Purpose: Acute kidney injury (AKI) is a serious complication in critically ill patients, associated with increased mortality and healthcare burden. Early identification of patients at high risk for disease progression is crucial for timely intervention and improved outcomes. To identify the risk factors for the progression of AKI in critically ill patients. Patients and Methods: A single-center, retrospective study was conducted involving 341 adult patients diagnosed with AKI stage 1 or 2 according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for AKI progression. Subgroup analyses were performed based on the initial AKI stage. Results: Among the 341 enrolled patients, 156 (45.7%) experienced AKI progression. Multivariate analysis identified the following independent risk factors: ischemic heart disease (adjusted Odds Ratio aOR = 2.994), sepsis (aOR = 2.644), lower minimum Mean Arterial Pressure (MAP) (aOR = 0.954), higher neutrophil percentage (aOR = 1.029), lower PaO 2 /FiO 2 ratio (aOR = 0.997), elevated D-dimer (aOR = 1.097), and increased anion gap (aOR = 1.163). Subgroup analysis revealed that risk factors differed between patients with initial AKI stage 1 and stage 2. Conclusion: This study identified multiple routinely available clinical factors independently associated with AKI progression. These findings support early risk stratification and targeted interventions—such as infection control, hemodynamic support, and correction of hypoxia and acidosis—to prevent the worsening of AKI and improve patient outcomes. Keywords: acute kidney injury, disease progression, risk factors, critical illness, logistic models, retrospective studies
Building similarity graph...
Analyzing shared references across papers
Loading...
Zihan Nan
xiaoxuan fan
Shiwei Guo
Risk Management and Healthcare Policy
Hebei Medical University
Fourth Hospital of Hebei Medical University
Affiliated Hospital of Hebei University
Building similarity graph...
Analyzing shared references across papers
Loading...
Nan et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69a765ecbadf0bb9e87dafa2 — DOI: https://doi.org/10.2147/rmhp.s576846