Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

Background: 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.Methods: 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.Results: 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.Conclusion: 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.

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Development and Validation of a Prediction Model for Irreversible Worsened Cardiac Function in Patients With Acute Decompensated Heart Failure

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.785587 ◽

2021 ◽

Vol 8 ◽

Author(s):

Lei Wang ◽

Yun-Tao Zhao

Keyword(s):

Heart Failure ◽

Cardiac Function ◽

Prediction Model ◽

Acute Decompensated Heart Failure ◽

Nyha Class ◽

Decompensated Heart Failure ◽

Study Data ◽

Left Ventricular ◽

Lasso Regression ◽

Multivariable Logistic Regression Model

Background: Irreversible worsening of cardiac function is an adverse event associated with significant morbidity among patients with acute decompensated heart failure (ADHF). We aimed to develop a parsimonious model which is simple to use in clinical settings for the prediction of the risk of irreversible worsening of cardiac function.Methods: A total of 871 ADHF patients were enrolled in this study. Data for each patient were collected from the medical records. Irreversible worsening of cardiac function included cardiac death within 30-days of patient hospitalization, implantation of a left ventricular assistance device, or emergency heart transplantation. We performed LASSO regression for variable selection to derive a multivariable logistic regression model. Five candidate predictors were selected to derive the final prediction model. The prediction model was verified using C-statistics, calibration curve, and decision curve.Results: Irreversible worsening of cardiac function occurred in 7.8% of the patients. Advanced age, NYHA class, high blood urea nitrogen, hypoalbuminemia, and vasopressor use were its strongest predictors. The prediction model showed good discrimination C-statistic value, 0.866 (95% CI, 0.817–0.907), which indicated good identical calibration and clinical efficacy.Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of irreversible worsening of cardiac function among ADHF patients. The findings may provide a reference for clinical physicians for detection of irreversible worsening of cardiac function and enable its prompt management.

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