Literature DB >> 32566557

Clinical characteristics of children with COVID-19: a rapid review and meta-analysis.

Zijun Wang1, Qi Zhou2, Chenglin Wang3,4,5, Qianling Shi2, Shuya Lu6,7, Yanfang Ma1, Xufei Luo8, Yangqin Xun1, Weiguo Li3,4,5, Muna Baskota3,4,5, Yinmei Yang3,4,5, Hui Zhai3,4,5, Toshio Fukuoka9,10, Hyeong Sik Ahn11,12, Myeong Soo Lee13,14, Zhengxiu Luo3,4,5, Enmei Liu3,4,5, Yaolong Chen1,15,16,17.   

Abstract

BACKGROUND: Most guidelines on COVID-19 published so far include recommendations for patients regardless of age. Clinicians need a more accurate understanding of the clinical characteristics of children with COVID-19.
METHODS: We searched studies reporting clinical characteristics in children with COVID-19 published until March 31, 2020. We screened the literature, extracted the data and evaluated the risk of bias and quality of evidence of the included studies. We combined some of the outcomes (symptoms) in a single-arm meta-analysis using a random-effects model.
RESULTS: Our search retrieved 49 studies, including 25 case reports, 23 case series and one cohort study, with a total of 1,667 patients. Our meta-analysis showed that most children with COVID-19 have mild symptoms. Eighty-three percent of the children were within family clusters of cases, and 19% had no symptoms. At least 7% with digestive symptoms. The main symptoms of children were fever [48%, 95% confidence interval (CI): 39%, 56%] and cough (39%, 95% CI: 30%, 48%). The lymphocyte count was below normal level in only 15% (95% CI: 8%, 22%) of children which is different from adult patients. 66% (95% CI: 55%, 77%) of children had abnormal findings in CT imaging.
CONCLUSIONS: Most children with COVID-19 have only mild symptoms, and many children are asymptomatic. Fever and cough are the most common symptoms in children. Vomiting and diarrhea were not common in children. The lymphocyte count is usually within the normal range in children. 2020 Annals of Translational Medicine. All rights reserved.

Entities:  

Keywords:  COVID-19; Children; clinical characteristics; meta-analysis; rapid review

Year:  2020        PMID: 32566557      PMCID: PMC7290619          DOI: 10.21037/atm-20-3302

Source DB:  PubMed          Journal:  Ann Transl Med        ISSN: 2305-5839


Introduction

In December 2019, a previously unknown type of pneumonia broke out in Wuhan, China, which was later confirmed to be caused by a novel type of beta coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). In February 2020, the World Health Organization (WHO) officially named the disease as “Coronavirus Disease 2019 (COVID-19)” (1). Like MERS-CoV and SARS-CoV, SARS-CoV-2 can also be transmitted between humans (2-5). Since the occurrence of COVID-19 case (6,7), the disease is spreading rapidly. WHO reassessed the potential impact of COVID-19 on global public health and subsequently declared COVID-19 as Public Health Emergency of International Concern (PHEIC) on January 30, 2020. Research has proven that people of all ages are susceptible to SARS-CoV-2. The mean age of COVID-19 patients was 47 years, with 55% of the patients being between 15 and 49 years old. Only 9% of the patients were under 15 years old (8). For this reason, most of the guidelines published so far include recommendations for patients regardless of age, only a few recommendations are for children. Although the great majority of patients are adults, children’s respiratory structural characteristics and immune response system differ essentially from those in adult (9-11), and the diagnostic criteria and management according to recommendations targeting adults may not be appropriate for children. Our study aims therefore to identify the clinical features of children with COVID-19, help clinicians to confirm and treat the suspected children as soon as possible, and provide support for the development of guidelines for COVID-19 in children. We present the following article in accordance with the PRISMA reporting checklist (available at http://dx.doi.org/10.21037/atm-20-3302).

Methods

Search strategy

We comprehensively searched the following electronic databases: Cochrane library, MEDLINE (via PubMed), Embase, Web of Science, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), and Wanfang Data from their inception until March 31, 2020 with the terms “2019-novel coronavirus”, “SARS-CoV-2”, “COVID-19”, “2019-nCoV”, “clinical features” and their derivatives. We also searched WHO, Chinese Center for Disease Control and Prevention (CCDC), National Health Commission of the People’s Republic of China, USA National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov), the ISRCTN registry, Google Scholar and the preprint servers medRxiv (https://www.medrxiv.org/), bioRxiv (https://www.biorxiv.org/) and SSRN (https://www.ssrn.com/index.cfm/en/). In addition, we searched the reference lists of the identified studies for further potential studies. The full search strategy can be found in Supplementary I.

Inclusion and exclusion criteria

We included studies on children (aged <18 years) with COVID-19 that report clinical features of patients, such as symptoms, signs, laboratory examinations and imaging manifestations. Diagnosis of COVID-19 was based on the Novel Coronavirus Pneumonia Prevention and Control Program (7th edition) issued by the National Health and Health Committee of China (12) and surveillance case definitions for human infection with novel coronavirus (nCoV) Interim guidance v2 issued by WHO (13). We excluded in vitro studies, Traditional Chinese Medicine studies, conference abstracts, comments, letters, and duplicates, and studies where we could not extract the data. We made no restrictions on language and publication status.

Study selection

Two reviewers (ZW and CW) selected the studies independently after first eliminating duplicates. The bibliographic software EndNote was used and any discrepancies were settled by discussion, consulting a third reviewer (QZ) if necessary. Before the formal selection, the reviewers searched a random sample of 50 citations. The reviewers screened first all titles and abstracts with the pre-defined criteria, and categorized the articles into three (eligible, not eligible, and unclear) groups. In the second step, full-texts of those potentially eligible or unclear studies were reviewed to identify the final inclusion. All the reasons for exclusion of ineligible studies were recorded, and the process of study selection was documented using a PRISMA flow diagram (14,15)).

Data extraction

Two reviewers (QS and SL) extracted the data independently with a standardized data collection form, including: (I) basic information (e.g., first author); (II) symptoms; (III) routine blood tests (e.g., leucocyte count); (IV) blood biochemistry [e.g., alanine aminotransferase (ALT)]; (V) coagulation function (e.g., activated partial thromboplastin time); (VI) imaging findings (e.g., abnormal imaging). For dichotomous outcomes, we abstracted the number of events and total participants per group. For continuous outcomes, we abstracted means, standard deviations (SD), and the number of total participants in per group. Outcomes with no events were reported, but these were excluded from the meta-analysis. If means and SD were not reported, we calculated them from the reported indicators (16). If data were missing or reported in an unusable way, we excluded the study from the meta-analysis and report the findings descriptively.

Risk of bias assessment

Two reviewers (ZW and CW) assess the risk of bias in each study independently. Discrepancies were settled by discussion, consulting a third reviewer (QZ) if necessary. For randomized controlled trials (RCTs), we will assess the risk of bias independently using Cochrane risk-of-bias tool (17). It consists of seven domains, for each, we will grade as “Low”, “Unclear”, and “High”. For nonrandomized controlled trials (nRCTs), ROBINS-I tool will be used (18). It consists of seven domains, for each, we will grade as “Low risk”, “Moderate risk”, “Serious risk”, “Critical risk”, and “No information”. For case-control and cohort studies, the Newcastle-Ottawa Scale will be used (19). It consists of eight domains, for each, we will grade with stars. The more stars, the lower the risk of bias. For cross-sectional studies, we use a methodology evaluation tool recommended by Agency for Healthcare Research and Quality (AHRQ) (20). This tool assesses the quality of bias according to 11 criteria. And each criterion is answered by “Yes”, “No” or “Unsure”. For case reports and case series, we used a methodology evaluation tool recommended by National Institute for Health and Care Excellence (NICE) (21). The risk of bias is evaluated according to eight criteria. The results were summarized by scoring method, for the “Yes” items, the score was 1, and for the “No” items, the score was 0. The higher the total score, the lower the risk of bias.

