment, during admission. Two of these patients were reported in a case series.8  Two patients had ill appearance and multiple symptoms (fatigue, abdominal pain, nausea, vomiting, and difficulty feeding). One patient, who was well appearing during ED assessment, presented with cough, fatigue, diarrhea, and systemic vasculitis and showed later signs of meningeal irritation. All patients were febrile, had high levels of procalcitonin (3.8, 7.5, and 59 ng/mL), and were treated with intravenous immunoglobulin and adjunctive steroids.

Our cohort included 17% asymptomatic, 63% mild, 19% moderate, 1% severe, and 1% critical patients. Asymptomatic patients resulted because the indication to test a patient for SARS-CoV-2, in the early phase of the epidemic, included epidemiological criteria even in asymptomatic patients (eg, recent travel to the Lombardy region or close contact with a SARS-CoV-2–positive patient).

Severe and critical cases were diagnosed in 2 patients with comorbidities. Infants (<1 year) presented more frequently as mild cases. The cumulative admission rate was 43% for clinical reasons and 20% due to local algorithms, which recommended admission for children whatever the disease severity or necessity of isolation (Supplemental Table 2). All patients had been discharged, and no deaths were reported in our cohort.

Our findings were compared with the data available from the Chinese Center for Disease Control and Prevention (CDC)2  and cohorts of Lu et al3  and Qiu et al,4  who described the features of children treated in 3 Chinese hospitals.

The age distribution of the Italian cohort was significantly different because of a larger number of patients <1 year (33%), compared with 18.1% of Lu et al3  and 11.8% of the Chinese CDC data2  (P < .001). The Italian cohort showed a significant difference of familiar versus nonfamiliar exposure compared with Lu et al3  and Qiu et al4  (P < .001). In the cohorts of Lu et al3  and Qiu et al,4  we found a proportion of febrile subjects (41% and 36%, respectively) that was lower than in the Italian cohort even if not significant (relative risk: 0.86 [95% CI: 0.68–1.09] and relative risk: 0.75 [95% CI: 0.47–1.19], respectively). Comparing the Italian cohort with those of Lu et al3  (Table 6), we found a significant prevalence of mild cases as opposed to moderate (P < .001), in particular for patients <1 year (P < .001). Considering the subgroups with mild or moderate disease severity, we found a different distribution in the Italian cohort compared with the published Chinese cohorts.24  The mild to moderate ratio was 3.1 in the Italian cohort, 1.0 in the Chinese CDC data,2  and 0.3 in the cohorts of Lu et al3  and Qiu et al4  Comparing the age distributions of mild and moderate cases between the Italian cohort and Lu et al,3  there is a higher probability of moderate than of mild cases in the Chinese cohort in all the age subgroups.

