ACEF score and its predictive performance in coronary artery disease patients undergoing PCI: a systematic review and meta-analysis of the C-statistic.

Background: Despite being minimally invasive, percutaneous coronary intervention (PCI) presents challenges, especially regarding major adverse cardiovascular events (MACE), which typically occur within the first year after intervention. Furthermore, many existing MACE prediction models are complex and challenging to apply in clinical practice. Aims: This study evaluated the simple Age, Creatinine, Ejection Fraction (ACEF) score for predicting outcomes in coronary artery disease patients undergoing PCI. Methods: A meta-analysis of randomised controlled trials (RCTs) and cohort studies was conducted using six prominent databases. Predictive performance was assessed with the C-statistic, with MACE as the primary endpoint and mortality and ACEF modifications as secondary endpoints. Outcomes reported in at least two studies were included. Results: Twenty studies involving 41,255 patients were analysed, including three RCTs and eight multicentre studies. Key findings include the following: (1) the ACEF score showed good discrimination for <=30-day MACE (area under the curve [AUC] 0.71), (2) it demonstrated stronger predictive ability for both cardiac mortality (AUC 0.75 at 2 years) and all-cause mortality (AUC 0.82 at <=30 days), and (3) its performance was comparable to more complex scores, such as the modified ACEF (mACEF), the Age, Glomerular filtration rate, Ejection Fraction (AGEF), and the clinical SYNTAX scores. Conclusions: Adhering to the law of parsimony, the ACEF score is a straightforward tool based on objectively measured variables. The ACEF score effectively predicts MACE and mortality at <=30 days in PCI patients. Its simplicity and accessibility highlight its value as a practical tool for clinical risk stratification. (PROSPERO Identifier CRD42024558580).