BACKGROUND Listeria meningitis is an infectious disease of the central nervous system caused by Listeria monocytogenes.This bacterium is widely present in the natural environment and can be transmitted through channel...BACKGROUND Listeria meningitis is an infectious disease of the central nervous system caused by Listeria monocytogenes.This bacterium is widely present in the natural environment and can be transmitted through channels such as food and water.Patients usually show symptoms such as fever,headache,and neck stiffness.In severe cases,coma,convulsions,or even death may occur.Traditional diagnostic methods,such as cerebrospinal fluid(CSF)culture and serological tests,have certain limitations.Although CSF culture is the“gold standard”for diagnosis,it is time-consuming and has a relatively low positivity rate.Serological detection may also result in false positive or false negative results.The emergence of metagenomic sequencing(mNGS)technology has led to a significant break-through in diagnosing Listeria meningitis,allowing quick and accurate detection of various pathogens in samples.CASE SUMMARY Here,we present the case of a previously healthy 64-year-old woman diagnosed with Listeria meningitis using mNGS.She was successfully treated with intravenous ampicillin and meropenem,without any complications.CONCLUSION Listeria meningitis must be considered,especially in patients who fail to show improvement with first-line antibiotic treatments.mNGS significantly reduces the diagnosis time,supporting timely treatment of patients.展开更多
目的探讨累积和控制图模型(cumulative sum control chart,CUSUM)在流行性腮腺炎早期预警中的应用价值,为流行性腮腺炎的应急防制提供科学依据,也为其他传染病突发公共卫生事件的预警研究提供参考和借鉴。方法以江苏省各区县每日发病数...目的探讨累积和控制图模型(cumulative sum control chart,CUSUM)在流行性腮腺炎早期预警中的应用价值,为流行性腮腺炎的应急防制提供科学依据,也为其他传染病突发公共卫生事件的预警研究提供参考和借鉴。方法以江苏省各区县每日发病数为基础,从2012年1月1日起以CUSUM模型进行前瞻性试验,用灵敏度、特异度、及时性等3个指标对预警结果进行评价,并比较CUSUM模型预警与国家传染病自动预警系统(CIDARS)之间的优劣。结果应用CUSUM模型进行预警分析全年共产生1688条预警信号,比自动预警系统产生的信号数少35.30%。CUSUM模型预警灵敏度为100%、特异度为95.84%,均高于自动预警系统(χ2=6.087,P=0.0136;χ2=602.48,P<0.0001);CUSUM模型预警及时性的中位数为3.5天,自动预警系统为6天,两者无统计学差异(Z=0.9173,P=0.3590)。结论江苏省腮腺炎疫情数据CUSUM模型预警分析效果优于自动预警系统,且有进一步提高的空间。展开更多
基金Supported by National Natural Science Foundation of China,No.82100631.
文摘BACKGROUND Listeria meningitis is an infectious disease of the central nervous system caused by Listeria monocytogenes.This bacterium is widely present in the natural environment and can be transmitted through channels such as food and water.Patients usually show symptoms such as fever,headache,and neck stiffness.In severe cases,coma,convulsions,or even death may occur.Traditional diagnostic methods,such as cerebrospinal fluid(CSF)culture and serological tests,have certain limitations.Although CSF culture is the“gold standard”for diagnosis,it is time-consuming and has a relatively low positivity rate.Serological detection may also result in false positive or false negative results.The emergence of metagenomic sequencing(mNGS)technology has led to a significant break-through in diagnosing Listeria meningitis,allowing quick and accurate detection of various pathogens in samples.CASE SUMMARY Here,we present the case of a previously healthy 64-year-old woman diagnosed with Listeria meningitis using mNGS.She was successfully treated with intravenous ampicillin and meropenem,without any complications.CONCLUSION Listeria meningitis must be considered,especially in patients who fail to show improvement with first-line antibiotic treatments.mNGS significantly reduces the diagnosis time,supporting timely treatment of patients.
文摘目的探讨累积和控制图模型(cumulative sum control chart,CUSUM)在流行性腮腺炎早期预警中的应用价值,为流行性腮腺炎的应急防制提供科学依据,也为其他传染病突发公共卫生事件的预警研究提供参考和借鉴。方法以江苏省各区县每日发病数为基础,从2012年1月1日起以CUSUM模型进行前瞻性试验,用灵敏度、特异度、及时性等3个指标对预警结果进行评价,并比较CUSUM模型预警与国家传染病自动预警系统(CIDARS)之间的优劣。结果应用CUSUM模型进行预警分析全年共产生1688条预警信号,比自动预警系统产生的信号数少35.30%。CUSUM模型预警灵敏度为100%、特异度为95.84%,均高于自动预警系统(χ2=6.087,P=0.0136;χ2=602.48,P<0.0001);CUSUM模型预警及时性的中位数为3.5天,自动预警系统为6天,两者无统计学差异(Z=0.9173,P=0.3590)。结论江苏省腮腺炎疫情数据CUSUM模型预警分析效果优于自动预警系统,且有进一步提高的空间。