Data synthesis

We summarized the results of the studies including less than nine patients and did meta-analysis of included studies that have at least nine patients. For dichotomous outcomes, we did a meta-analysis of proportions, reporting the effect size (ES) with 95% confidence intervals (CI). For continuous outcomes, we did a meta-analysis of continuous variable, calculating the ES with 95% CI. We described the results of the studies with patients that below nine. As clinical and methodological heterogeneity in the study design, characteristics of participants, interventions and outcome measures was expected, we used random-effects models (22). Two-sided P values <0.05 were considered statistically significant. Heterogeneity was defined as P values <0.10 and I2>50%. All analyses were performed in STATA version 14.

Quality of the evidence assessment

Two reviewers (QZ and YX) assessed the quality of main evidence independently using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. We produced a “Summary of Findings” table using the GRADE pro software (23,24). Direct evidence from RCTs is first set as high quality, and evidence from observational studies as low quality. Then initial quality can then be downgraded for five reasons (study limitations, consistency of effect, imprecision, indirectness, and publication bias) and upgraded for three reasons (large magnitude of effect, dose-response relation and plausible confounders or biases) (25-30). Finally, the quality of main evidence can be classified as high, moderate, low, or very low, which reflects the extent to what we can be confident that the effect estimates are correct. As COVID-19 is a PHEIC and the situation is evolving rapidly, our study was not registered in order to speed up the process (31).

Results

Study selection and characteristics

Our initial search retrieved 774 records (). After removing duplicates, we screened the titles, abstracts and full texts, and 49 studies were finally included. The articles included 25 case reports, 23 case series and one cohort study. The studies included a total of 1,667 patients: 955 males and 712 females. Eighteen percent of children were aged less than 1 year. Most of the studies were carried out in China, including 17 studies from Hubei (). One study was from Singapore, one from Korea, one from Vietnam and one from Iran. The results on risk of bias are reported in Supplementary II, and quality of the evidence in Supplementary III.
Figure 1

Flow diagram.

Table 1

Characteristics of included studies

First authorStudy locationNumberAge (year)Study design
AllMF
Deng 2020, (32)Xian2118.0±7.1Case report
Cai 2020, (33)Shanghai1107Case report
Zhang 2020, (34)Hunan1010.2 (0.1, 0.3)Case report
Wei 2020, (35)Hubei9270.58 (0.28, 0.79)Case series
Chen 2020, (36)Hubei1101.1Case report
Zeng 2020, (37)Hubei1100Case report
Feng 2020, (38)Shenzhen155108.0±2.9Case series
Wang 2020, (39)Hubei1105.6Case report
Quan 2020, (40)Liaoning1014Case report
Xiong 2020, (41)Chongqing2115.2/5.2Case report
Cai 2020, (42)Shanghai10466.5 (4.0, 9.0)Case series
Wang 2020, (43)Xian3115167.9±4.0Case series
Tang 2020, (44)Shenzhen269176.90±0.70Case series
Liu 2020, (45)Hubei6243.0 (3.0, 4.0)Case report
Lu 2020, (46)Hubei171104677.1±2.8Case series
Ma 2020, (47)Hubei5028222.5 (0.9, 7.0)Case series
Zhao 2020, (48)Zhejiang11013Case report
Li 2020, (49)Hubei3018126.5±3.4Case series
Zhang 2020, (50)Shandong10375.7±4.2Case series
Zhang 2020, (51)Hunan2021.2/1.2Case report
Liu 2020, (52)Hubei1109Case report
Xiao 2020, (53)Chongqing1017.83Case report
Xu 2020, (54)Chongqing3217159.0±4.7Case series
Chan 2020, (55)Hong Kong11010Case report
Kam 2020, (56)Singapore1100.5Case report
Park 2020, (57)Korea10110Case report
Du 2020, (58)Shandong14687.1±4.7Case series
Liu 2020, (59)Shanghai4223.8±4.1Case report
Wang 2020, (60)Hubei1100Case report
Rahimzadeh 2020, (61)Iran9635.0 (3.5, 5.5)Case series
Ji 2020, (62)Beijing2209/15Case report
Xu 2020, (63)Guangzhou10646.6 (1.8, 13.7)Case series
Xia 2020, (64)Hubei201374.7±3.9Case series
Dong 2020, (65)Shanghai73142031110 (NR)Case series
Xing 2020, (66)Hong Kong3211.5/2.5/3.6Case report
Yu 2020, (67)Hubei825131NR [0–16]Case series
Liu 2020, (68)Hubei915635NACase series
Ma 2020, (69)Hubei1157342NACase series
Qian 2020, (70)Zhejiang2021.1Case report
Qiu 2020, (71)Zhejiang3623138.3±3.5Cohort study
Zhang 2020, (72)Hubei2514113.0 (2.0, 9.0)Case series
Sun 2020, (73)Hubei8625.0 (1.0, 13.7)Case report
Dong 2020, (74)Hubei2203/2.3Case report
Wu 2020, (75)Shandong7444306.0 (0.1, 15.1)Case series
Su 2020, (76)Shandong9363.6 (1.8, 6.8)Case series
Le 2020, (77)Vietnam1010.3Case report
Zhong 2020, (78)Hunan9458 (1.5, 10.0)Case series
Yang 2020, (79)Shandong10374 (2, 8)Case series
Tang 2020, (80)Zhejiang11010Case report

Ages were reported either as mean ± SD, or median (interquartile range), or single year. †, This article once has been retracted and republished by SSRN, now the data was updated with the new article. SD, standard deviation; NR, not report; NA, not applicable.

Flow diagram. Ages were reported either as mean ± SD, or median (interquartile range), or single year. †, This article once has been retracted and republished by SSRN, now the data was updated with the new article. SD, standard deviation; NR, not report; NA, not applicable.

Symptoms and imaging results

All of the included studies reported the symptoms of children with COVID-19. The results showed that 83% (95% CI: 78%, 88%) of the cases had likely acquired the infection from their family members with COVID-19. Ninety-four percent (95% CI: 90%, 98%) of children were mild cases and 3% (95% CI: 2%, 4%) were severe case. Among the children with severe symptoms that reported symptom clearly, 9 children have comorbidity, 10 children have gastrointestinal symptoms and 4 children have concurrent infection. Only two children were dead that has been reported in our included studies (46,65). The main symptoms were fever [48% (95% CI: 39%, 56%)], cough [39% (95% CI: 30%, 48%)]. Thirty percent (95% CI: 18%, 42%) of children had both cough and fever. Seven percent (95% CI: 5%, 9%) and 6% (95% CI: 4%, 9%) of cases had diarrhea and nausea/vomiting. The proportion of children with more than one symptom was 35% (95% CI: 21%, 48%), and 19% (95% CI: 14%, 23%) of all children were asymptomatic. Forty-two studies reported the imaging features of children with COVID-19, including 19 case series and 23 case reports. Sixty-six percent (95% CI: 55%, 77%) had abnormal imaging. Thirty-five percent (95% CI: 26%, 44%) of children had ground-glass opacity. More information can be found in and Supplementary IV.
Table 2

