Predictive Models for Acute Kidney Injury Following Cardiac Surgery
Predictive Models for Acute Kidney Injury Following Cardiac Surgery
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DOI：
10.1053/j.ajkd.2011.10.046
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发表时间：
2012-03-01
影响因子：
13.2
通讯作者：
Bashour, Charles A.
中科院分区：
文献类型：
--
作者：
Demirjian, Sevag;Schold, Jesse D.;Bashour, Charles A.
背景：准确预测心脏手术相关急性肾损伤（AKI）有助于提高临床决策水平，促进及时诊断和治疗。该研究的目的是利用术前和术前及术中联合变量建立心脏手术相关AKI的预测模型。研究设计：前瞻性观察队列。背景和参与者：2000-2008年在克利夫兰诊所接受心脏手术的25,898例患者。预测因素：术前、术前和术中联合变量用于建立预测模型。结果：透析治疗和复合血清肌酐水平加倍或透析治疗在心脏手术后2周内（或出院如果更早）。结果：透析治疗和血清肌酐水平加倍或透析治疗的复合发生率分别为1.7%和4.3%。在所有4种模型中，肾功能参数都是很强的独立预测因子。在基于术前变量的模型中，由既往心脏手术类型和历史反映的手术复杂性是稳健的预测因子。然而，手术内变量的纳入解释了所有与手术相关信息解释的差异。预测透析治疗的模型具有良好的校准和极好的判别能力；术前和术中联合模型优于术前单独模型（C统计值分别为0.910和0.875）。预测复合终点的模型对术前和联合（术前和术中）变量也有很好的辨别能力（C统计量分别为0.797和0.825）。然而，术前模型预测复合终点显示次优校准（P < 0.001）。局限性：在大规模应用之前，需要在其他队列中对这些预测模型进行外部验证。结论：我们开发并内部验证了4种准确预测心脏手术相关AKI的新模型。这些模型以现成的临床信息为基础，可用于患者咨询、临床管理、风险调整和丰富高风险参与者的临床试验。[J]中华肾脏病杂志，2014,30(3):382-389。(C) 2012年由国家肾脏基金会，Inc。
Background: Accurate prediction of cardiac surgery-associated acute kidney injury (AKI) would improve clinical decision making and facilitate timely diagnosis and treatment. The aim of the study was to develop predictive models for cardiac surgery-associated AKI using presurgical and combined pre- and intrasurgical variables.Study Design: Prospective observational cohort.Settings & Participants: 25,898 patients who underwent cardiac surgery at Cleveland Clinic in 2000-2008.Predictor: Presurgical and combined pre-and intrasurgical variables were used to develop predictive models.Outcomes: Dialysis therapy and a composite of doubling of serum creatinine level or dialysis therapy within 2 weeks (or discharge if sooner) after cardiac surgery.Results: Incidences of dialysis therapy and the composite of doubling of serum creatinine level or dialysis therapy were 1.7% and 4.3%, respectively. Kidney function parameters were strong independent predictors in all 4 models. Surgical complexity reflected by type and history of previous cardiac surgery were robust predictors in models based on presurgical variables. However, the inclusion of intrasurgical variables accounted for all explained variance by procedure-related information. Models predictive of dialysis therapy showed good calibration and superb discrimination; a combined (pre-and intrasurgical) model performed better than the presurgical model alone (C statistics, 0.910 and 0.875, respectively). Models predictive of the composite end point also had excellent discrimination with both presurgical and combined (pre-and intrasurgical) variables (C statistics, 0.797 and 0.825, respectively). However, the presurgical model predictive of the composite end point showed suboptimal calibration (P < 0.001).Limitations: External validation of these predictive models in other cohorts is required before wide-scale application.Conclusions: We developed and internally validated 4 new models that accurately predict cardiac surgery-associated AKI. These models are based on readily available clinical information and can be used for patient counseling, clinical management, risk adjustment, and enrichment of clinical trials with high-risk participants. Am J Kidney Dis. 59(3): 382-389. (C) 2012 by the National Kidney Foundation, Inc.