Journal of cardiology · 2025
A simplified bedside model for prediction of acute kidney injury after percutaneous coronary intervention: CRASH score.
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Balanescu Dinu V, Fatema Kaniz, Lewis Brad R, Best Patricia J M, Gulati Rajiv, Herrmann Joerg
Аннотация
BACKGROUND: Acute kidney injury (AKI) following percutaneous coronary intervention (PCI) is associated with poor outcomes. The National Cardiovascular Data Registry (NCDR) AKI prediction model includes a relatively high number of complex clinical variables. We propose a simplified bedside score including 5 pre-procedural variables from the NCDR model as an effective tool for AKI prediction after PCI.
METHODS: The Mayo Clinic Rochester cardiac catheterization laboratory registry, which follows NCDR criteria, was analyzed between Q2 2022 and Q1 2023. Inclusion/exclusion criteria, definitions, and outcome data were based on the NCDR model. Logistic regression models were built to predict AKI, including a simplified integer score comprised of 5 pre-procedural variables: Cardiac arrest, Reduced glomerular filtration rate < 30 ml/min/1.73 m2, Anemia (Hb <10 mg/dl), Shock, and Heart failure history. Model calibration and discrimination were tested.
RESULTS: We identified 840 patients with a mean age of 70 (IQR 61-79), of which 593 (70.6 %) were men. AKI developed in 107 (12.7 %) patients. There was no significant difference between the groups in gender, vascular access, PCI indication, or contrast volume used (median: 150; IQR: 110-200 ml in the non-AKI group and median: 170 IQR: 123-213 ml in the AKI group; p = 0.14). The CRASH score demonstrated a c-statistic of 0.77 (0.60-0.88) and calibration intercept of 0.31 (-0.07-0.69) and slope of 1.03 (0.66-1.39) in the validation data, similar to the NCDR score.
CONCLUSIONS: A simplified integer score using 5 pre-procedural variables was an effective tool for risk prediction of post-PCI AKI, with performance similar to the more complex NCDR model.
METHODS: The Mayo Clinic Rochester cardiac catheterization laboratory registry, which follows NCDR criteria, was analyzed between Q2 2022 and Q1 2023. Inclusion/exclusion criteria, definitions, and outcome data were based on the NCDR model. Logistic regression models were built to predict AKI, including a simplified integer score comprised of 5 pre-procedural variables: Cardiac arrest, Reduced glomerular filtration rate < 30 ml/min/1.73 m2, Anemia (Hb <10 mg/dl), Shock, and Heart failure history. Model calibration and discrimination were tested.
RESULTS: We identified 840 patients with a mean age of 70 (IQR 61-79), of which 593 (70.6 %) were men. AKI developed in 107 (12.7 %) patients. There was no significant difference between the groups in gender, vascular access, PCI indication, or contrast volume used (median: 150; IQR: 110-200 ml in the non-AKI group and median: 170 IQR: 123-213 ml in the AKI group; p = 0.14). The CRASH score demonstrated a c-statistic of 0.77 (0.60-0.88) and calibration intercept of 0.31 (-0.07-0.69) and slope of 1.03 (0.66-1.39) in the validation data, similar to the NCDR score.
CONCLUSIONS: A simplified integer score using 5 pre-procedural variables was an effective tool for risk prediction of post-PCI AKI, with performance similar to the more complex NCDR model.