Symptoms and imaging results of patients with COVID-19

VariableESI2 (%)P value
The overall symptoms
   No Symptom19% (14%, 23%)70.7<0.10
   Mild symptom94% (90%, 98%)89.9<0.10
   Severe symptom3% (2%, 4%)22.50.24
   More than one sign or symptom35% (21%, 48%)80.8<0.10
Specific symptoms
   Fever48% (39%, 56%)85.7<0.10
   Cough39% (30%, 48%)84.4<0.10
   Fever and cough30% (18%, 42%)67.4<0.10
   Sputum production19% (0%, 44%)97.5<0.10
   Rhinorrhea9% (6%, 12%)0.00.64
   Shortness of breath/dyspnea9% (0%, 19%)91.8<0.10
   Myalgia or fatigue8% (5%, 12%)56.7<0.10
   Diarrhea7% (5%, 9%)0.00.62
   Nausea or vomiting6% (4%, 9%)0.01.00
   Nasal obstruction6% (3%, 9%)0.00.59
   Sore throat6% (2%, 10%)35.20.13
   Headache4% (1%, 6%)0.00.61
Imaging findings
   Abnormal66% (55%, 77%)89.6<0.10
   Unilateral pneumonia31% (20%, 43%)81.5<0.10
   Bilateral pneumonia28% (20%, 36%)81.3<0.10
   Ground-glass opacity35% (26%, 44%)84.7<0.10

ES, effect size.

ES, effect size.

Laboratory results

Seventeen case series reported the results of routine blood tests. The mean leucocyte count in children was 6.25×109/L (95% CI: 5.97, 6.54). Fifteen percent (95% CI: 4%, 26%) of cases had leucocyte count above the normal range and 28% (95% CI: 17%, 38%) of cases below the normal range. The mean lymphocyte count in children was 2.84×109/L (95% CI: 2.55, 3.13). Lymphocyte count was elevated in 41% (95% CI: 2%, 80%) and below normal in 15% (95% CI: 8%, 22%) of children. Eighteen case series reported the results of blood biochemistry tests. The mean value of ALT was 20.46 U/L (95% CI: 14.51, 26.41), and 11% (95% CI: 8%, 14%) of cases had elevated ALT values. The mean value of aspartate aminotransferase (AST) was 32.04 U/L (95% CI: 30.25, 33.83), and 15% (95% CI: 9%, 21%) of cases had elevated AST values. The mean value of C-reactive protein (CRP) was 5.05 mg/L (95% CI: 1.86, 8.24), and CRP was elevated in 22% (95% CI: 15%, 28%) of the children. Nine case series reported coagulation function test, the mean value of D-dimer was 0.33 mg/L (95% CI: 0.17, 0.49) in studies of children with COVID-19. Fifteen percent (95% CI: 7%, 22%) of cases above the normal range of D-dimer value. More information can be found in and Supplementary IV.
Table 3

Laboratory results of children with COVID-19

Laboratory resultsESI2 (%)P value
Routine blood values
   Leucocytes (×109/L)6.60 (6.19, 7.01)65.9<0.10
   Above normal range15% (4%, 26%)77.3<0.10
   Below normal range28% (17%, 39%)85.7<0.10
   Lymphocytes (×109/L)2.76 (2.47, 3.05)75.7<0.10
   Above normal range41% (3%, 78%)98.3<0.10
   Below normal range15% (8%, 22%)79.9<0.10
   Neutrophils (×109/L)2.70 (2.10, 3.31)93.8<0.10
   Above normal range23% (0%, 48%)85.8<0.10
   Below normal range24% (4%, 44%)58.5<0.10
   Platelets (×109/L)257.09 (251.06, 263.13)0.00.88
   Above normal range10% (3%, 17%)45.50.14
   Below normal range7% (0%, 19%)84.4<0.10
   Hemoglobin (g/L)127.61 (123.80, 131.41)87.4<0.10
   Above normal range13% (4%, 22%)58.4<0.10
   Below normal range7% (0%, 14%)53.60.12
Blood biochemistry
   Albumin (g/L)45.30 (45.13, 45.47)0.00.70
   Below normal range35% (25%, 45%)0.00.33
   Alanine aminotransferase (U/L)20.46 (14.51, 26.41)96.9<0.10
   Above normal range11% (8%, 14%)0.00.72
   Aspartate aminotransferase (U/L)32.04 (30.25, 33.83)49.2<0.10
   Above normal range15% (9%, 21%)45.8<0.10
   Total bilirubin (μmol/L)8.14 (1.45, 14.82)97.5<0.10
   Above normal range3% (0%, 6%)NANA
   Blood urea nitrogen (mmol/L)3.81 (3.43, 4.18)0.00.56
   Above normal range12% (0%, 33%)94.9<0.10
   Below normal range14% (0%, 35%)57.60.13
   Creatinine (μmol/L)41.60 (32.98, 50.22)95.6<0.10
   Above normal range12% (0%, 33%)94.9<0.10
   Below normal range8% (3%, 14%)0.00.59
   Creatine kinase (U/L)104.37 (95.66, 113.08)56.60.10
   Above normal range13% (0%, 38%)77.0<0.10
   Lactate dehydrogenase (U/L)264.43 (241.85, 287.02)98.1<0.10
   Above normal range38% (25%, 51%)72.9<0.10
   Below normal range11% (0%, 32%)NANA
   Myoglobin (μg/L)15.33 (11.18, 19.48)NANA
   Procalcitonin (g/L)0.06 (0.00, 0.16)0.01.00
   Above normal range44% (20%, 69%)98.0<0.10
   CRP (mg/L)5.05 (1.86, 8.24)86.9<0.10
   Above normal range22% (15%, 29%)71.3<0.10
Coagulation function
   Activated partial thromboplastin time (s)37.59 (28.69, 46.48)96.4<0.10
   Increased11% (5%, 18%)0.00.72
   Decreased4% (0%, 8%)NANA
   Prothrombin time (s)12.25 (11.30, 13.20)99.0<0.10
   Increased2% (0%, 4%)0.00.42
   Decreased2% (0%, 6%)NANA
   D-dimer (mg/L)0.33 (0.17, 0.49)0.00.98
   Increased15% (7%, 22%)38.40.17

ES, effect size; NA, not applicable.

ES, effect size; NA, not applicable.

