Division of Clinical Pharmacology, Amiens University Hospital, Avenue René Laennec, 80000, Amiens, France.
MP3CV Laboratory, EA7517, Jules Verne University of Picardie, Amiens, France.
J Nephrol. 2022 Apr;35(3):955-968. doi: 10.1007/s40620-021-01174-z. Epub 2021 Oct 7.
Acute kidney injury (AKI) has serious short- and long-term consequences. The objective of the present study of a cohort of hospitalized patients with AKI was to (i) evaluate the proportion of patients with hospital-acquired (HA) AKI and community-acquired (CA) AKI, the characteristics of these patients and the AKIs, and the short-term outcomes, and (ii) determine the performance of several ICD-10 codes for identifying AKI (both CA and HA) and drug-induced AKI.
A cohort of hospitalized patients with AKI was constituted by screening hospital's electronic medical records (EMRs) for cases of AKI. We distinguished between and compared CA-AKI and HA-AKI and evaluated the proportion of AKIs that were drug-induced. The EMR data were merged with hospital billing codes (according to the International Classification of Diseases, 10th Edition (ICD-10)) for each hospital stay. The ability of ICD-10 codes to identify AKIs (depending on the type of injury) was determined by calculating the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Lastly, we sought to validate specific ICD-10 codes for drug-induced AKI.
Of the 2473 patients included, 1557 experienced an AKI (HA-AKI: 59.3%; CA-AKI: 40.7%). Patients with CA-AKI had a better short-term outcome and a lower death rate (7.6%, vs. 20% for HA-AKI). One AKI in three was drug-induced. The combination of AKI codes had a very high specificity (94.8%), a high PPV (94.9%), a moderate NPV (56.7%) and moderate sensitivity (57.4%). The sensitivity was higher for CA-AKI (72.2%, vs. 47.2% for HA-AKI), for more severe AKI (82.8% for grade 3 AKI vs. 43.7% for grade 1 AKI), and for patients with CKD. Use of a specific ICD-10 code for drug-induced AKI (N14x) alone gave a very low sensitivity (1.8%), whereas combining codes for adverse drug reactions with AKI-specific codes increased the sensitivity.
Our results show that the combination of an EMR-based analysis with ICD-10-based hospital billing codes gives a comprehensive "real-life" picture of AKI in hospital settings. We expect that this approach will enable researchers to study AKI in more depth.
急性肾损伤（AKI）具有严重的短期和长期后果。本研究对一组住院 AKI 患者进行了研究，目的是：（i）评估医院获得性（HA）AKI 和社区获得性（CA）AKI 患者的比例、这些患者和 AKI 的特征以及短期结局，以及（ii）确定几种用于识别 AKI（CA 和 HA）和药物诱导性 AKI 的 ICD-10 代码的性能。
通过筛选医院电子病历（EMR）中 AKI 的病例，构建了一组住院 AKI 患者队列。我们区分并比较了 CA-AKI 和 HA-AKI，并评估了药物诱导性 AKI 的比例。将 EMR 数据与每个住院患者的医院计费代码（根据国际疾病分类，第 10 版（ICD-10））合并。通过计算敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）来确定 ICD-10 代码识别 AKI（取决于损伤类型）的能力。最后，我们试图验证药物诱导性 AKI 的特定 ICD-10 代码。
在纳入的 2473 名患者中，有 1557 名患者发生 AKI（HA-AKI：59.3%；CA-AKI：40.7%）。CA-AKI 患者的短期结局更好，死亡率更低（7.6%，HA-AKI 为 20%）。三分之一的 AKI 是药物诱导的。AKI 组合具有非常高的特异性（94.8%）、高 PPV（94.9%）、中等 NPV（56.7%）和中等敏感性（57.4%）。CA-AKI 的敏感性更高（72.2%，HA-AKI 为 47.2%）、更严重的 AKI（3 级 AKI 的敏感性为 82.8%，1 级 AKI 的敏感性为 43.7%）和慢性肾脏病患者。单独使用药物诱导性 AKI 的特定 ICD-10 代码（N14x）的敏感性非常低（1.8%），而将药物不良反应代码与 AKI 特异性代码结合使用可提高敏感性。
我们的结果表明，基于 EMR 的分析与基于 ICD-10 的医院计费代码相结合，可以全面了解医院环境中 AKI 的“真实情况”。我们希望这种方法将使研究人员能够更深入地研究 AKI。