TABLE 6

Severity of Disease

AsymptomaticMildModerateSevereCriticalTotal
Italian Cohort: CONFIDENCE, n (%)       
 <1 y 5 (5) 26 (26) 7 (7) 1 (1) 0 (0) 39 (39) 
 1–5 y 4 (4) 11 (11) 1 (1) 0 (0) 0 (0) 16 (16) 
 6–10 y 8 (8) 7 (7) 6 (6) 0 (0) 0 (0) 21 (21) 
 >10 y 4 (4) 14 (14) 5 (5) 0 (0) 1 (1) 24 (24) 
 Total 21 (21) 58 (58) 19 (19) 1 (1) 1 (1) 100 (100) 
Lu, et al,3 n (%)       
 <1 y 0 (0) 6 (18) 25 (23) 0 (0) 0 (0) 31 (18) 
 1–5 y 1 (4) 12 (37) 27 (24) 0 (0) 0 (0) 40 (23) 
 6–10 y 14 (52) 10 (30) 34 (31) 0 (0) 0 (0) 58 (34) 
 >10 y 12 (4) 5 (15) 25 (22) 0 (0) 0 (0) 42 (25) 
 Total 27 (16) 33 (19) 111 (65) 0 (0) 0 (0) 171 (100) 
Dong, et al,2,an (%)       
 <1 y — — — — — 86 (11.8) 
 1–5 y — — — — — 137 (18.7) 
 6–10 y — — — — — 171 (23.4) 
 >10 y — — — — — 337 (46.1) 
 Total 94 (12.9)a 315 (43.1)a 300 (41.0)a 18 (2.5)a 3 (0.4)a 731 (100) 
Qiu, et al4,b       
 Total, n (%) 10 (28) 7 (19) 19 (53) 0 (0) 0 (0) 36 (100) 
Between-group comparison, n (%)       
 Italian Cohort: CONFIDENCE 21 (21) 58 (58) 19 (19) 1 (1) 1 (1) 100 (100) 
 Lu et al3  27 (16) 33 (19) 111 (65) b0 (0) 0 (0) 171 (100) 
 Dong et al2  94 (12.9)a 315 (43.1)a 300 (41.0)a 18 (2.5)a 3 (0.4)a 731 (100) 
 Qiu et al4  10 (28) 7 (19) 19 (53) 0 (0) 0 (0) 36 (100) 
AsymptomaticMildModerateSevereCriticalTotal
Italian Cohort: CONFIDENCE, n (%)       
 <1 y 5 (5) 26 (26) 7 (7) 1 (1) 0 (0) 39 (39) 
 1–5 y 4 (4) 11 (11) 1 (1) 0 (0) 0 (0) 16 (16) 
 6–10 y 8 (8) 7 (7) 6 (6) 0 (0) 0 (0) 21 (21) 
 >10 y 4 (4) 14 (14) 5 (5) 0 (0) 1 (1) 24 (24) 
 Total 21 (21) 58 (58) 19 (19) 1 (1) 1 (1) 100 (100) 
Lu, et al,3 n (%)       
 <1 y 0 (0) 6 (18) 25 (23) 0 (0) 0 (0) 31 (18) 
 1–5 y 1 (4) 12 (37) 27 (24) 0 (0) 0 (0) 40 (23) 
 6–10 y 14 (52) 10 (30) 34 (31) 0 (0) 0 (0) 58 (34) 
 >10 y 12 (4) 5 (15) 25 (22) 0 (0) 0 (0) 42 (25) 
 Total 27 (16) 33 (19) 111 (65) 0 (0) 0 (0) 171 (100) 
Dong, et al,2,an (%)       
 <1 y — — — — — 86 (11.8) 
 1–5 y — — — — — 137 (18.7) 
 6–10 y — — — — — 171 (23.4) 
 >10 y — — — — — 337 (46.1) 
 Total 94 (12.9)a 315 (43.1)a 300 (41.0)a 18 (2.5)a 3 (0.4)a 731 (100) 
Qiu, et al4,b       
 Total, n (%) 10 (28) 7 (19) 19 (53) 0 (0) 0 (0) 36 (100) 
Between-group comparison, n (%)       
 Italian Cohort: CONFIDENCE 21 (21) 58 (58) 19 (19) 1 (1) 1 (1) 100 (100) 
 Lu et al3  27 (16) 33 (19) 111 (65) b0 (0) 0 (0) 171 (100) 
 Dong et al2  94 (12.9)a 315 (43.1)a 300 (41.0)a 18 (2.5)a 3 (0.4)a 731 (100) 
 Qiu et al4  10 (28) 7 (19) 19 (53) 0 (0) 0 (0) 36 (100) 

Comparison between age groups and different cohorts. CONFIDENCE, Coronavirus Infection in Pediatric Emergency Departments; —, not applicable.

a

Data are reported only as cumulative. In Dong et al,2 the total number of 731 includes also a missing patient.

b

Mean age, y, 8.3 (SD 3–5).

In this study, we have presented our experience with the diagnosis and treatment of 170 children with COVID-19, from the perspective of 17 EDs in Italy. With the data presented, we confirm what we reported in a preliminary report7  and add new knowledge on the possible late presentation of MIS-C. Even if rare, this condition might be serious and requires prompt recognition, which may not be immediately feasible because of the early presentation of patients (before all symptoms develop) or the presence of different features of the MIS-C (eg, toxic shock syndrome, secondary hemophagocytic lymphohistiocytosis, or macrophage activation syndrome).10 

Our results reveal differences compared with 3 recent Chinese cohorts reported in the literature.24  The higher number of patients aged <1 year is the primary difference finding observed when compared with the wider population of the Chinese CDC data,2  which has a prevalence of COVID-19 in patients aged ≥10 years.

The exposure of the Italian cohort differs from that of the Chinese cohorts because it was highly (>50%) due to exposure outside family clusters (nonfamiliar). This difference may be associated with the delayed lockdown in Italy, imposed on March 8, 5 weeks after the pandemic outbreak. In China, the lockdown occurred 3 weeks after the outbreak was declared a public health emergency of international concern.

