摘要
目的探讨远程心电系统在基层医院的临床应用价值及发展前景。方法从总院、分院、社区医院及乡镇卫生院通过远程心电网络系统记录并上传的386500份心电图中,随机抽取1000份作为研究对象,根据其资料来源、心电图特征和不同年龄段进行分组分析。结果1000份网络心电图中533份来自总院,467份来自分院、社区医院和乡镇卫生院等基层医院;共发现快速性心律失常191份(19.1%),缓慢性心律失常103份(10.3%),ST段改变334份(33.4%),起搏心电图52份(5.2%)。异常心电图发生率总院高于基层医院(P<0.01),且不同年龄组异常心电图发生率差异均有统计学意义(P均<0.05)。结论远程心电网络诊断便捷,能明显节约就诊时间,为急危重症患者的及时诊断和救治赢得时间,值得临床推广。
Objective To discuss the application value and developing prospect of remote ECG system in primary hospitals.Methods We randomly selected 1000 cases as research objects from 386500 ECGs recorded and uploaded via remote ECG network system from the general hospital,branch hospitals,community hospitals,and township health clinics.They were divided into different groups according to data source,ECG characteristics and age before making comparative analysis.Results Among the 1000 ECGs,533 cases are from the general hospital while 467 come from primary hospitals such as branch hospitals,community hospitals and township health clinics.A total of 191(19.1%)cases of tachyarrhythmia,103(10.3%)cases of bradyarrhythmia,334(33.4%)cases of ST changes and 52(5.2%)cases of pacing ECGs are found.The incidence of ECG abnormalities in the general hospital is higher than that in primary hospitals(P<0.01);the incidence of ECG abnormalities varies significantly among different age groups(P<0.05).Conclusion Remote ECG network is convenient for diagnosis,which can significantly save the medical time,and win time for diagnosing and treating critical and severe patients.It is worthy of being promoted in clinical practice.
作者
冯湘红
方胜
李娜
江辉
杨冬冬
张媛
余媛
FENG Xianghong;FANG Sheng;LI Na;JIANG Hui;YANG Dongdong;ZHANG Yuan;YU Yuan(Department of Cardiac Func-tion,General Hospital of Huainan Oriental Hospital Group,Huainan Anhui 232001;Department of Electrocar-diogram,Fenghuang Hospital of Huainan Oriental Hospital Group,Huainan Anhui 232000,China)
出处
《实用心电学杂志》
2022年第2期103-107,共5页
Journal of Practical Electrocardiology
关键词
心电图
心电信息化
远程心电系统
心电网络
心律失常
electrocardiogram
ECG informationization
remote ECG system
ECG network
arrhythmia