基于人群的估计参考肌酐值:一个强大的电子急性肾损伤警报系统的新方法。

Nephron Clinical Practice Pub Date : 2014-01-01 Epub Date: 2014-11-19 DOI:10.1159/000368236
Shahed Ahmed, Sarah Curtis, Charlotte Hill, Trevor Hine
{"title":"基于人群的估计参考肌酐值:一个强大的电子急性肾损伤警报系统的新方法。","authors":"Shahed Ahmed,&nbsp;Sarah Curtis,&nbsp;Charlotte Hill,&nbsp;Trevor Hine","doi":"10.1159/000368236","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Acute kidney injury (AKI) is common in hospitalized patients. Despite the progress that has been made in the last decade, early identification of AKI cases remains a challenge. In recent years, electronic AKI alert (e-AKI alert) systems have been tested and are usually based on changes in serum creatinine (Cr) values. However, these methods do not include one of the common scenarios, i.e. when there is no available preadmission Cr value available for a patient to compare and hence an e-AKI alert cannot be issued. Therefore, it is essential to have an alternative algorithm to produce e-AKI alerts in such scenarios.</p><p><strong>Method: </strong>We have developed e-AKI alert algorithms which compare serum Cr values at presentation with previous results, within KDIGO AKI guideline-specified classifications. However, where a comparator is not available, we have produced a 'population-based reference Cr value' age and sex matched from 137,000 serum Cr values extracted from blood tests in general practice from our Telepath system.</p><p><strong>Results: </strong>Cr results were split by gender, and then within each group the Cr were stratified according to year of age. The median Cr for each individual year of age was identified and plotted versus age to give separate graphs for males and females that gave excellent fits (R(2)) to cubic regressions.</p><p><strong>Conclusion: </strong>Population-based estimated reference Cr measurements from community blood test results is a more robust method of baseline Cr value estimation in generating potential e-AKI alerts to help early recognition and treatment of AKI cases leading to improved outcome.</p>","PeriodicalId":19094,"journal":{"name":"Nephron Clinical Practice","volume":"128 1-2","pages":"166-70"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000368236","citationCount":"8","resultStr":"{\"title\":\"Population-based estimated reference creatinine values: a novel method of a robust electronic acute kidney injury alert system.\",\"authors\":\"Shahed Ahmed,&nbsp;Sarah Curtis,&nbsp;Charlotte Hill,&nbsp;Trevor Hine\",\"doi\":\"10.1159/000368236\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Acute kidney injury (AKI) is common in hospitalized patients. Despite the progress that has been made in the last decade, early identification of AKI cases remains a challenge. In recent years, electronic AKI alert (e-AKI alert) systems have been tested and are usually based on changes in serum creatinine (Cr) values. However, these methods do not include one of the common scenarios, i.e. when there is no available preadmission Cr value available for a patient to compare and hence an e-AKI alert cannot be issued. Therefore, it is essential to have an alternative algorithm to produce e-AKI alerts in such scenarios.</p><p><strong>Method: </strong>We have developed e-AKI alert algorithms which compare serum Cr values at presentation with previous results, within KDIGO AKI guideline-specified classifications. However, where a comparator is not available, we have produced a 'population-based reference Cr value' age and sex matched from 137,000 serum Cr values extracted from blood tests in general practice from our Telepath system.</p><p><strong>Results: </strong>Cr results were split by gender, and then within each group the Cr were stratified according to year of age. The median Cr for each individual year of age was identified and plotted versus age to give separate graphs for males and females that gave excellent fits (R(2)) to cubic regressions.</p><p><strong>Conclusion: </strong>Population-based estimated reference Cr measurements from community blood test results is a more robust method of baseline Cr value estimation in generating potential e-AKI alerts to help early recognition and treatment of AKI cases leading to improved outcome.</p>\",\"PeriodicalId\":19094,\"journal\":{\"name\":\"Nephron Clinical Practice\",\"volume\":\"128 1-2\",\"pages\":\"166-70\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1159/000368236\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nephron Clinical Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1159/000368236\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2014/11/19 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nephron Clinical Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1159/000368236","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2014/11/19 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

背景:急性肾损伤(AKI)在住院患者中很常见。尽管在过去十年中取得了进展,但AKI病例的早期识别仍然是一个挑战。近年来,已经测试了电子AKI警报(e-AKI警报)系统,通常基于血清肌酐(Cr)值的变化。然而,这些方法不包括一种常见的情况,即当没有可用的入院前Cr值供患者比较时,因此不能发出e-AKI警报。因此,在这种情况下,必须有一种替代算法来产生e-AKI警报。方法:我们开发了e-AKI警报算法,在KDIGO AKI指南指定的分类中,将呈现时的血清Cr值与先前的结果进行比较。然而,在没有比较器的情况下,我们制作了一个“基于人群的参考铬值”,年龄和性别与我们的心灵感应系统从常规血液检测中提取的137,000个血清铬值相匹配。结果:Cr结果按性别划分,然后在每组内按年龄分层。确定了每个年龄的中位数Cr,并根据年龄绘制了男性和女性的单独图表,这些图表对三次回归具有很好的拟合性(R(2))。结论:基于人群的社区血液检测结果的估计参考铬测量是一种更可靠的基线铬值估计方法,可产生潜在的e-AKI警报,有助于早期识别和治疗AKI病例,从而改善预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Population-based estimated reference creatinine values: a novel method of a robust electronic acute kidney injury alert system.

Background: Acute kidney injury (AKI) is common in hospitalized patients. Despite the progress that has been made in the last decade, early identification of AKI cases remains a challenge. In recent years, electronic AKI alert (e-AKI alert) systems have been tested and are usually based on changes in serum creatinine (Cr) values. However, these methods do not include one of the common scenarios, i.e. when there is no available preadmission Cr value available for a patient to compare and hence an e-AKI alert cannot be issued. Therefore, it is essential to have an alternative algorithm to produce e-AKI alerts in such scenarios.

Method: We have developed e-AKI alert algorithms which compare serum Cr values at presentation with previous results, within KDIGO AKI guideline-specified classifications. However, where a comparator is not available, we have produced a 'population-based reference Cr value' age and sex matched from 137,000 serum Cr values extracted from blood tests in general practice from our Telepath system.

Results: Cr results were split by gender, and then within each group the Cr were stratified according to year of age. The median Cr for each individual year of age was identified and plotted versus age to give separate graphs for males and females that gave excellent fits (R(2)) to cubic regressions.

Conclusion: Population-based estimated reference Cr measurements from community blood test results is a more robust method of baseline Cr value estimation in generating potential e-AKI alerts to help early recognition and treatment of AKI cases leading to improved outcome.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Nephron Clinical Practice
Nephron Clinical Practice 医学-泌尿学与肾脏学
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信