Development and validation of a dynamic nomogram for short-term survival in acute heart failure patients with acute kidney injury upon ICU admission.

OBJECTIVE

The objective of this study is to develop and validate an effective prognostic nomogram for predicting the short-term survival rate of patients with acute heart failure (AHF) complicated by acute kidney injury (AKI) who are admitted to the intensive care unit (ICU).

PATIENTS AND METHODS

We conducted an analysis of data from patients of AHF with AKI spanning the period from 2008 to 2019, utilizing the MIMIC-IV database. Patients were randomly divided into training and validation sets. The training set employed the least absolute shrinkage and selection operator regression model to identify predictors of AKI. Subsequently, a dynamic nomogram was constructed using multivariate Cox regression analysis within the training set and was subsequently validated using the validation set. The nomogram's predictive accuracy, calibration, and clinical utility were evaluated through the concordance index (C-index), calibration plots, and decision curve analysis (DCA).

RESULTS

A total of 978 AHF patients with AKI were analyzed. Multivariate analysis identified serum creatinine, race, age, use of human albumin, use of vasoactive drug, and hemoglobin as independent predictors significantly influencing the short-term prognosis of AHF patients with AKI upon ICU admission. The C-index for the training and validation sets were 0.81 (95%CI: 0.74-0.87) and 0.80 (95 % CI: 0.67-0.92), respectively. The calibration plot of the nomogram demonstrated a close alignment between predicted and observed probabilities. Furthermore, the DCA confirmed the clinical utility of the nomogram.

CONCLUSIONS

This study presents a dynamic nomogram that incorporates clinical risk factors and can be conveniently utilized to predict short-term prognosis for AHF patients with AKI upon ICU admission.