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预测非危重症患者严重医院获得性急性肾损伤模型的开发与验证

Development and Validation of a Model to Predict Severe Hospital-Acquired Acute Kidney Injury in Non-Critically Ill Patients.

作者信息

Carpio Jacqueline Del, Marco Maria Paz, Martin Maria Luisa, Ramos Natalia, de la Torre Judith, Prat Joana, Torres Maria J, Montoro Bruno, Ibarz Mercedes, Pico Silvia, Falcon Gloria, Canales Marina, Huertas Elisard, Romero Iñaki, Nieto Nacho, Gavaldà Ricard, Segarra Alfons

机构信息

Department of Nephrology, Arnau de Vilanova University Hospital, 25198 Lleida, Spain.

Department of Medicine, Autonomous University of Barcelona, 08193 Barcelona, Spain.

出版信息

J Clin Med. 2021 Aug 31;10(17):3959. doi: 10.3390/jcm10173959.

Abstract

BACKGROUND

The current models developed to predict hospital-acquired AKI (HA-AKI) in non-critically ill fail to identify the patients at risk of severe HA-AKI stage 3.

OBJECTIVE

To develop and externally validate a model to predict the individual probability of developing HA-AKI stage 3 through the integration of electronic health databases.

METHODS

Study set: 165,893 non-critically ill hospitalized patients. Using stepwise logistic regression analyses, including demography, chronic comorbidities, and exposure to risk factors prior to AKI detection, we developed a multivariate model to predict HA-AKI stage 3. This model was then externally validated in 43,569 non-critical patients admitted to the validation center.

RESULTS

The incidence of HA-AKI stage 3 in the study set was 0.6%. Among chronic comorbidities, the highest odds ratios were conferred by ischemic heart disease, ischemic cerebrovascular disease, chronic congestive heart failure, chronic obstructive pulmonary disease, chronic kidney disease and liver disease. Among acute complications, the highest odd ratios were associated with acute respiratory failure, major surgery and exposure to nephrotoxic drugs. The model showed an AUC of 0.906 (95% CI 0.904 to 0.908), a sensitivity of 89.1 (95% CI 87.0-91.0) and a specificity of 80.5 (95% CI 80.2-80.7) to predict HA-AKI stage 3, but tended to overestimate the risk at low-risk categories with an adequate goodness-of-fit for all risk categories (Chi: 16.4, : 0.034). In the validation set, incidence of HA-AKI stage 3 was 0.62%. The model showed an AUC of 0.861 (95% CI 0.859-0.863), a sensitivity of 83.0 (95% CI 80.5-85.3) and a specificity of 76.5 (95% CI 76.2-76.8) to predict HA-AKI stage 3 with an adequate goodness of fit for all risk categories (Chi: 15.42, : 0.052).

CONCLUSIONS

Our study provides a model that can be used in clinical practice to obtain an accurate dynamic assessment of the individual risk of HA-AKI stage 3 along the hospital stay period in non-critically ill patients.

摘要

背景

目前开发的用于预测非危重症患者医院获得性急性肾损伤(HA-AKI)的模型无法识别出有发生严重HA-AKI 3期风险的患者。

目的

通过整合电子健康数据库,开发并外部验证一个预测发生HA-AKI 3期个体概率的模型。

方法

研究集:165,893例非危重症住院患者。我们采用逐步逻辑回归分析(包括人口统计学、慢性合并症以及在检测到AKI之前暴露于危险因素的情况),开发了一个多变量模型来预测HA-AKI 3期。然后在43,569例入住验证中心的非危重症患者中对该模型进行外部验证。

结果

研究集中HA-AKI 3期的发生率为0.6%。在慢性合并症中,缺血性心脏病、缺血性脑血管病、慢性充血性心力衰竭、慢性阻塞性肺疾病、慢性肾脏病和肝病的比值比最高。在急性并发症中,急性呼吸衰竭、大手术和接触肾毒性药物的比值比最高。该模型预测HA-AKI 3期的曲线下面积(AUC)为0.906(95%可信区间0.904至0.908),敏感性为89.1(95%可信区间87.0 - 91.0),特异性为80.5(95%可信区间80.2 - 80.7),但在低风险类别中倾向于高估风险且对所有风险类别拟合优度良好(卡方值:16.4;P值:0.034)。在验证集中HA-AKI3期的发生率为0.62%。该模型预测HA-AKI 3期的AUC为0.861(95%可信区间0.859 - 0.863),敏感性为83.0(95%可信区间80.5 - 85.3),特异性为76.5(95%可信区间76.2 - 76.8),对所有风险类别拟合优度良好(卡方值:15.42;P值:0.052)。

结论

我们的研究提供了一个可用于临床实践的模型,可以在非危重症患者住院期间准确动态评估其发生HA-AKI 3期的个体风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/33a7/8432169/301fee700af8/jcm-10-03959-g001.jpg

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