Another major difference from previously described COVID-19 cohorts24  is the significant difference in distributions of patients within the disease severity classification. Specifically, our data revealed that children were more frequently categorized as asymptomatic or mild, whereas both Lu et al3  and the CDC2  described a prevalence of moderate cases. These data should not lower the attention and preparedness to COVID-19 because children may represent an important source of viral transmission and amplification.11 

One of the main features defining a moderate, instead of mild, disease status is the presence of pneumonia, which is diagnosed by either chest radiograph or CT scan,2  regardless of the clinical status of the patient (the authors state that this stage may be asymptomatic). In Italian centers, acting independently from one another because no official protocols were available at the time, chest radiographs were performed in a limited number of cases. On the basis of clinical findings, CT scans were performed only in 3 patients because the use of CT scan was considered unnecessary for COVID-19 diagnosis, without any aggravation of the final outcome.

Radiologic imaging was obtained at the discretion of the treating physician at every ED. For this reason, the number of radiologic images obtained may reflect the true behavior of Italian pediatricians in obtaining imaging, which, in such circumstances, was clinically oriented, in the absence of official specific guidelines.

Diversely, all of the patients included in the Qiu et al4  series underwent a chest CT. In Lu et al3  and the CDC report,2  there is no information about the rate of chest radiograph or CT used to define the severity of disease. The minimal use of chest CT in our experience could have determined the reduced number of cases classified as moderate, also defined as patients presenting no signs and symptoms at clinical evaluation and radiologic but subclinical lung lesions by means of a chest CT.

To accurately compare reports by using homogeneous classifications, we suggest that a clinically driven classification, rather than a radiologic one, could be more helpful for the appropriate clinical diagnosis of children with COVID-19.

A classification of disease severity will help clinicians predict patient needs, plan appropriate ED flow management, and obtain optimal allocation of resources (eg, necessity of a blood test, imaging, or admission).

Conversely, including a radiologic diagnosis of pneumonia as a disease-classification criterion may lead physicians to routinely perform chest CT in children with COVID-19, increasing radiation risk, resource use, and the contagion risk of other healthy workers,12  without additional benefit to the child.

A key question remains unsolved: that is, trying to manage children (as well adults) with COVID-19 in an evidence-based way, despite the limitation of evidence-based interventions at our disposal. Within this context, radiologic imaging (especially chest CT) does not represent, in our opinion, best practice because of the high number of asymptomatic and mild cases and, in addition, no single finding can reliably differentiate pneumonia of any etiology from other causes of childhood respiratory illness,13  and pediatricians are aware of the radiation-induced risk for children.1418 

Chest CT improves diagnostic capabilities, but its use comes with a well-demonstrated increased risk of solid cancer or leukemia.14  From a patient perspective, the benefits of a medically necessary CT scan exceed the small increase in radiation-induced cancer risk. Once more, because of the high number of asymptomatic and mild cases of COVID-19 (which in our cohort resulted even higher), chest CTs could be unnecessary for the assessment of the disease severity.

Point-of-care lung ultrasound, which allows for accurate and high-quality investigations without using ionizing radiation, could represent a reasonable alternative for assessing interstitial syndrome and, also, detecting consolidations in children.19  In our experience, 11 of 13 (84%) patients investigated by using a lung ultrasound has positive results for sonographic findings of interstitial syndrome, with 5 of them showing an associated consolidation. Because, in adults who are COVID-19–positive, lung ultrasound abnormalities have been described before clinical manifestations and virus detection, ultrasound has been proposed as a tool for early diagnosis.19,20  For children presenting to EDs, an ultrasound approach by expert sonographers could represent an adjunct tool for achieving a rapid severity assessment of COVID-19 lung involvement and tracing the disease evolution. However, we must acknowledge that not all pediatricians may have the proper skills to perform this examination properly, although they could be rapidly trained in lung ultrasound during an emergency situation, such as this.

Considering the different mortality rates across nations and variation of our cohort from the other pediatric cohorts, in further studies, researchers should investigate the possibility of a variable expression of COVID-19 in populations. Some of the differences we highlighted could be explained by the disparity between health systems, which can lead to a limited number of patients accessing hospitals resources.

