Rethinking acute kidney injury risk: beyond contrast volume in acute myocardial infarction

Abstract Introduction Acute kidney injury (AKI) is a frequent complication following acute myocardial infarction (AMI), influenced by multiple factors and associated to prolonged hospital stays and worse outcomes. While contrast volume used in coronary angiography is traditionally considered a key risk factor, its significance in contemporary clinical practice remains controversial. Purpose The purpose of this study was to assess predictive factors for AKI and to evaluate the prognostic value of the presence and grade of AKI in AMI patients. Methods Retrospective analysis including all consecutive AMI patients admitted to a Cardiology Department from November 2021 to October 2022. Demographic characteristics, cardiovascular risk factors, serial creatinine levels (at admission, 24- and 48- hours post-coronary angiography), hs-TnI, NT-proBNP, and other laboratory parameters were collected. AKI presence and severity were classified using the AKIN criteria. Logistic regression models were employed to identify predictors of AKI. Results 375 patients were included (72% male), of which 7.7% had previous history of chronic kidney disease (CKD). 10.7% of patients developed AKI (7.5% AKIN I, 1.9% AKIN II and 2.4% AKIN III). Patient characteristics are described in Table 1. Patients with CKD had 5.26 times higher odds of developing AKI (OR=5.26 95% CI: 2.37-13.00; p0.001). Patients on angiotensin converting enzyme inhibitors or angiotensin receptor blockers had higher odds of AKI (OR=2.10 95% CI: 1.06-4.20; p=0.03), as did those on insulin therapy (OR=3.04 95% CI: 1.13-8.19; p=0.04). Killip class was significantly associated with the presence of AKI (p0.001), with higher prevalence of AKI in Killip classes III and IV. Overall, mean contrast volume did not differ significantly between AKI and non-AKI groups. However, when analysing AKIN stages, we found contrast volume to be higher in patients with AKIN III (p=0.013). Results of logistic regression are shown in table 2. On multivariate analysis, NTproBNP was the only independent predictor of AKI, remaining a strong predictor even when adjusted for the most relevant baseline clinical and laboratory parameters (Wald=14.093; p0.001). Patients with AKI had higher in-hospital mortality (OR=6.673 95% CI: 2.011 to 22.144; p=0.005). Conclusions These findings suggest the need to focus on intrinsic patient factors rather than contrast volume alone when assessing AKI risk. In particular, NT-proBNP, as a surrogate for congestion, may be a good predictor of AKI after AMI. The fact that AKI was associated with increased in-hospital mortality underscores the need for targeted prevention and management strategies.