Discussion

Principal findings

Children had on average milder symptoms, with many children having even no symptoms. Most children infected with COVID-19 were exposed through family clusters. About half of children present with fever or cough, and about one-third of children with both fever and cough. Only a small minority of children had vomiting or diarrhea as initial symptoms. Leucocyte and lymphocyte counts are often in normal or above the normal range in children with COVID-19. Abnormalities in CT imaging were found in more than half of the children, the most common being ground-glass opacity in unilateral lung. The course of COVID-19 in children can be characterized by mild illness and no symptoms. According to a study by the CCDC, as of February 11, 2020, 81% of all patients with COVID-19 showed only mild symptoms (81). However, although the disease was less severe in the majority of adults (51–74%) (82-84), 26–32% of adults were still committed to ICU, and had often basic diseases such as hypertension or diabetes (85-87). In contrast, we found only 3% report of children with severe illness. The CCDC also pointed out that 889 (1%) patients with COVID-19 were asymptomatic (81); in our study, about 19% of children were completely asymptomatic, which is higher than the average level of the whole patient significantly. A study of asymptomatic infections with COVID-19 also showed that 29.2% of cases showed normal CT image and had no symptoms during hospitalization. What’s more, these cases were younger (median age: 14.0 years; P=0.012) than the rest (88). Of children with COVID-19, 83% had other family members infected. The majority of asymptomatic children in family clusters were confirmed after a positive nucleic acid test, which was conducted because of the close contact to infected family members. It seems that family cluster in children were more likely to be tested than adults. So, we suspect whether asymptomatic children are really asymptomatic or are still in the incubation period. Another explanation could be that only symptomatic cases transmit; So, adults without symptoms are seldom diagnosed, while children without symptoms (who had not that many any other contacts during the holiday season than their family members) get diagnosed anyway because of the obvious exposure. The diagnosis of suspected cases in children needs comprehensive consideration. Fever and cough were the main symptoms in patients with COVID-19, which is reported by the most of current guidelines and recommendations (12,89-92). Although fever and cough also the first two symptom of children. When compared with adults, fever and cough occurred only in 48% and 39% of children, respectively. The rates of fever and cough in adults are up to 98% (87) and 87% (83), which indicates that fever and cough in children are not as common as in adults. Compared with children infected with SARS, MERS and other viral diseases (93,94), there are no specific symptoms in children with COVID-19 that could help to diagnose the disease accurately. Therefore, detection methods are particularly important for the diagnosis of COVID-19. Chinese National Health Commission also pointed out that fever and/or respiratory symptoms, imaging features indicating of pneumonia, leukocyte and lymphocyte counts characteristics in the early stage, and epidemiological history should be comprehensively used to determine suspected cases. After that, RT-PCR, sequencing or specific antibody were used to make a definite diagnosis (12). Attention should be paid to the children with COVID-19 who start with gastrointestinal symptoms. Although gastrointestinal symptoms such as nausea, vomiting and diarrhea are less common in children with COVID-19, recent studies have SARS-CoV-2 in the feces of patients (95,96) and a study showed that some children persistently tested positive on rectal swabs even after nasopharyngeal testing was negative, raising the possibility of fecal-oral transmission (63). According to one study, diarrhea was the first symptom in three out of 31 children (87). Moreover, three of the eight children with severe cases of COVID-19 that reported symptom clearly had gastrointestinal symptoms, one of them started with gastrointestinal symptoms, without any obvious respiratory tract infection in the early stage (36). In addition, comorbidity cannot be ignored either. Our results showed that half of these eight children with severe cases had other diseases, including two with intussusception and one of them was dead (46). Similarly, a study of children with MERS also suggest that serious illness can occur in children with underlying disease (94). Although there is no evidence that gastrointestinal symptoms and comorbidity in children are related to the severity of the disease, clinicians should pay attention to the gastrointestinal symptoms and comorbidity in the process of diagnosing children with COVID-19 and apply real-time monitoring and protection. Abnormal CT imaging was less common in children with COVID-19 than adults, but the imaging findings were similar in children and adults. Unilateral pneumonia is common in children with COVID-19, and the main change in imaging is ground-glass opacity. However, bilateral pneumonia is more common in adults, and the main change in imaging is also ground-glass opacity (85,86). One guideline (92) pointed out that there were multiple small patch shadows and interstitial changes in the early stages of the disease in adults, especially in the extrapulmonary zone in chest imaging. Furthermore, multiple ground-glass opacity or infiltrative shadows may develop in both lungs. In severe cases, pulmonary consolidation may occur, and pleural effusion is rare. An analysis of CT features in children with COVID-19 showed that in 15 cases, inflammatory infiltration was found in the chest CT imaging during initial diagnosis and reexamination. Most inflammatory infiltrations were manifested as small nodular ground-glass opacities, and multiple lobe segments were less involved. Multiple lobe segments were involved in only one case, and the imaging changes were not typical in the advanced stage as well (38). These findings suggest that pulmonary inflammation in children is mild and localized. The results of laboratory tests of children with COVID-19 were more often within the normal range than those of adults. The leukocyte count of children with COVID-19 was usually normal or below the normal range. The lymphocyte count was generally normal or above the normal range, and only 15% of cases were below the normal range. While for adults, the leukocyte count was usually normal or above the normal range, and the lymphocyte count were mostly below the normal range (35–63%) (85,86). It can be seen that there were significant differences in routine blood values between adults and children. However, some published COVID-19 guidelines and consensus for children consider a reduction in lymphocyte count as one of the factors for diagnosing suspected cases (89-91). Our study demonstrates that guidelines for children should not be formulated in full accordance with adult standards, otherwise true cases may be missed. Other laboratory tests, including liver and renal function, CRP, procalcitonin (PCT) and coagulation tests, most indicators in children tend to be normal. Although 35% of children with COVID-19 had albumin below the normal range, 38% of cases had lactate dehydrogenase above the normal range, and 22% of cases had CRP above the normal range, which were the most significant changes of children, the rate of changes was still much lower than in adults (86). This result suggests that majority of children with COVID-19 have laboratory results within the normal range, but close clinical monitoring should still be observed. Most of the existing systematic reviews on characteristics of patients with COVID-19 are based on adult patients or patients regardless of age (97-102). Two of these compared the differences between children and adult patients (97,98). Only one review reported the clinical characteristics of children with COVID-19 at present (103). All reviews that considered children had similar outcomes: for example, children had milder symptoms than adults, some children had no symptoms, and lymphopenia in children did not occur as often as in adults. But our rapid review has included 49 studies of children patients, which is more than most of these reviews together. In contrast to another systematic review of children with COVID-19 (103), we included studies not only China but also from other countries such as Singapore, which were published in Chinese and English. Moreover, we conducted a meta-analysis whereas the previous study only did a systematic literature review.

Strengths and limitations

This rapid review has several strengths. First, although this is not the first systemic review about the clinical characteristics of children with COVID-19, but is to our knowledge the first to combine the results with meta-analysis and GRADE evaluation of the quality of main evidence, which is of great importance for clinicians to diagnose and treat children rapidly. Second, our study points out the loopholes in some current guidance documents that suggest the diagnosis of suspected cases—also in children—based on the lymphocyte count. Third, as a rapid review, this study summarizes the latest published information on clinical cases, which provides relatively high-quality evidence for the formulation of clinical practice guidelines in the rapidly evolving public health emergency situation and helps policy-makers to make evidence-based decisions quickly (104). Our study has also some limitations. First, due to the rapid fermentation of the public health emergency and new cases emerging continuously, the findings of this review may get outdates relatively soon. Second, cannot be sure if some cases were included in multiple studies. Third, at present, there is no unified definition for clinical classification of the severity of COVID-19, so we had to combine light, mild and moderate disease into one category (mild), while severe and critical cases were both considered as severe cases.

Future implications

The researchers should aim to conduct more targeted studies on COVID-19 in specific subpopulations. Policy makers should develop accurate guidelines for both children and adults. Clinical practitioners should pay attention on the specific characteristics of different patient populations to improve the accuracy of diagnosis and treatment.