Our study has some limitations. First, the nature of the study is retrospective. Secondly, the real number of children with a SARS-CoV-2 infection is still unknown in Italy and other countries currently affected by this epidemic. Although we provided a statistical comparison between an Italian cohort and the most representative Chinese studies to date, the scope of this work is not epidemiological because there are currently no estimations of the real disease prevalence among populations, especially in the asymptomatic patient group. For this reason, the real prevalence of COVID-19, its spectrum of presentation, and the real mortality rate remain unknown. Moreover, the reported death rates across countries are heterogeneous, suggesting a lack of uniform case definitions,21  possibly due to different patient enrollment settings (hospitalized children [Lu et al3  and Qiu et al4 ] and the Chinese CDC registry [Dong et al2 ]). Last, we may have missed some of the initial clinical features related to COVID-19. Patients presented to EDs at different stages of illness onset, and the clinical spectrum of the disease may have varied in those patients. Our data collection included only clinical information gathered during ED evaluation and not reports of previously experienced disease-related symptoms, possibly resulting in bias during each clinical observation.

This may lead to an overestimation of more severe cases (moderate to critical), although, with our results, we demonstrated that these numbers are lower than what has been previously reported.

Our population may be not representative of the real COVID-19 spectrum of disease in Italian children, and the comparison with Chinese cohorts may, therefore, be biased. For further analysis, we will collect additional data and perform more effective statistical estimations.

In this preliminary report, we describe the clinical profile of COVID-19 pediatric patients from the ED perspective and detail two major observations. First, the most fundamental task regarding the management of pediatric COVID-19 patients in the ED is represented by the organizational burden (eg, management of patient flow), rather than any one specific clinical task.21 

Italian children with COVID-19 infrequently had notable disease symptoms at ED admission. Nonetheless, rare but severe presentations of SARS-CoV-2 infection, such as MIS-C, should be taken into consideration. Second, pediatric patients with COVID-19 may benefit from undergoing fewer diagnostic tests than adult patients. Because children may represent an important channel for viral transmission and amplification, pediatric EDs have the challenge of differentiating among those patients with suspected COVID-19 with alternative methods of case identification and classification and through a proper allocation of resources and treatment. Strong collaboration is needed at different levels of the health care system and across countries to optimize public availability of reliable real-time data22  and apply our data to larger pediatric populations.

Idanna Sforzi, MD (Department of Emergency Medicine and Trauma Center, Meyer Children’s Hospital, University of Florence, Florence, Italy); Martina Giacalone, MD (Department of Emergency Medicine and Trauma Center, Meyer Children’s Hospital, University of Florence, Florence, Italy); Sandra Trapani, PhD (Department of Health Science, University of Florence, Florence, Italy); Maria Carmela Leo, PhD (Scientific Secretariat of the Paediatric Ethics Committee of the Tuscany Region, Florence, Italy); Martina Falconi (Scientific Secretariat of the Paediatric Ethics Committee of the Tuscany Region, Florence, Italy); Giuseppe Indolfi, MD (Department Neurofarba University of Florence and Meyer Children’s University Hospital, Florence, Italy); Lorenzo D’Antiga, MD (Department of Pediatrics, Papa Giovanni XXIII Hospital, Bergamo, Italy); Angelo Mazza, MD (Department of Pediatrics, Papa Giovanni XXIII Hospital, Bergamo, Italy); Donatella De Martiis, MD (Pediatric Emergency Department, Presidio Ospedale dei Bambini, ASST Spedali Civili, Brescia, Italy); Giuseppe Bertolozzi, MD (Pediatric Emergency Department, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy); Paola Marchisio, MD (Department of Health Science, University of Florence, Florence, Italy and Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Pediatric highly ICU, Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy); Giovanna Chidini, MD (Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Pediatric ICU, Milan, Italy); Edoardo Calderini, MD (Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Pediatric ICU, Milan, Italy); Andrea Gori, MD (Department of Health Science, University of Florence, Florence, Italy and Infectious Diseases Unit, Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy); Claudia Bondone, MD (Department of Pediatric Emergency, Regina Margherita Children's Hospital, A.O.U. Città della Salute e della Scienza di Torino, Turin, Italy); Daniele Donà, MD (Department for Woman and Child Health, Pediatric Emergency Department, University of Padua, Padua, Italy); Marco Todeschini, MD (Department for Woman and Child Health, Pediatric Emergency Department, University of Padua, Padua, Italy); Martina Scilipoti, MD (Department of Pediatric Emergency Medicine, Bambino Gesù Children's Hospital Istituto di Ricovero e Cura a Carattere Scientifico, Rome, Italy); Davide Silvagni, MD (Department of Neonatal and Paediatric Critical Care, Verona University Hospital, Verona, Italy); Paola Cogo, MD (Division of Paediatrics, Department of Medicine, Academic Hospital Santa Maria della Misericordia, University of Udine, Udine, Italy); Francesca Ginocchio, MD (Department of Neonatal and Paediatric Critical Care, Verona University Hospital, Verona, Italy); Valeria Spica Russotto, MD (Department of Pediatrics, Ospedale San Jacopo, Pistoia, Italy); Luca Pierantoni, MD (Department of Pediatrics, Lodi Hospital, Lodi, Italy); Mauro Margherita, MD (Ospedale Santa Maria degli Angeli, Pordenone, Italy); Stefano Maiandi, MSN (Department of Healthcare Professions, ASST of Lodi, Lodi, Italy); Barbara Tubino, MD (Istituto di Ricovero e Cura a Carattere Scientifico Istituto Gaslini, Genova, Italy); Antonio Chiaretti, MD (Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli, Istituto di Ricovero e Cura a Carattere Scientifico, Rome, Italy, and Department of Neonatal and Paediatric Critical Care, Verona University Hospital, Verona, Italy); Alfonso Mazzuca, MD (Azienda Sanitaria Cosenza, Cosenza, Italy); Iuri Corsini, MD (Division of Neonatology, Careggi University Hospital of Florence, Florence, Italy).

