Abstract
BACKGROUND: Stress-induced hyperglycemia (SIH) is a common phenomenon in acute myocardial infarction and is associated with poor prognosis. The relationship between glycemic gap (GG), a marker of SIH, and ST-segment elevation myocardial infarction (STEMI)-associated acute kidney injury (STAAKI) remains unclear. This study aims to explore the predictive value of GG for the risk of STAAKI after percutaneous coronary intervention (PCI) in STEMI patients. METHODS: This study retrospectively selected patients diagnosed with STEMI who underwent primary PCI. Logistic regression analysis was used to identify the risk factors associated with STAAKI. To examine the dose-response relationship between GG and STAAKI, restricted cubic splines (RCS) were employed. The predictive accuracy of the models was assessed using Delong test, net reclassification index (NRI) and integrated discrimination improvement (IDI). RESULTS: This study included 595 patients, the incidence of STAAKI was 9.2%. Multivariate logistic regression showed LVEF (OR per 1% increase = 0.931, 95% CI: 0.895 ~ 0.969), NT-proBNP (OR per 1 pg/mL increase = 1.579, 95% CI: 1.212 ~ 2.057), and GG (OR per 1 mmol/L increase = 1.379, 95% CI: 1.223 ~ 1.554) as independent predictors of STAAKI. RCS analysis indicated a linear dose-response relationship between GG and STAAKI. After integrating GG, the new model could significantly improve the risk model for STAAKI (Z = 2.77, NRI = 0.780, and IDI = 0.095; All P < 0.05). CONCLUSION: GG is an independent risk factor for the occurrence of STAAKI after PCI in STEMI patients, and integrating GG can significantly improve risk modeling regarding STAAKI. CLINICAL TRIAL NUMBER: Not applicable.