{"title":"Leveraging electronic health records for detection of acute kidney injury in critical care units.","authors":"Mays Mohammad Arar, Amani A Khalil","doi":"10.1097/NSG.0000000000000166","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>To assess the incidence of acute kidney injury (AKI) and identify associated risk factors using Kidney Disease Improving Global Outcomes (KDIGO) criteria through the analysis of electronic health record (EHR) data in ICUs.</p><p><strong>Methods: </strong>A retrospective observational study was conducted using EHR data from 563 adult ICU patients admitted to a large public hospital in Jordan between January and December 2019, analyzing demographic, clinical, and medication variables through univariate and multivariate logistic regression.</p><p><strong>Results: </strong>The incidence of AKI was 24.5%, with significant risk factors including advanced age, respiratory disorders, post-CPR status, electrolyte imbalances, and use of specific medications such as inotropes, vasopressors, mannitol, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and glycopeptide antibiotics.</p><p><strong>Conclusion: </strong>This study, leveraging EHR data, identified key predictors of AKI in critically ill patients, highlighting the potential of using high-content analytic techniques on comprehensive datasets to improve early detection and prevention strategies in ICU settings.</p>","PeriodicalId":35641,"journal":{"name":"Nursing","volume":"55 5","pages":"49-56"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nursing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/NSG.0000000000000166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/21 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Nursing","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: To assess the incidence of acute kidney injury (AKI) and identify associated risk factors using Kidney Disease Improving Global Outcomes (KDIGO) criteria through the analysis of electronic health record (EHR) data in ICUs.
Methods: A retrospective observational study was conducted using EHR data from 563 adult ICU patients admitted to a large public hospital in Jordan between January and December 2019, analyzing demographic, clinical, and medication variables through univariate and multivariate logistic regression.
Results: The incidence of AKI was 24.5%, with significant risk factors including advanced age, respiratory disorders, post-CPR status, electrolyte imbalances, and use of specific medications such as inotropes, vasopressors, mannitol, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and glycopeptide antibiotics.
Conclusion: This study, leveraging EHR data, identified key predictors of AKI in critically ill patients, highlighting the potential of using high-content analytic techniques on comprehensive datasets to improve early detection and prevention strategies in ICU settings.
期刊介绍:
Nursing2020 (ISSN 0360-4039; online ISSN 1538-8689) published its first issue in November 1971, under founders Gene W. Jackson and Daniel Cheney. In the intervening years, its circulation has grown to over 150,000, making it one of the largest nursing journals in the world. Published monthly, Nursing2020 is widely regarded as offering current, practical contents to its readers, and has won many editorial awards testifying to the quality of its copy and graphics. The editorial and clinical staff, a 19-member Editorial Board of distinguished clinicians and practitioners, and over 100 invited reviewers help ensure the quality of this publication.