Hepatitis E is a globally distributed infection that varies in seroprevalence between developed and developing regions.In the less developed regions of Asia and Africa,a high seropositivity rate has been reported for hepatitis E virus(HEV)antibodies.Although acute hepatitis E is often self-limited and has a favorable prognosis,some populations experience severe manifestations,which may progress to liver failure.Moreover,some immunocompromised patients are at risk of developing chronic HEV infection and cirrhosis.Proactive screening,reducing misdiagnosis,improving patient management,timely anti-viral therapy for severe and chronic cases,and vaccination of high-risk groups are important measures to reduce the morbidity of hepatitis E.This review focused on the clinical presentation,management,and prevention of hepatitis E.

Objective To explore the early predictors of macrolide-unresponsive Mycoplasma pneumoniae pneumonia(MUMPP)and construct a nomogram prediction model.Methods The clinical data of 159 chil-dren with Mycoplasma pneumoniae pneumonia(MPP)admitted to the hospital from January 2023 to Februar-y 2024 were retrospectively collected.According to the time of admission,they were divided into modeling group(112 cases)and validation group(47 cases).The modeling group was further divided into MUMPP group(51 cases)and MPP group(61 cases)according to the drug response.The clinical data and laboratory indexes of each group were compared.The independent predictors of MUMPP were analyzed by univariate and multivariate analysis,and a nomogram prediction model was constructed.Receiver operating characteristic(ROC)curve,area under the curve(AUC),decision curve,calibration curve and Hosmer-Lemeshow goodness of fit test were used to evaluate the discrimination,clinical practicability and calibration of the model.Results The systemic immune inflammation index(SII),C-reactive protein(CRP)/albumin(ALB)and D-dimer were independent influencing factors of MUMPP(P＜0.05).The AUC was 0.938(95％CI 0.890-0.986)in the modeling group and 0.912(95％CI 0.832-0.992)in the validation group.x2 was 3.768 and P was 0.877 in Hosmer-Lemeshow goodness-of-fit test,threshold probability between 5％and 99％had high net clinical benefit.Conclusion The nomogram prediction model established by SII,CRP/ALB and D-dimer has good prediction accuracy and high clinical application value for children with MUMPP.

OBJECTIVES: To discuss the demands and countermeasures for outpatients and emergency patients during the outbreak of coronavirus disease 2019 (COVID-19) in large general hospital. METHODS: By analyzing patients' demands, outpatient service system and emergency system complemented each other with the help of "internet medical" to provide online medical treatment, self-diagnosed pneumonia program, online pharmacies, outpatient appointment and online pre-examination services, open green channels for special patients, and to provide referral services for critical patients. The COVID-19 suspected patients and other common fever patients were separated from other patients. RESULTS: From January 28 to March 1, we have received 26 000 patients online, 1 856 special patients, 2 929 suspected patients and common fever patients including 31 confirmed patients, 0 case of misdiagnosis and cross-infection. CONCLUSIONS Targeting patient's demands and taking appropriate measures are effective on meeting the needs of outpatients' and emergency patients' medical services.
Betacoronavirus ; Coronavirus Infections ; epidemiology ; prevention & control ; Cross Infection ; prevention & control ; Emergency Medical Services ; organization & administration ; Health Services Needs and Demand ; Hospitals, General ; organization & administration ; Humans ; Outpatients ; Pandemics ; prevention & control ; Pneumonia, Viral ; epidemiology ; prevention & control