Acute kidney injury prediction model utility in premature myocardial infarction.

ABSTRACT: The incidence of premature myocardial infarction (PMI) has been rising and acute kidney injury (AKI) occurring in PMI patients severely impacts prognosis. This study aimed to develop and validate a prediction model for AKI specific to PMI patients. The MIMIC-Ⅲ-CV and MIMIC-Ⅳ databases were utilized for model derivation of PMI patients. Single-center data served for external validation. There were 571 and 182 AKI patients in the training set (n = 937) and external validation set (n = 292) cohorts, respectively. Finally, a 7-variable model consisting of: Sequential Organ Failure Assessment (SOFA) score, coronary artery bypass grafting (CABG), ICU stay time, loop diuretics, estimated glomerular filtration rate (eGFR) HCO3- and Albumin was developed, achieving an AUC of 0.85 (95% CI: 0.83-0.88

SUBMITTER: Tao F 

PROVIDER: S-EPMC10882170 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature