SYSTEMATIC REVIEW article
Front. Med.
Sec. Nephrology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1629369
Risk prediction models for contrast-induced acute kidney injury in patients with acute coronary syndromes : A systematic review and meta-analysis
Provisionally accepted
- 1School of Nursing, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- 2Department of Gynecology Nursing, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
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Background: Percutaneous coronary intervention (PCI) has become a crucial method for the treatment of acute coronary syndromes (ACS), which includes ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), and unstable angina (UA). However, contrast-induced acute kidney injury(CI-AKI) is one of its serious complications. A growing number of models have been used to predict ACS patients undergoing coronary angiography (CAG) or PCI, but the predictive efficacy of these models is unclear. Methods: We systematically searched PubMed, Web of Science, The Cochrane Library, and Embase from the inception to May 18, 2024. This study excluded non-English studies to reduce potential language bias. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate bias risk and applicability of the studies in the prediction model, and the area under the curve (AUC) values of the models were meta-analyzed by Stata 15.0 software. Results: 13,834 articles were retrieved, and 16 studies were finally included after screening. The This is a provisional file, not the final typeset article incidence of CI-AKI in patients with ACS underwent PCI or CAG ranged from 4.66% to 19.85%. The developed models exhibited a pooled AUC of 0.804 (95% CI: 0.772–0.836), while the validation models demonstrated a pooled AUC of 0.785 (95% CI: 0.747–0.823). However, significant heterogeneity was observed in both the development and validation cohorts (89.7% and 84.8%, respectively), along with publication bias (P < 0.05). All included studies were assessed as having a high risk of bias, mainly due to inappropriate data sources and bias in statistical analysis. Conclusions: No existing model for CI-AKI after CAG or PCI can currently be recommended for routine use due to the high risk of bias and the lack of external validation. Researchers should follow PROBAST and use a prospective design with a large sample size to improve the quality of prediction models and provide better clinical value.
Keywords: Acute Coronary Syndromes, Percutaneous Coronary Intervention, coronaryangiography, Contrast-induced acute kidney injury, Prediction model, Meta-analysis
Received: 15 May 2025; Accepted: 03 Sep 2025.
Copyright: © 2025 Zhang, Cao, Yang, Fu, Jia, Hu and Xiang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xuehua Cao, Department of Gynecology Nursing, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China
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