CAJ | 학술논문

目的了解综合医院门诊呼吸道症候群信息的来源与构成,描述不同呼吸道症候群的分布特征与相互关系;探讨呼吸道症候群数据应用于呼吸道疾病暴发、流行预警监测的可行性.方法回顾性调查广州市某综合医院的信息系统(HIS)资料,对门诊病例信息进行症候群分类;比较不同呼吸道症候群数据的时间分布,选择与流感样病例(ILI)有相似趋势的数据,通过交叉相关分析探讨其应用于呼吸道疾病预警监测的意义.结果门诊主要呼吸道症候群包括上呼吸道感染(51.20%)、气管/支气管感染(18.80%)、哮喘(17.52%)等,肺部感染仅占2.26%.上呼吸道感染、气管/支气管炎、肺部感染、咳嗽、哮喘等症候群以及门诊X线检查例数、肺炎/急性呼吸窘迫综合征(ARDS)表现病例数的时间分布趋势类似,均存在两个季节高峰.对1～28周数据进行时间交叉相关分析,显示肺部感染与前移4周的ILI相关性最佳(r=0.739,P＜0.01),上呼吸道感染与前移5周的ILI相关性最佳(r=0.714,P＜0.01);X线检查例数及肺炎/ARDS表现病例数均与前移1周的ILI相关性最佳(r=0.858,P＜0.001;r=0.821,P＜0.001).结论 HIS中的门诊病例信息可应用于流感等呼吸道传染病的症候群预警监测.门诊肺部感染数据具有良好的特异性与及时性,可作为首选预警症候群资料;上呼吸道感染、咳嗽数据的意义次之;X线检查及肺炎/ARDS表现病例数据的监测及时性稍差,但特异性较好,可辅助预警监测.
목적 료해종합의원문진호흡도증후군신식적래원여구성,묘술불동호흡도증후군적분포특정여상호관계;탐토호흡도증후군수거응용우호흡도질병폭발、류행예경감측적가행성.방법 회고성조사엄주시모종합의원적신식계통(HIS)자료,대문진병례신식진행증후군분류;비교불동호흡도증후군수거적시간분포,선택여류감양병례(ILI)유상사추세적수거,통과교차상관분석탐토기응용우호흡도질병예경감측적의의.결과 문진주요호흡도증후군포괄상호흡도감염(51.20%)、기관/지기관감염(18.80%)、효천(17.52%)등,폐부감염부점2.26%.상호흡도감염、기관/지기관염、폐부감염、해수、효천등증후군이급문진X선검사례수、폐염/급성호흡군박종합정(ARDS)표현병례수적시간분포추세유사,균존재량개계절고봉.대1～28주수거진행시간교차상관분석,현시폐부감염여전이4주적ILI상관성최가(r=0.739,P＜0.01),상호흡도감염여전이5주적ILI상관성최가(r=0.714,P＜0.01);X선검사례수급폐염/ARDS표현병례수균여전이1주적ILI상관성최가(r=0.858,P＜0.001;r=0.821,P＜0.001).결론 HIS중적문진병례신식가응용우류감등호흡도전염병적증후군예경감측.문진폐부감염수거구유량호적특이성여급시성,가작위수선예경증후군자료;상호흡도감염、해수수거적의의차지;X선검사급폐염/ARDS표현병례수거적감측급시성초차,단특이성교호,가보조예경감측.
Objective To find out the data sources of respiratory syndromes and their components from the outpatients of general hospitals and to describe the time distribution and mutual relations of different respiratory syndromes. Feasibility of respiratory syndromes used for early warning surveillance on respiratory infectious disease was also under research. Methods Retrospective investigation on Hospital Information System (HIS) was implemented in a general hospital in Guangzhou, 2005, and data of outpatients was collected and classified into different syndromes. The respiratory syndromes with its time distribution similar to influenza like illness (ILI),were selected, and cross-correlation analyses were conducted to inveshgate the feasibility of respiratory syndromes for early warning surveillance on respiratory infection diseases (influenza as an example). Results Primary sub-classification of respiratory syndromes in outpatient department would include upper respiratory infection(URI)(51.20%), trachitis/bronchitis (18.80%), asthma ( 17.52% ), etc. Pulmonary infection accounted for only 2.26%. Time distributions of URI, trachitis/bronchitis, pulmonary infection, cough and asthma in outpatient department, X-ray tests and pneumonia/acute respiratory distress syndromes (ARDSs) in outpatient X-ray room were similar, with two peaks observed. Cross-correlation functions were calculated with the data sets of 1st-28th week.The most significant correlation was detected between the time series of outpatient pulmonary infections and ILIs moved 4 weeks backward (r＝0.739, P＜0.01 ), and that was detected between URIs and ILIs moved 5 weeks backward (r=0.714, P＜0.01 ). Correlation between X-ray tests,pneumonia/ARDSs in outpatient X-ray room and ILIs was the strongest when ILIs time series moved 1 week backward (r=0.858, P＜0.001; r=0.821, P＜0.001 ). Conclusion Outpatient data from HIS system in general hospital could be applied to syndromic surveillance on respiratory diseases. For early warning epidemics or outbreaks of influenza or other respiratory infectious diseases, data of outpatient pulmonary infection appeared to be the most feasible for its specificity and timeliness, followed by URI and cough. X-ray tests and pneumonia/ARDSs in outpatient X-ray findings were important supplementary to verify the respiratory disease epidemics or outbreaks for its good specificity, but with no advantage for early warning.