Acute kidney injury (AKI) is a common complication among patients hospitalized for acute heart failure (AHF), and is associated with increased mortality. The goal of this study was to derive and validate a prediction score for AKI in AHF patients.Methods:
The hospital medical records of 1709 patients with AHF were reviewed. AKI was defined as an increase in serum creatinine (SCr) of ≥26.4 μmol/L or ≥50% within 48 h. A multivariate logistic regression analysis was undertaken to develop a new prediction score. The area under the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow goodness-of-fit statistic test were calculated to assess the discrimination and calibration of the prediction score, respectively.Results:
Acute kidney injury developed in 32.2% of patients with AHF. Factors independently associated with the risk of AKI included: ≥70 years of age, ≥3 previous hospital admissions for AHF, systolic blood pressure <90 mmHg, serum sodium <130 mmol/L, heart functional class IV, proteinuria, SCr ≥104 μmol/L and intravenous furosemide dose ≥80 mg/day. A prediction score for AKI was derived based on the β coefficients of each risk factor. Patients with ≥8 points would be considered at high risk for development of AKI (55.1% incidence vs 18% in those with <8 points,P< 0.001). Both the derived and validated datasets showed adequate discrimination (area under ROC curve was 0.76 in both datasets) and calibration (Hosmer-Lemeshow statistic test,P= 0.98 and 0.13, respectively).Conclusion:
The newly derived and validated clinical prediction score may effectively predict AKI in the patients hospitalized with AHF.SUMMARY AT A GLANCE
Development and validation of a risk prediction score for patients with acute heart failure (AHF) in a Chinese cohort identified that age, previous hospital admissions for AHF, heart function class, systolic hypotension, hyponatraemia, proteinuria, elevated serum creatinine and Frusemide dose effectively predict AKI in the patients hospitalized with AHF.