Dr Parri conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Lenge designed the data collection instruments, was the data manager, drafted the initial manuscript, and reviewed and revised the manuscript; Drs Cantoni, Arrighini, Romanengo, Urbino, Da Dalt, Verdoni, Giacchero, Lanari, Musolino, Biban, La Fauci, Pilotto, Buonsenso, Chiossi, Agostiniani, Plebani, Barbieri, and Zampogna coordinated and supervised data collection at their sites, served as data managers at their institutions, and critically reviewed the manuscript for important intellectual content; Dr Agostoni critically reviewed and revised the manuscript and overviewed the revisions of the manuscript; Dr De Masi provided statistical analysis and helped draft the manuscript; Dr Masi helped with study design and overviewed the study; all members of the Coronavirus Infection in Pediatric Emergency Department research group actively contributed to the study development at their sites, data collection, and development of the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

     
  • CDC

    Center for Disease Control and Prevention

  •  
  • CI

    confidence interval

  •  
  • COVID-19

    coronavirus disease 2019

  •  
  • CT

    computed tomography

  •  
  • ED

    emergency department

  •  
  • MIS-C

    multisystem inflammatory syndrome in children

  •  
  • SARS-CoV-2

    severe acute respiratory syndrome coronavirus 2

1
Grasselli
G
,
Pesenti
A
,
Cecconi
M
.
Critical care utilization for the COVID-19 outbreak in Lombardy, Italy: early experience and forecast during an emergency response
.
JAMA
.
2020
;
323
(
16
):
1545
1546
2
Dong
Y
,
Mo
X
,
Hu
Y
, et al
.
Epidemiology of COVID-19 among children in China
.
Pediatrics
.
2020
;
145
(
6
):
e20200702
3
Lu
X
,
Zhang
L
,
Du
H
, et al.;
Chinese Pediatric Novel Coronavirus Study Team
.
SARS-CoV-2 infection in children
.
N Engl J Med
.
2020
;
382
(
17
):
1663
1665
4
Qiu
H
,
Wu
J
,
Hong
L
,
Luo
Y
,
Song
Q
,
Chen
D
.
Clinical and epidemiological features of 36 children with coronavirus disease 2019 (COVID-19) in Zhejiang, China: an observational cohort study
.
Lancet Infect Dis
.
2020
;
20
(
6
):
689
696
5
Italian National Health Institute (Istituto Superiore di Sanità)
. Coronavirus epidemic: situation report – May, 4. Available at: https://www.epicentro.iss.it/coronavirus/bollettino/Infografica_4maggio%20ITA.pdf. Accessed May 6, 2020
6
Harris
PA
,
Taylor
R
,
Thielke
R
,
Payne
J
,
Gonzalez
N
,
Conde
JG
.
Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support
.
J Biomed Inform
.
2009
;
42
(
2
):
377
381
7
Parri
N
,
Lenge
M
,
Buonsenso
D
;
Coronavirus Infection in Pediatric Emergency Departments (CONFIDENCE) Research Group
.
Children with Covid-19 in pediatric emergency departments in Italy
.
N Engl J Med
.
2020
;
383
(
2
):
187
190
8
Verdoni
L
,
Mazza
A
,
Gervasoni
A
, et al
.