Conclusions

Children with COVID-19 are more common to have only mild symptoms, and many children are even completely asymptomatic. Fever and cough are the main symptoms of COVID-19 in both children. Vomiting and diarrhea occurring less frequently in children. Ground-glass opacity is the most common CT imaging of children. Whereas adults tend to have elevated lymphocyte count at the beginning of the disease, in children the lymphocytes were usually within the normal range. As the characteristics of COVID-19 differ between adults and children in multiple ways, specific criteria for the diagnosis and treatment of COVID-19 in children are urgently needed. The article’s supplementary files as
Table A

National Institute for Health and Care Excellence

Author1. Case series collected in more than one centre, i.e., multi-centre study2. Is the hypothesis/aim/objective of the study clearly described?3. Are the inclusion and exclusion criteria (case definition) clearly reported?4. Is there a clear definition of the outcomes reported?5. Were data collected prospectively?6. Is there an explicit statement that patients were recruited consecutively?7. Are the main findings of the study clearly described?8. Are outcomes stratified? (e.g., by disease stage, abnormal test results, patient characteristics)Total Score
Deng 2020, (32)NoYesYesNoYesNoYesNo4
Cai 2020, (33)NoYesYesNoYesNoYesNo4
Zhang 2020, (34)NoYesYesNoYesNoYesNo4
Wei 2020, (35)YesYesYesYesNoNoYesNo5
Chen 2020, (36)NoYesYesYesYesNoYesNo5
Zeng 2020, (37)NoYesYesYesYesNoYesNo5
Feng 2020, (38)NoYesYesYesNoNoYesYes5
Wang 2020, (39)NoYesYesNoYesNoYesNo4
Quan 2020, (40)NoYesYesNoYesNoYesNo4
Xiong 2020, (41)NoYesYesNoYesNoYesNo4
Cai 2020, (42)YesYesYesNoYesNoYesNo5
Wang 2020, (43)YesYesYesYesNoNoYesNo5
Tang 2020, (44)NoYesYesYesNoNoYesNo4
Liu 2020, (45)YesYesYesYesNoNoYesYes6
Lu 2020, (46)NoYesYesNoYesNoYesYes5
Ma 2020, (47)NoYesNoNoNoNoYesYes3
Zhao 2020, (48)NoYesNoYesNoNoYesYes4
Li 2020, (49)YesYesYesYesNoNoYesNo5
Zhang 2020, (50)NoYesYesYesNoNoYesNo4
Zhang 2020, (51)NoYesNoNoNoNoYesYes3
Liu 2020, (52)NoYesNoNoNoNoYesYes3
Xiao 2020, (53)NoYesYesYesNoNoYesYes5
Xu 2020, (54)YesYesYesYesNoNoYesYes5
Chan 2020, (55)NoYesYesYesNoYesYesYes6
Kam 2020, (56)NoYesNoYesNoNoYesYes4
Park 2020, (57)NoYesNoNoNoNoYesYes3
Du 2020, (58)YesYesYesYesNoYesYesYes7
Liu 2020, (59)YesYesNoYesNoNoYesYes5
Wang 2020, (60)NoYesNoYesNoNoYesYes4
Rahimzadeh 2020, (61)YesYesNoNoNoNoYesYes4
Ji 2020, (62)NoYesNoYesNoNoYesYes4
Xu 2020, (63)NoYesYesNoNoNoYesYes4
Xia 2020, (64)NoYesYesYesNoNoYesNo4
Dong 2020, (65)YesYesYesYesNoNoYesYes6
Xing 2020, (66)NoYesYesYesNoNoYesYes5
Yu 2020, (67)NoYesYesNoNoNoYesYes4
Liu 2020, (68)NoYesYesYesNoNoYesYes5
MA 2020, (69)NoYesYesYesNoNoYesYes5
Qian 2020, (70)NoYesNoNoNoNoYesYes3
Zhang 2020, (72)YesYesYesYesNoNoYesYes6
Sun 2020, (73)NoYesYesYesNoNoYesNo4
Dong 2020, (74)YesYesNoYesNoNoYesYes5
Wu 2020, (75)YesYesYesYesNoNoYesNo5
Su 2020, (76)NoYesYesYesNoNoYesYes5
Le 2020, (77)NoYesNoNoNoNoYesYes3
Zhong 2020, (78)NoYesYesYesNoNoYesYes5
Liu 2020, (79)YesYesYesYesNoNoYesYes6
Tang 2020, (80)NoYesNoNoNoNoYesYes3
Table B

Newcastle-Ottawa Scale

AuthorSELECTIONCOMPARABILITYOUTCOME
1) Representativeness of the Exposed Cohort2) Selection of the Non-Exposed Cohort3) Ascertainment of Exposure4) Demonstration That Outcome of Interest Was Not Present at Start of Study1) Comparability of Cohorts on the Basis of the Design or Analysis1) Assessment of Outcome2) Was Follow-Up Long Enough for Outcomes to Occur3) Adequacy of Follow Up of Cohorts
Qiu 2020, (71)

☆ means one star, which have been explained in the part of the “Risk of bias assessment”.

Table C

Symptoms and imaging findings

No. of studiesCertainty assessmentNo. of patientsEffect value(95% CI)Certainty
Risk of biasInconsistencyIndirectnessImprecisionOther considerationsTotalEvent
The overall symptoms
   No symptom, (17)Serious1Serious2Not seriousNot seriousNone1,39621819% (14%, 23%)⊕⊕○○Low
   Mild symptom, (19)Serious1Serious2Not seriousNot seriousNone1,5401,39694% (90%, 98%)⊕⊕○○Low
   Severe symptom, (19)Serious1Not seriousNot seriousNot seriousNone1,525493% (2%, 4%)⊕⊕⊕○Moderate
   More than one sign or symptom, (15)Serious1Serious2Not seriousNot seriousNone28110435% (21%, 48%)⊕⊕○○Low
Specific symptoms
   Fever, (22)Serious1Serious2Not seriousNot seriousNone89041848% (39%, 56%)⊕⊕○○Low
   Cough, (20)Serious1Serious2Not seriousNot seriousNone76635239% (30%, 48%)⊕⊕○○Low
   Fever and cough, (7)Serious1Serious2Not seriousNot seriousNone2037630% (18%, 42%)⊕⊕○○Low
   Sputum production, (4)Serious1Serious2Not seriousSerious3None2929219% (0%, 44%)⊕○○○Very low
   Rhinorrhoea, (9)Serious1Not seriousNot seriousNot seriousNone380379% (6%, 12%)⊕⊕⊕○Moderate
   Shortness of breath/dyspnoea, (6)Serious1Serious2Not seriousNot seriousNone343649% (0%, 19%)⊕⊕○○Low
   Myalgia or fatigue, (10)Serious1Serious2Not seriousNot seriousNone524498% (5%, 12%)⊕⊕○○Low
   Diarrhoea, (10)Serious1Not seriousNot seriousNot seriousNone528427% (5%, 9%)⊕⊕⊕○Moderate
   Nausea or vomiting, (8)Serious1Not seriousNot seriousNot seriousNone430276% (4%, 9%)⊕⊕⊕○Moderate
   Nasal obstruction, (6)Serious1Not seriousNot seriousNot seriousNone262196% (3%, 9%)⊕⊕⊕○Moderate
   Sore throat, (10)Serious1Not seriousNot seriousNot seriousNone244206% (2%, 10%)⊕⊕⊕○Moderate
   Headache, (7)Serious1Not seriousNot seriousNot seriousNone289144% (1%, 6%)⊕⊕⊕○Moderate
Imaging findings
   Abnormal, (18)Serious1Serious2Not seriousNot seriousNone67444766% (55%, 77%)⊕⊕○○Low
   Unilateral pneumonia, (10)Serious1Serious2Not seriousNot seriousNone34711131% (20%, 43%)⊕⊕○○Low
   Bilateral pneumonia, (13)Serious1Serious2Not seriousNot seriousNone59714628% (20%, 36%)⊕⊕○○Low
   Ground-glass opacity, (14)Serious1Serious2Not seriousNot seriousNone72724635% (26%, 44%)⊕⊕○○Low
Table D

