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采用行政或索赔数据捕获心肌炎的验证方法的系统评价。

A systematic review of validated methods to capture myopericarditis using administrative or claims data.

机构信息

Vanderbilt Institute for Global Health, Vanderbilt University Medical Center, Suite 700, Suite 600, 2525 West End Avenue, Nashville, TN 37203-1738, USA.

Department of Epidemiology, University of Iowa College of Public Health, S437 CPHB University of Iowa, 105 River Street, Iowa City, IA 52242, USA.

出版信息

Vaccine. 2013 Dec 30;31 Suppl 10:K34-40. doi: 10.1016/j.vaccine.2013.08.074.

Abstract

PURPOSE

To identify algorithms that can capture incident cases of myocarditis and pericarditis in administrative and claims databases; these algorithms can eventually be used to identify cardiac inflammatory adverse events following vaccine administration.

METHODS

We searched MEDLINE from 1991 to September 2012 using controlled vocabulary and key terms related to myocarditis. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics as well as study conduct.

RESULTS

Nine publications (including one study reported in two publications) met criteria for inclusion. Two studies performed medical record review in order to confirm that these coding algorithms actually captured patients with the disease of interest. One of these studies identified five potential cases, none of which were confirmed as acute myocarditis upon review. The other study, which employed a search algorithm based on diagnostic surveillance (using ICD-9 codes 420.90, 420.99, 422.90, 422.91 and 429.0) and sentinel reporting, identified 59 clinically confirmed cases of myopericarditis among 492,671 United States military service personnel who received smallpox vaccine between 2002 and 2003. Neither study provided algorithm validation statistics (positive predictive value, sensitivity, or specificity).

CONCLUSIONS

A validated search algorithm is currently unavailable for identifying incident cases of pericarditis or myocarditis. Several authors have published unvalidated ICD-9-based search algorithms that appear to capture myocarditis events occurring in the context of other underlying cardiac or autoimmune conditions.

摘要

目的

确定可在行政和理赔数据库中捕获心肌炎和心包炎事件病例的算法;这些算法最终可用于识别疫苗接种后的心脏炎症不良事件。

方法

我们使用与心肌炎相关的受控词汇和关键词,从 1991 年到 2012 年 9 月在 MEDLINE 上进行了检索。我们还检索了纳入研究的参考文献列表。两名调查员独立根据预先确定的纳入标准评估研究的全文。两名评审员独立提取有关参与者和算法特征以及研究实施的信息。

结果

有 9 篇出版物(包括 2 篇出版物中的 1 项研究)符合纳入标准。有两项研究进行了病历回顾,以确认这些编码算法实际上捕获了感兴趣疾病的患者。其中一项研究确定了 5 个潜在病例,但在审查后没有一个被确认为急性心肌炎。另一项研究采用了基于诊断监测的搜索算法(使用 ICD-9 代码 420.90、420.99、422.90、422.91 和 429.0)和哨点报告,在 2002 年至 2003 年间接受天花疫苗的 492671 名美国军人中发现了 59 例临床确诊的心包心肌炎病例。这两项研究均未提供算法验证统计数据(阳性预测值、敏感性或特异性)。

结论

目前尚无用于识别心包炎或心肌炎事件病例的经过验证的搜索算法。有几位作者发表了未经验证的基于 ICD-9 的搜索算法,这些算法似乎可捕获在其他潜在心脏或自身免疫条件下发生的心肌炎事件。

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