, Available online , doi: 10.3967/bes2020.080
This study aimed to understand the differences in clinical, epidemiological, and laboratory features between the new coronavirus disease 2019 (COVID-2019) and influenza A in children.Data of 23 hospitalized children with COVID-19 (9 boys, 5.7 ± 3.8 years old) were compared with age- and sex-matched 69 hospitalized and 69 outpatient children with influenza A from a hospital in China. The participants’ epidemiological history, family cluster, clinical manifestations, and blood test results were assessed.Compared with either inpatients or outpatients with influenza A, children with COVID-19 showed significantly more frequent family infections and higher ratio of low fever (< 37.3 °C), but shorter cough and fever duration, lower body temperature, and lower rates of cough, fever, high fever (> 39 °C), nasal congestion, rhinorrhea, sore throat, vomiting, myalgia or arthralgia, and febrile seizures. They also showed higher counts of lymphocytes, T lymphocyte CD8, and platelets and levels of cholinesterase, aspartate aminotransferase, lactate dehydrogenase, and lactic acid, but lower serum amyloid, C-reactive protein, and fibrinogen levels and erythrocyte sedimentation rate, and shorter prothrombin time. The level of alanine aminotransferase in children with COVID-19 is lower than that in inpatients but higher than that in outpatients with influenza A.Pediatric COVID-19 is associated with more frequent family infection, milder symptoms, and milder immune responses relative to pediatric influenza A.
, Available online , doi: 10.3967/bes2020.081
Real-time quaking-induced conversion (RT-QuIC) assay is a newly established PrPSc-detecting method. The development of RT-QuIC improves the diagnosis of sporadic Creutzfeldt–Jakob disease (sCJD), showing good sensitivity and specificity in many countries when the method was used in cerebrospinal fluid (CSF) samples. However, in China, the sensitivity and specificity of RT-QuIC has yet to be determined due to the lack of definitive diagnosis samples. Recently, 30 definitive sCJD and 30 non-CJD diagnoses were evaluated by RT-QuIC assay. In the 30 sCJD CSF samples, 29 showed positive results. By contrast, all the non-CJD samples were negative. The sensitivity and specificity of our RT-QuIC assay were 96.67% and 100%, respectively, and are comparable to other published data. Results can provide a fundamental basis for the usage of RT-QuIC assay in CJD surveillance in China.
, Available online , doi: 10.3967/bes2020.075
Objective This study aimed to measure the basal energy expenditure (BEE) of Chinese healthy adults and establish an accurate predictive equation for this population. Methods In total, 470 Chinese healthy adults had their BEE measured using the Cosmed K4b2 portable metabolic system. Multiple linear regression analysis was applied to develop new optimal equations for predicting BEE. The bias, accuracy rate, concordance correlation coefficient (CCC), and root mean square error (RMSE) were used to evaluate the accuracy of the predictive equations. Results There was a significant difference in BEE between males and females, with 5,954 kJ/d and 5,089 kJ/d, respectively. People living in rural areas expended significantly higher BEE (5,885 kJ/d) than those in urban areas (5,279 kJ/d). Previous equations developed by Henry, Schofield, Harris-Benedict (H-B), and Liu overestimated the BEE of Chinese healthy adults. The new equations derived from the present study displayed the smallest average bias and RMSE from the measured basal energy expenditure (mBEE). The CCC of the new equations was higher than other predictive equations, but it was lower than 0.8. There was no significant difference in the accuracy rate among all predictive equations. Conclusions Sex and regional differences in BEE were observed in Chinese healthy adults. Neither the widely used previous predictive equations nor the one derived in the present study were accurate enough for estimating the BEE of Chinese healthy adults. Further study is required to develop more accurate equations for predicting the BEE of Chinese healthy adults aged between 20–45 years.