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基于医疗行政数据的算法识别因主要出血而到急诊科就诊的住院患者的敏感性和特异性。

Sensitivity and specificity of an algorithm based on medico-administrative data to identify hospitalized patients with major bleeding presenting to an emergency department.

机构信息

Univ Rennes, EA 7449 REPERES [Pharmacoepidemiology and Health Services Research], Rennes, France.

Department of Medical Information, CHU Rennes, Rennes, France.

出版信息

BMC Med Res Methodol. 2019 Oct 18;19(1):194. doi: 10.1186/s12874-019-0841-6.


DOI:10.1186/s12874-019-0841-6
PMID:31627721
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6798331/
Abstract

BACKGROUND: Validation studies on an ICD-10-based algorithm to identify major bleeding events are scarce, and mostly focused on positive predictive values. OBJECTIVE: To evaluate the sensitivity and specificity of an ICD-10-based algorithm in adult patients referred to hospital. METHODS: This was a cross-sectional, retrospective analysis. Among all hospital stays of adult patients referred to Rennes University Hospital, France, through the emergency ward in 2014, we identified major bleeding events according to an index test based on a list of ICD-10 diagnoses. As a reference, a two-step process was applied: firstly, a computerized request for electronic health records from the emergency ward, using several hemorrhage-related diagnostic codes and specific emergency therapies so as to discard stays with a very low probability of bleeding; secondly, a chart review of selected records was conducted by a medical expert blinded to the index test results and each hospital stay was classified into one of two exclusive categories: major bleeding or no major bleeding, according to pre-specified criteria. RESULTS: Out of 16,012 hospital stays, the reference identified 736 major bleeding events and left 15,276 stays considered as without the target condition. The index test identified 637 bleeding events: 293 intracranial hemorrhages, 197 gastrointestinal hemorrhages and 147 other bleeding events. Overall, sensitivity was 65% (95%CI, 62 to 69), and specificity was 99.0%. We observed differential sensitivity and specificity across bleeding types, with the highest values for intracranial hemorrhage. Positive predictive values ranged from 59% for "other" bleeding events, to 71% (95%CI, 65 to 78) for gastrointestinal hemorrhage, and 96% for intracranial hemorrhage. CONCLUSIONS: Low sensitivity and differential measures of accuracy across bleeding types support the need for specific data collection and medical validation rather than using an ICD-10-based algorithm for assessing the incidence of major bleeding.

摘要

背景:基于 ICD-10 的算法来识别大出血事件的验证研究很少,且大多集中在阳性预测值上。

目的:评估一种基于 ICD-10 的算法在转诊至医院的成年患者中的敏感性和特异性。

方法:这是一项横断面、回顾性分析。在法国雷恩大学医院通过急诊病房于 2014 年转诊的所有成年患者的住院期间中,我们根据基于 ICD-10 诊断列表的指数测试来确定大出血事件。作为参考,我们采用了两步法:首先,通过与出血相关的诊断代码和特定的急诊治疗,从急诊病房计算机请求电子病历,以排除出血可能性非常低的住院患者;其次,由一位对指数测试结果和每个住院情况均不知情的医学专家对选定病历进行图表审查,并根据预设标准将每个住院情况分为两个排他性类别之一:大出血或无大出血。

结果:在 16012 次住院中,参考标准确定了 736 例大出血事件,留下了 15276 例被认为没有目标疾病的住院情况。指数测试确定了 637 例出血事件:293 例颅内出血、197 例胃肠道出血和 147 例其他出血。总体而言,敏感性为 65%(95%CI,62 至 69),特异性为 99.0%。我们观察到不同出血类型的敏感性和特异性存在差异,颅内出血的数值最高。阳性预测值范围从“其他”出血事件的 59%到胃肠道出血的 71%(95%CI,65 至 78),再到颅内出血的 96%。

结论:敏感性低和不同出血类型的准确性衡量指标支持需要进行特定的数据收集和医学验证,而不是使用基于 ICD-10 的算法来评估大出血的发生率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd5e/6798331/52724e55a0ef/12874_2019_841_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd5e/6798331/52724e55a0ef/12874_2019_841_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dd5e/6798331/52724e55a0ef/12874_2019_841_Fig1_HTML.jpg

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本文引用的文献

[1]
Ascertainment and validation of major bleeding events in a primary care database.

Pharmacoepidemiol Drug Saf. 2018-6-27

[2]
Assessment of the coding accuracy of warfarin-related bleeding events.

Thromb Res. 2017-10-12

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Thromb Res. 2015-12

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Pharmacoepidemiol Drug Saf. 2014-3

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J Epidemiol Community Health. 2013-11-18

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