Wang Lei, Zhao Yun-Tao
Department of Cardiology, Aerospace Center Hospital, Beijing, China.
Front Cardiovasc Med. 2021 Nov 15;8:719307. doi: 10.3389/fcvm.2021.719307. eCollection 2021.
Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence. Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve. Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729-0.803) and good identical calibration. In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.
急性肾损伤是急性失代偿性心力衰竭（ADHF）患者中具有显著发病率的不良事件。我们计划开发一种简约模型，该模型简单易用，可在临床实践中预测急性肾损伤（AKI）发生的风险。本研究纳入了650例ADHF患者。从病历中收集每位患者的数据。我们采用三种不同的变量选择方法来推导四个多变量逻辑回归模型。我们选择了六个候选预测因子，这些因子在不同模型中导致相对稳定的结果，以推导最终预测模型。通过使用C统计量和校准曲线对预测模型进行验证。42.8%的患者发生了急性肾损伤。高龄、糖尿病、既往肾功能不全、高基线肌酐、高B型利钠肽和低白蛋白血症是AKI的最强预测因子。预测模型显示出中等的辨别力C统计量：0.766（95%CI，0.729 - 0.803）和良好的一致性校准。在本研究中，我们开发了一种预测模型和列线图，以估计ADHF患者中AKI的风险。它可能有助于临床医生检测AKI并及时进行处理。
