Prediction of Mortality Risk After Ischemic Acute Kidney Injury With a Novel Prognostic Model: A Multivariable Prediction Model Development and Validation Study.
Prediction of Mortality Risk After Ischemic Acute Kidney Injury With a Novel Prognostic Model: A Multivariable Prediction Model Development and Validation Study.
复制标题
使用新型预后模型预测缺血性急性肾损伤后的死亡风险：多变量预测模型开发和验证研究
DOI：
10.3389/fmed.2022.892473
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发表时间：
2022
影响因子：
3.9
通讯作者：
Duan, Shao-Bin
中科院分区：
文献类型：
--
作者：
Wang, Mei;Yan, Ping;Zhang, Ning-Ya;Deng, Ying-Hao;Luo, Xiao-Qin;Wang, Xiu-Fen;Duan, Shao-Bin
急性肾损伤（AKI）是一种常见的临床综合征，在住院患者中具有较高的发病率和死亡率。然而，目前还没有预测缺血性AKI死亡风险的临床工具。在本研究中，我们旨在建立并验证预测缺血性AKI住院患者30天和1年死亡风险的模型。从2015年1月至2015年12月在中南大学三所附属三级综合医院住院的277898例患者中，共招募了1836例缺血性AKI患者。最终分析的患者随访1年。研究患者按7:3的比例随机分组，组成训练组和验证组。采用多变量回归分析建立死亡率预测模型。肝肾综合征、休克、中枢神经系统衰竭、Charlson合并症指数（≥2分）、机械通气、出院时肾功能是缺血性AKI后30天死亡率的独立危险因素，而恶性肿瘤、败血症、心力衰竭、肝功能衰竭、Charlson合并症指数（≥2分）、机械通气、出院时肾功能是1年死亡率的预测因素。30天预测模型的受试者工作特征曲线下面积（auroc）在训练组为0.878(95%可信区间（CI）： 0.849 ~ 0.908)，在验证组为0.867 （95% CI: 0.820 ~ 0.913）。训练组和验证组1年死亡率预测的auroc分别为0.803 （95% CI: 0.772-0.834）和0.788 （95% CI: 0.741-0.835）。我们的预测模型易于应用，可以有效识别缺血性AKI住院患者30天或1年内死亡风险高的个体。它可以指导最佳的临床管理，以减少缺血性AKI发作后的死亡率。
Acute kidney injury (AKI) that results from ischemia is a common clinical syndrome and correlates with high morbidity and mortality among hospitalized patients. However, a clinical tool to predict mortality risk of ischemic AKI is not available. In this study, we aimed to develop and validate models to predict the 30-day and 1-year mortality risk of hospitalized patients with ischemic AKI. A total of 1,836 admissions with ischemic AKI were recruited from 277,898 inpatients admitted to three affiliated tertiary general hospitals of Central South University in China between January 2015 and December 2015. Patients in the final analysis were followed up for 1 year. Study patients were randomly divided in a 7:3 ratio to form the training cohort and validation cohort. Multivariable regression analyses were used for developing mortality prediction models. Hepatorenal syndrome, shock, central nervous system failure, Charlson comorbidity index (≥2 points), mechanical ventilation, renal function at discharge were independent risk factors for 30-day mortality after ischemic AKI, while malignancy, sepsis, heart failure, liver failure, Charlson comorbidity index (≥2 points), mechanical ventilation, and renal function at discharge were predictors for 1-year mortality. The area under the receiver operating characteristic curves (AUROCs) of 30-day prediction model were 0.878 (95% confidence interval (CI): 0.849-0.908) in the training cohort and 0.867 (95% CI: 0.820–0.913) in the validation cohort. The AUROCs of the 1-year mortality prediction in the training and validation cohort were 0.803 (95% CI: 0.772–0.834) and 0.788 (95% CI: 0.741–0.835), respectively. Our easily applied prediction models can effectively identify individuals at high mortality risk within 30 days or 1 year in hospitalized patients with ischemic AKI. It can guide the optimal clinical management to minimize mortality after an episode of ischemic AKI.
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影响因子：
39.3
作者：
Ronco C;McCullough P;Anker SD;Anand I;Aspromonte N;Bagshaw SM;Bellomo R;Berl T;Bobek I;Cruz DN;Daliento L;Davenport A;Haapio M;Hillege H;House AA;Katz N;Maisel A;Mankad S;Zanco P;Mebazaa A;Palazzuoli A;Ronco F;Shaw A;Sheinfeld G;Soni S;Vescovo G;Zamperetti N;Ponikowski P;Acute Dialysis Quality Initiative (ADQI) consensus group
通讯作者：
Acute Dialysis Quality Initiative (ADQI) consensus group
影响因子：
--
作者：
Brown JR;Rezaee ME;Marshall EJ;Matheny ME
通讯作者：
Matheny ME
影响因子：
9.8
作者：
Larsson, J. Skytte;Bragadottir, G.;Ricksten, S. -E.
通讯作者：
Ricksten, S. -E.
影响因子：
19.6
作者：
Chertow, G. M.;Soroko, S. H.;Mehta, R. L.
通讯作者：
Mehta, R. L.
影响因子：
120.7
作者：
Annane, Djillali;Siami, Shidasp;Chevret, Sylvie
通讯作者：
Chevret, Sylvie