Laboratory results

No. of studiesCertainty assessmentNo. of patientsEffect value(95% CI)Certainty
Risk of biasInconsistencyIndirectnessImprecisionOther considerationsTotal
Blood routine values
   Leucocytes, (×109/L), (11)Serious1Not seriousNot seriousNot seriousNone4656.60 (6.19, 7.01)⊕⊕⊕○○Moderate
   Lymphocytes, (×109/L), (8)Serious1Serious2Not seriousNot seriousNone3562.76 (2.47, 3.05)⊕⊕○○Low
   Neutrophils, (×109/L), (5)Serious1Serious2Not seriousNot seriousNone2362.70 (2.10, 3.31)⊕⊕○○Low
   Platelets, (×109/L), (6)Serious1Serious2Not seriousNot seriousNone133257.09 (251.06, 263.13)⊕⊕○○Low
   Haemoglobin, (g/L), (7)Serious1Serious2Not seriousNot seriousNone304127.61 (123.80, 131.41)⊕⊕○○Low
Blood biochemistry
   Albumin, (g/L), (2)Serious1Not seriousNot seriousNot seriousNone4145.30 (45.13, 45.47)⊕⊕⊕○Moderate
   Alanine aminotransferase, (U/L), (8)Serious1Serious2Not seriousSerious3None30620.46 (14.51, 26.41)⊕○○○Very low
   Aspartate aminotransferase, (U/L), (7)Serious1Serious2Not seriousNot seriousNone28132.04 (30.25, 33.83)⊕⊕○○Low
   Total bilirubin, (μmol/L), (2)Serious1Serious2Not seriousSerious3None418.14 (1.45, 14.82)⊕○○○Very low
   Blood urea nitrogen, (mmol/L), (5)Serious1Not seriousNot seriousNot seriousNone2403.81 (3.43, 4.18)⊕⊕⊕○Moderate
   Creatinine, (μmol/L), (5)Serious1Serious2Not seriousSerious3None24041.60 (32.98, 50.22)⊕○○○Very low
   Creatine kinase, (U/L), (3)Serious1Serious2Not seriousNot seriousNone59104.37 (95.66, 113.08)⊕⊕○○Low
   Lactate dehydrogenase, (U/L), (7)Serious1Serious2Not seriousSerious3None334264.43 (241.85, 287.02)⊕○○○Very low
   Myoglobin, (ug/L), (2)Serious1Not seriousNot seriousNot seriousNone2315.33 (11.18, 19.48)⊕⊕⊕○Moderate
   Procalcitonin, (g/L), (7)Serious1Not seriousNot seriousNot seriousNone3980.06 (0.00, 0.16)⊕⊕⊕○Moderate
   CRP, (mg/L), (8)Serious1Serious2Not seriousNot seriousNone3485.05 (1.86, 8.24)⊕⊕○□Low
Coagulation function
   Activated partial thromboplastin time(s), (2)Serious1Serious2Not seriousSerious3None3837.59 (28.69, 46.48)⊕○○○Very low
   Prothrombin time(s), (4)Serious1Serious2Not seriousNot seriousNone22312.25 (11.30, 13.20)⊕⊕○○Low
   D-dimer, (mg/L), (8)Serious1Not seriousNot seriousNot seriousNone2610.33 (0.17, 0.49)⊕⊕⊕○Moderate
Table E

Symptom

Study IDNumberMild symptomSevere symptomFeverCoughFever and coughSputum productionMyalgia or fatigueSore throatShortness of breath/dyspnoeaDiarrhoeaHeadacheNasal obstructionRhinorrhoeaNausea or vomitingNo symptomMore than one sign or symptom
Deng 2020, (32)22/20/21/20/20/20/20/21/20/20/20/20/20/20/20/20/2
Cai 2020, (33)11/10/11/11/11/10/10/10/10/10/10/10/10/11/10/11/1
Zhang 2020, (34)11/10/11/10/10/10/10/10/10/10/10/10/10/10/10/10/1
Chen 2020, (36)10/11/11/10/10/10/10/10/10/11/10/10/10/11/10/11/1
Zeng 2020, (37)11/10/10/10/10/10/10/10/10/10/10/10/10/10/10/11/1
Wang 2020, (39)11/10/11/11/10/10/10/10/10/10/10/10/10/11/10/11/1
Quan 2020, (40)11/10/10/10/10/10/10/10/10/10/10/10/10/10/11/10/1
Xiong 2020, (41)22/20/22/22/22/20/20/20/20/21/20/20/21/20/20/22/2
Liu 2020, (45)65/61/66/66/66/60/60/60/61/60/60/60/61/64/60/66/6
Zhao 2020, (48)11/10/11/10/10/10/10/10/10/10/10/10/10/10/10/10/1
Zhang 2020, (51)22/20/22/22/22/20/20/20/20/21/20/20/20/20/20/22/2
Liu 2020, (52)11/10/11/10/10/10/10/10/10/11/10/10/10/11/10/11/1
Xiao 2020, (53)11/10/11/11/11/10/10/10/10/10/10/10/11/10/10/11/1
Chan 2020, (55)11/10/10/10/10/10/10/10/10/10/10/10/10/10/11/10/1
Kam 2020, (56)11/10/11/10/10/10/10/10/10/10/10/10/10/10/10/10/1
Park 2020, (57)11/10/11/10/10/11/10/10/10/10/10/10/10/10/10/11/1
Liu 2020, (59)44/40/43/43/42/40/41/40/40/40/40/40/40/40/40/42/4
Wang 2020, (60)11/10/10/10/10/10/10/10/10/10/10/10/10/10/11/10/1
Ji 2020, (62)22/20/21/20/20/20/20/20/20/21/20/20/20/20/20/20/2
Xing 2020, (66)33/30/33/30/30/30/30/30/30/30/30/30/30/30/30/30/3
Qian, (70)11/10/10/10/10/10/10/10/10/10/10/10/10/10/11/10/1
Sun, (73)80/88/86/86/84/84/81/80/88/83/81/80/80/84/80/88/8
Dong, (74)22/20/21/21/21/21/20/20/20/20/20/20/20/20/20/21/2
Le, (77)11/10/10/10/10/10/10/10/10/10/10/11/11/10/10/11/1
Tang, (80)11/10/10/10/10/10/10/10/10/10/10/10/10/10/11/10/1
Table F

Imaging findings and family contact

Study IDNumberAbnormalUnilateral pneumoniaBilateral pneumoniaGround-glass opacityFamily contact
Deng 2020, (32)20/20/20/20/22/2
Cai 2020, (33)11/1NR/1NR/1NR/11/1
Zhang 2020, (34)11/1NR/1NR/1NR/1NR/1
Chen 2020, (36)11/11/10/11/10/1
Zeng 2020, (37)11/10/11/10/11/1
Wang 2020, (39)11/11/10/11/11/1
Quan 2020, (40)11/11/10/10/11/1
Xiong 2020, (41)22/22/20/21/22/2
Liu 2020, (45)64/50/54/51/50/6
Zhao 2020, (48)11/11/10/10/11/1
Zhang 2020, (51)21/20/21/2NR/22/2
Liu 2020, (52)11/10/11/11/11/1
Xiao 2020, (53)11/10/11/10/11/1
Chan 2020, (55)11/1NR/1NR/11/11/1
Kam 2020, (56)1NR/1NR/1NR/1NR/11/1
Park 2020, (57)11/11/10/11/11/1
Liu 2020, (59)43/4NR/4NR/41/4NR/4
Wang 2020, (60)11/1NR/1NR/1NR/11/1
Ji 2020, (62)20/20/20/20/22/2
Xing 2020, (66)32/32/30/32/33/3
Qian, (70)1NR/1NR/1NR/1NR/11/1
Sun, (73)88/82/86/86/85/8
Dong, (74)21/20/21/2NR/2NR/2
Le, (77)10/10/10/10/11/1
Tang, (80)10/10/10/10/10/1

NR, not report.