An outbreak of severe Kawasaki-like disease at the Italian epicentre of the SARS-CoV-2 epidemic: an observational cohort study
.
Lancet
.
2020
;
395
(
10239
):
1771
1778
9
Volpicelli
G
,
Elbarbary
M
,
Blaivas
M
, et al.;
International Liaison Committee on Lung Ultrasound (ILC-LUS) for International Consensus Conference on Lung Ultrasound (ICC-LUS)
.
International evidence-based recommendations for point-of-care lung ultrasound
.
Intensive Care Med
.
2012
;
38
(
4
):
577
591
10
Feldstein
LR
,
Rose
EB
,
Horwitz
SM
, et al.;
Overcoming COVID-19 Investigators
;
Centers for Disease Control and Prevention COVID-19 Response Team
.
Multisystem inflammatory syndrome in U.S. children and adolescents
.
N Engl J Med
.
2020
;
383
(
4
):
334
346
11
Cao
Q
,
Chen
Y-C
,
Chen
C-L
,
Chiu
C-H
.
SARS-CoV-2 infection in children: transmission dynamics and clinical characteristics
.
J Formos Med Assoc
.
2020
;
119
(
3
):
670
673
12
Buonsenso
D
,
Pata
D
,
Chiaretti
A
.
COVID-19 outbreak: less stethoscope, more ultrasound
.
Lancet Respir Med
.
2020
;
8
(
5
):
e27
13
Shah
SN
,
Bachur
RG
,
Simel
DL
,
Neuman
MI
.
Does this child have pneumonia?: the rational clinical examination systematic review
.
JAMA
.
2017
;
318
(
5
):
462
471
14
Miglioretti
DL
,
Johnson
E
,
Williams
A
, et al
.
The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk
.
JAMA Pediatr
.
2013
;
167
(
8
):
700
707
15
Brenner
DJ
,
Hall
EJ
.
Computed tomography–an increasing source of radiation exposure
.
N Engl J Med
.
2007
;
357
(
22
):
2277
2284
16
Mathews
JD
,
Forsythe
AV
,
Brady
Z
, et al
.
Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians
.
BMJ
.
2013
;
346
:
f2360
17
Pearce
MS
,
Salotti
JA
,
Little
MP
, et al
.
Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study
.
Lancet
.
2012
;
380
(
9840
):
499
505
18
Brenner
D
,
Elliston
C
,
Hall
E
,
Berdon
W
.
Estimated risks of radiation-induced fatal cancer from pediatric CT
.
AJR Am J Roentgenol
.
2001
;
176
(
2
):
289
296
19
Soldati
G
,
Smargiassi
A
,
Inchingolo
R
, et al
.
Is there a role for lung ultrasound during the COVID-19 pandemic?
J Ultrasound Med
.
2020
;
39
(
7
):
1459
1462
20
Buonsenso
D
,
Piano
A
,
Raffaelli
F
,
Bonadia
N
,
de Gaetano Donati
K
,
Franceschi
F
.
Point-of-care lung ultrasound findings in novel coronavirus disease-19 pnemoniae: a case report and potential applications during COVID-19 outbreak
.
Eur Rev Med Pharmacol Sci
.
2020
;
24
(
5
):
2776
2780
21
Chidini
G
,
Villa
C
,
Calderini
E
,
Marchisio
P
,
De Luca
D
.
SARS-CoV-2 infection in a pediatric department in milan: a logistic rather than a clinical emergency
.
Pediatr Infect Dis J
.
2020
;
39
(
6
):
e79
e80
22
Lazzerini
M
,
Putoto
G
.
COVID-19 in Italy: momentous decisions and many uncertainties
.
Lancet Glob Health
.
2020
;
8
(
5
):
e641
e642

Competing Interests

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

Supplementary data