Epidemiological features of coronavirus disease 2019 in children: a meta-analysis.

OBJECTIVE: Many studies have been published recently on the characteristics of the clinical manifestations of COVID-19 in children. The quality scores of literature are different, and the incidence of clinical manifestations and laboratory tests results vary greatly. Therefore, a systematic retrospective meta-analysis is needed to determine the incidence of the clinical manifestations of COVID-19 in children. MATERIALS AND METHODS: Data from databases, such as PubMed, Web of science, EMBASE, Johns Hopkins University, and Chinese databases were analysed from January 31, 2020 to October 20, 2020. High-quality articles were selected for analysis based on a quality standard score. A meta-analysis of random effects was used to determine the prevalence of comorbidities and subgroup meta-analysis to examine the changes in the estimated prevalence in different subgroups. RESULTS: Seventy-one articles involving 11,671 children were included in the study. The incidence of fever, respiratory symptoms, gastrointestinal symptoms, asymptomatic patients, nervous system symptoms, and chest tightness was 55.8%, 56.8%, 14.4%, 21.1%, 6.7%, and 6.1%, respectively. The incidence of multisystem inflammatory syndrome was 6.2%. Laboratory examination results showed that lymphocytes decreased in 12% and leukocytes decreased in 8.8% of patients, whereas white blood cells increased in 7.8% of patients. Imaging showed abnormalities in 66.5%, and ground-glass opacities were observed in 36.9% patients. Epidemiological history was present in 85.2% cases; severe disease rate was 3.33%. The mortality rate was 0.28%. CONCLUSIONS: The clinical symptoms of COVID-19 in children are mild, and laboratory indicators and imaging manifestations are atypical. While screening children for COVID-19, in addition to assessing patients for symptoms as the first step of screening, the epidemiological history of patients should be obtained.

[The appropriate cut-off point of time in range (TIR) for evaluating glucose control in type 2 diabetes mellitus].

Objective: To investigate the appropriate cut-off point of time in range (TIR) for evaluating glucose control in type 2 diabetes mellitus (T2DM) patients, and analyze the prevalence of abnormal carotid intima-media thickness (CIMT) and diabetic retinopathy (DR) in different TIR categories. Methods: A total of 2 161 subjects with T2DM (1 183 males) were enrolled from hospitalized patients at the Department of Endocrinology and Metabolism of the Sixth People's Hospital Affiliated to Shanghai Jiao Tong University from January 2005 to February 2012. The age of the enrolled participants was (60.4±11.9) years. Each patient underwent continuous glucose monitoring (CGM) for three consecutive days, then TIR (3.9-10.0 mmol/L), time above range (TAR) and time below range (TBR) were calculated. Fundus photography and carotid artery Doppler ultrasound were performed to diagnose DR and abnormal CIMT (defined as CIMT≥1.0 mm), respectively. Multivariate logistic regression models were used to examine the independent association of different TIR groups with CIMT and DR. Results: All subjects were divided into 4 groups according to TIR:≤40%, 41%-70%, 71%-85% and>85%. Significant linear trends in age, diabetes duration, body mass index (BMI), total cholesterol, glycated hemoglobin A1c (HbA1c), TAR and mean glucose (MG) existed among the 4 groups (all P(trend)<0.05). However, there was only a weak correlation between TIR and TBR (<3.9 mmol/L) (r=0.087, P<0.001), and no significant association was observed between TBR (<3 mmol/L) and the TIR categories (P(trend)=0.378). The overall prevalence of abnormal CIMT and DR was 12.1% and 23.8%, respectively. The prevalence of abnormal CIMT in the 4 groups with ascending levels of TIR was 16.9% (59/349), 12.9% (96/746), 11.2% (57/510) and 9.0% (50/556) (P(trend)<0.001), respectively. And the prevalence of DR was 30.7% (107/349), 29.4% (219/746), 20.8% (106/510) and 14.9% (83/556), respectively (P(trend)<0.001). In the binary logistic regression model by adjusting confounding factors, compared with TIR≤ 40%, the risk of abnormal CIMT was reduced by 33.8% (OR=0.662, 95%CI: 0.456-0.963, P=0.031), 40.8% (OR=0.592, 95%CI: 0.390-0.899, P=0.014), and 45.0% (OR=0.550, 95%CI: 0.358-0.846, P=0.006) in the other three groups, respectively. And the risk of DR was reduced by 2.9% (OR=0.971, 95%CI: 0.725-1.301, P=0.844), 33.4%(OR=0.666, 95%CI: 0.479-0.924, P=0.015) and 53.3% (OR=0.467, 95%CI: 0.331-0.657, P<0.001), respectively. Conclusion: Using 40%, 70% and 85% as cut-off point of TIR helps stratify the risk of diabetic complications, and assess the glucose control (Poor: TIR≤40%; Unsatisfactory: TIR≤70%; Satisfactory: TIR>70%; Optimal: TIR>85%) in patients with T2DM.