Table G

Laboratory results

Study IDNumberLeucocytes (×109/L)Lymphocytes (×109/L)Neutrophils (×109/L)Platelets (×109/L)Haemoglobin (×109/L)Albumin (g/L)Alanine aminotransferase (U/L)Aspartate aminotransferase (U/L)Total bilirubin (μmol/L)Blood urea nitrogen (mmol/L)Creatinine (μmol/L)Creatine kinase (U/L)Lactate dehydrogenase (U/L)Myoglobin (ug/L)Procalcitonin (ng/mL)CRP (mg/L)Activated partial thromboplastin time (s)Prothrombin time (s)D-dimer (mg/L)
Deng 2020, (32)24.83/5.083.37/2.89NR225/287NRNR10.63/12.2523.32/20.87NRNR27.33/35.2975.33/83.78NRNR0.19/<0.0512/<10Normal/NRNormal/NR0.41/NR
Cai 2020, (33)116.0NRNR138NRNR1733NRNR29NRNRNR0.0715NormalNormal0.58
Zhang 2020, (34)19.68NRNR494113NRNRNRNRNRNRNRNRNR0.0735.66NRNRNR
Chen 2020, (36)17.52NRNR183108NormalNormalNormalNormal15.9224NRNRNRNRNRNR14.3Normal
Zeng 2020, (37)17.66NRNR399132NormalNormalNormalNormalNormalNormalNRNRNR0.08<0.75NRNRNR
Wang 2020, (39)116.091.3813.97278NRNormal2031NormalNormalNormalNRNRNRNRNRNormalNormalNormal
Quan 2020, (40)19.14.5NR234138NormalNormalNormalNormalNormalNormalNormalNormalNormalNR<0.499NRNRNR
Xiong 2020, (41)26.0/6.22.56/3.732.18/1.72301/252112/11743.2/Normal58.5/Normal83.5/NormalNR/NormalNormalNormalNR/NormalNRNRNR/0.050.36/7.81NormalNormalNormal
Liu 2020, (45)62.96/6.49/5.48/3.04/3.95/1.81/1.19/1.25/1.7/0.87/0.361.3/3.15/2.54/0.66/2.85/0.27203/272/256/191/153/165104/120/113/118/115/12040/45.2/43.6/45.4/44.3/42.36/14/11/23/43/1545/30/42/64/36/37NR/4/4.2/2.7/3.6/5.4NR33/34/22/29/23/3029/50/77/148/71/82384/197/476/375/297/280NRNR38.4/21/23.32/11.8/58.79/6.84NA/32.2/43.7/41/34/41.5NR/13.2/12.8/11.9/12.3/12.50.59/0.22/0.78/0.22/0.74/0.38
Zhao 2020, (48)13.9NRNRNRNRNormalNormalNormalNormal496NormalNormalNormalNormal0.06NormalNRNRNR
Zhang 2020, (51)25.94/8.98NRNR255/324111/112NR/NR12.48/13.1145.48/63.94NR5.16/5.3021.6/17.9030.48/102.53318.37/540.33NR0.85/0.230.05/0.04NormalNormalNormal
Liu 2020, (52)13.781.861.68149138NRNRNRNRNRNRNRNRNRNRNRNRNRNR
Xiao 2020, (53)1NormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormalNormal
Chan 2020, (55)16.52.83.219714649.123.928.23.65.65178194NRNR0.234.013.1NR
Kam 2020, (56)1NormalNormalNormalNormalNormalNRNRNRNRNRNRNRNRNRNRNRNRNRNR
Park 2020, (57)14.08NRNR251135NRNRNRNRNRNRNRNRNRNR< 0.04NRNRNR
Liu 2020, (59)4Decreased/Normal/Normal/NormalIncreased/Increased/Normal/NormalNRNRNRNRNRNRNRNRNRNRNRNRNRNormal/Normal/Normal/IncreasedNRNRNR
Wang 2020, (60)1NR2.43NRNRNRNRNR14333NRNR479NRNRNRNRNRNRNR
Ji 2020, (62)211.82/6.6NRNRNRNRNRNRNRNRNRNRNRNRNRNR34.64/3.49NRNRNR
Xing 2020, (66)37.3/9.6/6.05.4 /5.2 /4.91.2 /3.6/1.7333.0 /411.0/186.0332.0/359.0/332.0NRNRNRNRNR22.8/28.3/53.473.2/88.6/91.0264.3/NR/194.0NR0.23/0.21/0.73<0.8/<5.0/10.5NRNR860.0/230.0/190.0
Qian, (70)1NRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNR
Sun, (73)81.65/14.95/9.19/8.32/8.8/10.6/3.85/7.60.69/1.96/2.7/6.41/3.6/4.04/1.7/2.80.78/11.63/5.7/1.27/3.5/5.9/1.9/3.8140/68/145/666/247/515/154/25083/90/103/111/123/150/159/136NR58/66/36/100/55/9/16/837/27/33/41/16/14/14/1611.8/20.4/16.5/12.4/5.3/7.8/8.1/8.1NR27.1/43.4/21.3/15/24.8/64.5/58/72.115/20,702/33/148/262/106/72/77394/888/282/891/471/370/209/187NR0.18/17.16/0.05/0.08/0.11/0.04/0.09/0.056.48/57.9/103/0.75/27.02/1/9.9/0.5NRNR0.47/40.34/3.07/NR/NR/NR/0.23/0.44
Dong, (74)2NR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normalNR/normal
Le, (77)110.238.31.19230112NR34.859.9NRNR36.5NR327NR0.080.32NRNRNR
Tang, (80)1NRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNRNR

NR, not report; NA, not applicable.

  74 in total

1.  [First case of 2019 novel coronavirus infection in children in Shanghai].

Authors:  J H Cai; X S Wang; Y L Ge; A M Xia; H L Chang; H Tian; Y X Zhu; Q R Wang; J S Zeng
Journal:  Zhonghua Er Ke Za Zhi       Date:  2020-02-02

2.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

Authors:  Chaolin Huang; Yeming Wang; Xingwang Li; Lili Ren; Jianping Zhao; Yi Hu; Li Zhang; Guohui Fan; Jiuyang Xu; Xiaoying Gu; Zhenshun Cheng; Ting Yu; Jiaan Xia; Yuan Wei; Wenjuan Wu; Xuelei Xie; Wen Yin; Hui Li; Min Liu; Yan Xiao; Hong Gao; Li Guo; Jungang Xie; Guangfa Wang; Rongmeng Jiang; Zhancheng Gao; Qi Jin; Jianwei Wang; Bin Cao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

3.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

4.  A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster.

Authors:  Jasper Fuk-Woo Chan; Shuofeng Yuan; Kin-Hang Kok; Kelvin Kai-Wang To; Hin Chu; Jin Yang; Fanfan Xing; Jieling Liu; Cyril Chik-Yan Yip; Rosana Wing-Shan Poon; Hoi-Wah Tsoi; Simon Kam-Fai Lo; Kwok-Hung Chan; Vincent Kwok-Man Poon; Wan-Mui Chan; Jonathan Daniel Ip; Jian-Piao Cai; Vincent Chi-Chung Cheng; Honglin Chen; Christopher Kim-Ming Hui; Kwok-Yung Yuen
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

5.  A Well Infant With Coronavirus Disease 2019 With High Viral Load.

Authors:  Kai-Qian Kam; Chee Fu Yung; Lin Cui; Raymond Tzer Pin Lin; Tze Minn Mak; Matthias Maiwald; Jiahui Li; Chia Yin Chong; Karen Nadua; Natalie Woon Hui Tan; Koh Cheng Thoon
Journal:  Clin Infect Dis       Date:  2020-07-28       Impact factor: 9.079

6.  Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis.

