Development and Validation of a Risk Score for Prediction of Acute Kidney Injury in Patients With Acute Decompensated Heart Failure: A Prospective Cohort Study in China

Abstract

Background: Although several risk factors for acute kidney injury (AKI) have been identified, early detection of AKI in acute decompensated heart failure patients remains a challenge. The aim of this study was to develop and validate a risk score for early prediction of AKI in acute decompensated heart failure patients.

Methods and results: A total of 676 consecutive acute decompensated heart failure participants were prospectively enrolled from 6 regional central hospitals. Data from 507 participants were analyzed. Participants from 4 of the 6 hospitals (n=321) were used to develop a risk score and conduct internal validation. External validation of the developed risk score was conducted in participants from the other 2 hospitals (n=186). Sequential logistic regression was used to develop and validate the risk score. The c statistic and calibration plot were used to assess the discrimination and calibration of the proposed risk score. The overall occurrence of AKI was 33.1% (168/507). The risk score, ranging from 0 to 55, demonstrated good discriminative power with an optimism-corrected c statistic of 0.859. Similar results were obtained from external validation with c statistic of 0.847 (95% CI 0.819-0.927). The risk score had good calibration with no apparent over- or under-prediction observed from calibration plots.

Conclusions: The novel risk score is a simple and accurate tool that can help clinicians assess the risk of AKI in acute decompensated heart failure patients, which in turn helps them plan and initiate the most appropriate disease management for patients in time.

Keywords: acute decompensated heart failure; acute kidney injury; risk prediction; risk stratification.

Figure 1

Receiver operator characteristic curves showing area under the curve for AKI in ADHF patients. Receiver operator characteristic curves showing area under the curve for clinical model alone, 0.765; uNGAL, 0.762; uAGT, 0.814; risk model, 0.874; risk score in development cohort, 0.859; risk score in validation cohort, 0.847.

Figure 2

Calibration plot of observed vs predicted fracture risk for developing AKI during the first 7 days of hospitalization. Hosmer‐Lemeshow chi‐squared statistic is shown for the risk score in both development and validation cohorts. The points and circles indicate the observed frequencies by decile of predicted probability.

Figure 3

Risk levels according to the risk score in development and validation cohorts. Risks were categorized into low risk (0‐24 points), moderate risk (25‐34 points), high risk (35‐44 points), and very high risk (45‐55 points). Higher points means higher risk of developing AKI in patients with ADHF; P for trend <0.001.