Humans ; Diabetes Mellitus, Type 2 ; Counseling ; Health Education

Objective To predict the monthly reported echinococcosis cases in China with the autoregressive integrated mov-ing average(ARIMA)model,so as to provide a reference for prevention and control of echinococcosis. Methods SPSS 24.0 software was used to construct the ARIMA models based on the monthly reported echinococcosis cases of time series from 2007 to 2015 and 2007 to 2014,respectively,and the accuracies of the two ARIMA models were compared. Results The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2015 was ARIMA(1,0,0)(1,1, 0)12,the relative error among reported cases and predicted cases was-13.97%,AR(1)=0.367(t=3.816,P<0.001),SAR (1)=-0.328(t=-3.361,P=0.001),and Ljung-Box Q=14.119(df=16,P=0.590).The model based on the data of the monthly reported cases of echinococcosis in China from 2007 to 2014 was ARIMA(1,0,0)(1,0,1)12,the relative error among reported cases and predicted cases was 0.56%,AR(1)=0.413(t=4.244,P<0.001),SAR(1)=0.809(t=9.584, P<0.001),SMA(1)=0.356(t=2.278,P=0.025),and Ljung-Box Q=18.924(df=15,P=0.217).Conclusions The different time series may have different ARIMA models as for the same infectious diseases.It is needed to be further verified that the more data are accumulated,the shorter time of predication is,and the smaller the average of the relative error is.The estab-lishment and prediction of an ARIMA model is a dynamic process that needs to be adjusted and optimized continuously accord-ing to the accumulated data,meantime,we should give full consideration to the intensity of the work related to infectious diseas-es reported(such as disease census and special investigation).

This study analyzed the quality markers(Q-markers) of Yuquan Capsules(YQC) based on serum pharmacochemistry of Chinese medicine and detected the components and metabolites of YQC absorbed into the blood by UPLC-Q-TOF-MS and UNIFI systems. As a result, 32 components of YQC were detected, including 17 prototype components and 15 metabolized components. Among them, 12 prototype components(ginsenoside Rh_2, genistein, formononetin, puerarin, daidzein, schizandrin A, schizandrin B, schizandrin C, schizandrol A, schizandrol B, gomisin D, and ononin) and 12 metabolized components(ginsenoside Rg_1, ginsenoside Rg_2, ginsenoside Rg_3, ginsenoside Ro, 3'-methoxypuerarin, daidzin, astragaloside Ⅱ, astragaloside Ⅳ, glycyrrhizic acid, liquiritigenin, isoliquiritin, and verbascoside) showed inhibitory effects and pharmacological activities against diabetes, and these 24 blood-entering components against diabetes were identified as Q-markers of YQC.
Capsules ; Chromatography, High Pressure Liquid ; Drugs, Chinese Herbal/pharmacology* ; Ginsenosides/analysis* ; Medicine, Chinese Traditional ; Serum/chemistry*

Diagnosis, Differential ; Humans ; Sarcoma, Myeloid/diagnosis*

Carotid Artery Injuries/etiology* ; Carotid Artery, Internal/diagnostic imaging* ; Foreign Bodies/complications* ; Humans ; Skull ; Skull Base/diagnostic imaging*

OBJECTIVES: To explore the etiology composition and outcomes of pediatric chronic critical illness (PCCI) in the pediatric intensive care unit (PICU). METHODS: The children who were hospitalized in the PICU of Dongguan Children's Hospital Affiliated to Guangdong Medical University and met the diagnostic criteria for PCCI from January 2017 to December 2022 were included in the study. The etiology of the children was classified based on their medical records and discharge diagnoses. Relevant clinical data during hospitalization were collected and analyzed. RESULTS: Among the 3 955 hospitalized children in the PICU from January 2017 to December 2022, 321 cases (8.12%) met the diagnostic criteria for PCCI. Among the 321 cases, the most common etiology was infection (71.3%, 229 cases), followed by unintentional injury (12.8%, 41 cases), postoperation (5.9%, 19 cases), tumors/immune system diseases (5.0%, 16 cases), and genetic and chromosomal diseases (5.0%, 16 cases). Among the 321 cases, 249 cases (77.6%) were discharged after improvement, 37 cases (11.5%) were discharged at the request of the family, and 35 cases (10.9%) died in the hospital. Among the deaths, infection accounted for 74% (26/35), unintentional injury accounted for 17% (6/35), tumors/immune system diseases accounted for 6% (2/35), and genetic and chromosomal diseases accounted for 3% (1/35). From 2017 to 2022, the proportion of PCCI in PICU diseases showed an increasing trend year by year (P<0.05). Among the 321 children with PCCI, there were 148 infants and young children (46.1%), 57 preschool children (17.8%), 54 school-aged children (16.8%), and 62 adolescents (19.3%), with the highest proportion in the infant and young children group (P<0.05). The in-hospital mortality rates of the four age groups were 14.9% (22/148), 8.8% (5/57), 5.6% (3/54), and 8.1% (5/62), respectively. The infant and young children group had the highest mortality rate, but there was no statistically significant difference among the four groups (P>0.05). CONCLUSIONS The proportion of PCCI in PICU diseases is increasing, and the main causes are infection and unintentional injury. The most common cause of death in children with PCCI is infection. The PCCI patient population is mainly infants and young children, and the in-hospital mortality rate of infant and young children with PCCI is relatively high.
Adolescent ; Infant ; Child, Preschool ; Humans ; Child ; Critical Illness ; Prognosis ; Child, Hospitalized ; Chronic Disease ; Intensive Care Units, Pediatric

According to different toxicities of various aqueous extracts of Polygonum multiflorum on hepatocyte, the impacts of chemical composition on the safety of P. multiforum was studied. In this study, 8 main chemical compositions in aqueous extracts of P. multiflorum were determined by the established HPLC method; at the same time, the inhibition ratios of different aqueous extracts of P. multiflorum on L02 cell were determined. Afterwards, the potential compounds related to the toxicity of P. multiforum were tentatively found through a multiple correlation analysis. The results showed that P. multiforum with different chemical compositions exhibited great differences in dissolution. The hepatocyte toxicity of P. multiflorum powder was much greater than P. multiflorum lumps. In addition, three constituents closely related to toxicity of P. multiflorum were found by multiple correlation analysis. The study revealed that chemical composition of P. multiflorum is closely related to the hepatotoxicity, and the hepatotoxicity of P. multiflorum powder is greater than that of other dosage forms. This study indicates that P. multiflorum with different chemical compositions show varying toxicity, which therefore shall be given high attention.