Authors:  Alfonso J Rodriguez-Morales; Jaime A Cardona-Ospina; Estefanía Gutiérrez-Ocampo; Rhuvi Villamizar-Peña; Yeimer Holguin-Rivera; Juan Pablo Escalera-Antezana; Lucia Elena Alvarado-Arnez; D Katterine Bonilla-Aldana; Carlos Franco-Paredes; Andrés F Henao-Martinez; Alberto Paniz-Mondolfi; Guillermo J Lagos-Grisales; Eduardo Ramírez-Vallejo; Jose A Suárez; Lysien I Zambrano; Wilmer E Villamil-Gómez; Graciela J Balbin-Ramon; Ali A Rabaan; Harapan Harapan; Kuldeep Dhama; Hiroshi Nishiura; Hiromitsu Kataoka; Tauseef Ahmad; Ranjit Sah
Journal:  Travel Med Infect Dis       Date:  2020-03-13       Impact factor: 6.211

7.  Clinical characteristics of hospitalized patients with SARS-CoV-2 infection: A single arm meta-analysis.

Authors:  Pengfei Sun; Shuyan Qie; Zongjian Liu; Jizhen Ren; Kun Li; Jianing Xi
Journal:  J Med Virol       Date:  2020-03-11       Impact factor: 20.693

8.  A Familial Cluster of Infection Associated With the 2019 Novel Coronavirus Indicating Possible Person-to-Person Transmission During the Incubation Period.

Authors:  Ping Yu; Jiang Zhu; Zhengdong Zhang; Yingjun Han
Journal:  J Infect Dis       Date:  2020-05-11       Impact factor: 5.226

9.  Clinical features of pediatric patients with COVID-19: a report of two family cluster cases.

Authors:  Li-Na Ji; Shuang Chao; Yue-Jiao Wang; Xue-Jun Li; Xiang-Dong Mu; Ming-Gui Lin; Rong-Meng Jiang
Journal:  World J Pediatr       Date:  2020-03-16       Impact factor: 9.186

10.  Clinical Characteristics of Children with Coronavirus Disease 2019 in Hubei, China.

Authors:  Fang Zheng; Chun Liao; Qi-Hong Fan; Hong-Bo Chen; Xue-Gong Zhao; Zhong-Guo Xie; Xi-Lin Li; Chun-Xi Chen; Xiao-Xia Lu; Zhi-Sheng Liu; Wei Lu; Chun-Bao Chen; Rong Jiao; Ai-Ming Zhang; Jin-Tang Wang; Xi-Wei Ding; Yao-Guang Zeng; Li-Ping Cheng; Qing-Feng Huang; Jiang Wu; Xi-Chang Luo; Zhu-Jun Wang; Yan-Yan Zhong; Yan Bai; Xiao-Yan Wu; Run-Ming Jin
Journal:  Curr Med Sci       Date:  2020-03-24
View more
  22 in total

1.  Multisystem Inflammatory Syndrome in Children (MIS-C) With Hematological Manifestations: A Case Report.

Authors:  Yazeid Alrefaey; Ahmad Alamoudi; Reshale Johar; Rawia F Albar
Journal:  Cureus       Date:  2022-04-11

2.  COVID-19 and Speech-Language Pathology Clinical Practice of Voice and Upper Airway Disorders.

Authors:  Emerald J Doll; Maia N Braden; Susan L Thibeault
Journal:  Am J Speech Lang Pathol       Date:  2020-12-17       Impact factor: 2.408

3.  Correlations of Clinical and Laboratory Characteristics of COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Ramy Abou Ghayda; Jinhee Lee; Jun Young Lee; Da Kyung Kim; Keum Hwa Lee; Sung Hwi Hong; Young Joo Han; Jae Seok Kim; Jae Won Yang; Andreas Kronbichler; Lee Smith; Ai Koyanagi; Louis Jacob; Jae Il Shin
Journal:  Int J Environ Res Public Health       Date:  2020-07-13       Impact factor: 3.390

4.  Systematic review of reviews of symptoms and signs of COVID-19 in children and adolescents.

Authors:  Russell M Viner; Joseph Lloyd Ward; Lee D Hudson; Melissa Ashe; Sanjay Valabh Patel; Dougal Hargreaves; Elizabeth Whittaker
Journal:  Arch Dis Child       Date:  2020-12-17       Impact factor: 3.791

5.  Sudden anosmia and ageusia in a child: A COVID-19 case report.

Authors:  Ellen Wang; Seckin O Ulualp; Christopher Liu; Maria Veling
Journal:  Otolaryngol Case Rep       Date:  2021-01-23

6.  Multisystem inflammatory syndrome in children during the coronavirus disease 2019 (COVID-19) pandemic: a systematic review of published case studies.

Authors:  Yuyi Tang; Weiguo Li; Muna Baskota; Qi Zhou; Zhou Fu; Zhengxiu Luo; Yuan Shi; Yaolong Chen; Enmei Liu
Journal:  Transl Pediatr       Date:  2021-01

7.  Is liver involvement overestimated in COVID-19 patients? A meta-analysis.

Authors:  Gang Li; Yitian Yang; Danyang Gao; Yongxing Xu; Jianwen Gu; Pengfei Liu
Journal:  Int J Med Sci       Date:  2021-01-18       Impact factor: 3.738

8.  Risk profiles of severe illness in children with COVID-19: a meta-analysis of individual patients.

Authors:  Bo Zhou; Yuan Yuan; Shunan Wang; Zhixin Zhang; Min Yang; Xiangling Deng; Wenquan Niu
Journal:  Pediatr Res       Date:  2021-03-22       Impact factor: 3.756

9.  The perfect storm: A case of COVID-19 infection in an adolescent patient with EVALI.

Authors:  Kubra Melike Bozkanat; Devika R Rao; Tiffany J Lieu; Yadira M Rivera-Sanchez
Journal:  Respir Med Case Rep       Date:  2020-11-25

Review 10.  Rapid advice guidelines for management of children with COVID-19.

Authors:  Enmei Liu; Rosalind L Smyth; Zhengxiu Luo; Amir Qaseem; Joseph L Mathew; Quan Lu; Zhou Fu; Xiaodong Zhao; Shunying Zhao; Janne Estill; Edwin Shih-Yen Chan; Lei Liu; Yuan Qian; Hongmei Xu; Qi Wang; Toshio Fukuoka; Xiaoping Luo; Gary Wing-Kin Wong; Junqiang Lei; Detty Nurdiati; Wenwei Tu; Xiaobo Zhang; Xianlan Zheng; Hyeong Sik Ahn; Mengshu Wang; Xiaoyan Dong; Liqun Wu; Myeong Soo Lee; Guobao Li; Shu Yang; Xixi Feng; Ruiqiu Zhao; Xiaoxia Lu; Zhihui He; Shihui Liu; Weiguo Li; Qi Zhou; Luo Ren; Yaolong Chen; Qiu Li
Journal:  Ann Transl Med       Date:  2020-05
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.