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通过自动登记系统的链接识别用于流行病学研究的重症肌无力患者。

Identifying patients with myasthenia for epidemiological research by linkage of automated registers.

机构信息

Department of Neurology, Odense University Hospital, Odense, Denmark.

出版信息

Neuroepidemiology. 2011;37(2):120-8. doi: 10.1159/000331481. Epub 2011 Oct 7.

Abstract

BACKGROUND

We validated a new method of identifying patients with incident myasthenia in automated Danish registers for the purpose of conducting epidemiological studies of the disorder.

METHODS

For residents of a Danish county (population 484,862) in 1993-2008, we identified any hospital contacts coded for myasthenia in a nationwide patient register and any prescriptions for pyridostigmine in the county prescription register. Results from an acetylcholine receptor antibody register were linked to the data. We verified the diagnosis by a review of medical records.

RESULTS

Subjects identified in the Patient Register (n = 83) were comparable with individuals found in the Prescription Register (n = 89) with regard to age and gender, but were more often seropositive (83.1 vs. 74.2%). Seropositivity increased to 91.6% by restricting the data to individuals recorded in both Patient and Prescription Registers (n = 71). We found that for subjects identified in both Patient and Prescription Registers the positive predictive value of the register diagnosis was 92.9% (95% confidence interval, CI, 84.3-97.7), the false-positive rate was low (2.8%), and the sensitivity was acceptable (81.2%; 95% CI 71.2-88.8).

CONCLUSIONS

Our data indicate that this novel approach of combining diagnosis register and prescription register information provides a feasible and valid method to trace incident myasthenia patients for population-based epidemiological studies.

摘要

背景

为了开展对该疾病的流行病学研究,我们验证了一种在丹麦自动化登记处识别新发重症肌无力患者的新方法。

方法

对于 1993-2008 年期间丹麦一个县(484862 居民)的居民,我们在全国患者登记处识别出任何编码为重症肌无力的医院接触记录,并在县处方登记处识别出任何吡斯的明处方。乙酰胆碱受体抗体登记处的结果与数据相关联。我们通过审查病历来验证诊断。

结果

在患者登记处(n=83)中识别出的受试者在年龄和性别方面与在处方登记处(n=89)中发现的个体相当,但阳性率更高(83.1%比 74.2%)。通过将数据限制在同时记录在患者和处方登记处的个体(n=71)中,阳性率增加到 91.6%。我们发现,对于同时在患者和处方登记处中识别出的个体,登记诊断的阳性预测值为 92.9%(95%置信区间,CI,84.3-97.7),假阳性率低(2.8%),灵敏度可接受(81.2%;95%CI,71.2-88.8)。

结论

我们的数据表明,这种结合诊断登记和处方登记信息的新方法为基于人群的流行病学研究追踪新发重症肌无力患者提供了一种可行且有效的方法。

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