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利用电子健康记录预测异基因造血细胞移植后急性肾损伤的风险。

Leveraging Electronic Health Records to Predict the Risk of Acute Kidney Injury after Allogeneic Hematopoietic Cell Transplantation.

作者信息

Bischoff Elena, Kirilov Nikola

机构信息

Faculty of Global Health and Health Care, University "Prof Dr Assen Zlatarov", 8010 Burgas, Bulgaria.

Institute of Medical Informatics, Heidelberg University Hospital, 69120 Heidelberg, Germany.

出版信息

Life (Basel). 2024 Aug 8;14(8):987. doi: 10.3390/life14080987.

Abstract

BACKGROUND

The objective of this study is to assess the electronic health records (EHRs), which are potential risk factors for acute kidney injury (AKI) after allogenic hematopoietic cell transplantation (allo-HCT), and to propose a basic dataset and score for the calculation of HCT-acute kidney injury risk (HCT-AKIR).

METHODS

We undertook a retrospective analysis of the EHRs of 312 patients. Pre- and post-transplant factors were assessed, recognizing the following structured entries: laboratory data, encounters, medication, imaging studies, diagnoses, and procedures. Composite variables were used to create patient groups by combining two or more multivariate significant risk factors for AKI. The EHRs dataset and HCT-AKIR score were created based on the multivariate analysis of the composite variables.

RESULTS

A multivariate analysis showed that previous CKD and once-impaired pre-transplant kidney function, sepsis, imaging procedures with contrast media, and cumulative length of intensive care unit stay after transplantation were significant risk factors. A new unit-weighted composite score based on the combination of significant risk factors contained in common EHR resources was proposed.

CONCLUSIONS

Using our novel HCT-AKIR score calculated from the basic EHR dataset could be an easy way to increase awareness of post-transplant AKI and provide risk stratification.

摘要

背景

本研究的目的是评估电子健康记录(EHRs),其为异基因造血细胞移植(allo-HCT)后急性肾损伤(AKI)的潜在风险因素,并提出用于计算造血细胞移植相关急性肾损伤风险(HCT-AKIR)的基础数据集和评分。

方法

我们对312例患者的电子健康记录进行了回顾性分析。评估移植前后的因素,识别以下结构化条目:实验室数据、会诊、用药、影像学检查、诊断和操作。通过合并两个或更多AKI的多变量显著风险因素,使用复合变量创建患者组。基于复合变量的多变量分析创建了电子健康记录数据集和HCT-AKIR评分。

结果

多变量分析显示,既往慢性肾脏病和移植前曾出现的肾功能损害、脓毒症、使用造影剂的影像学检查以及移植后重症监护病房的累计住院时间是显著风险因素。提出了一种基于常见电子健康记录资源中包含的显著风险因素组合的新的单位加权复合评分。

结论

使用我们从基础电子健康记录数据集计算出的新型HCT-AKIR评分可能是提高对移植后急性肾损伤的认识并提供风险分层的一种简便方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a1bd/11355793/c61c5f77b003/life-14-00987-g001.jpg

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