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首页> 外文期刊>Journal of biomedical informatics. >The epidemiology of liver disease in Tayside database: a population-based record-linkage study.
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The epidemiology of liver disease in Tayside database: a population-based record-linkage study.

机译:Tayside数据库中肝脏疾病的流行病学:一项基于人群的记录链接研究。

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BACKGROUND: The true incidence and prevalence of liver disease is difficult to ascertain because there are few, if any, population-based registers of liver disease available to ensure proper case and comparator selection. The epidemiology of liver disease in Tayside (ELDIT) is a specially built register of liver disease for a well-defined geographical area of Scotland. AIMS: This paper describes the electronic linkage of multiple data sources to form ELDIT and provides initial results from the database. PATIENTS: All subjects resident in Tayside and registered with a general practitioner in the study period 1980-1999, approximately 400,000 people. METHODS: Electronic record-linkage techniques were employed to include anonymised data from primary and secondary sources. Hospital admissions, dispensed medication, and laboratory results from immunology, virology, and biochemistry were used to identify cases of liver disease. Diagnostic algorithms were used to verify and classify subjects with liver disease. A validation of the algorithms against the clinical diagnosis was used to determine the measure of agreement (true positive rate) of ELDIT. RESULTS: At present approximately 10,000 subjects have been identified with liver disease or abnormal liver function. The data set is nearing completion with cases of rarer liver disease being identified last. Incidence densities for the population were calculated. From the validation study, agreement between electronic and clinical diagnosis was 0.98 and positive predictive value was 0.83 showing electronic diagnostic algorithms are sensitive enough to identify liver disease using para-clinical data. CONCLUSIONS: ELDIT demonstrates how clinical information can be harnessed electronically to provide a better understanding of liver disease in a population.
机译:背景:肝脏疾病的真正发病率和患病率很难确定,因为很少有(如果有的话)基于人群的肝脏疾病登记资料可用于确保正确选择病例和比较者。 Tayside(ELDIT)的肝病流行病学是专门为苏格兰明确定义的地理区域建立的肝病登记册。目的:本文描述了多个数据源形成ELDIT的电子链接,并提供了数据库的初步结果。患者:1980年至1999年研究期间,居住在Tayside并在全科医生中注册的所有受试者,约有40万人。方法:电子记录链接技术被用来包括来自主要和次要来源的匿名数据。医院入院,分配的药物以及免疫学,病毒学和生物化学的实验室检查结果被用于识别肝病病例。使用诊断算法对肝病患者进行验证和分类。针对临床诊断的算法验证用于确定ELDIT一致性(真实阳性率)的量度。结果:目前已鉴定出约10,000名患有肝病或肝功能异常的受试者。数据集已接近完成,最后发现了罕见的肝病病例。计算了人口的发病率密度。根据验证性研究,电子诊断与临床诊断之间的一致性为0.98,阳性预测值为0.83,表明电子诊断算法足够灵敏,可以使用副临床数据来识别肝病。结论:ELDIT演示了如何以电子方式利用临床信息,以更好地了解人群中的肝病。

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