Predictive models for acute pancreatitis complicating acute kidney injury : A systematic review and meta-analysis

The utilisation of predictive models facilitates the identification of patients at risk, thereby enabling the implementation of individualised interventions. Despite the growing use of predictive models to estimate the likelihood of acute kidney injury in acute pancreatitis, concerns persist regarding their effectiveness in clinical settings and the rigor and rele-vance of forthcoming research. The objective of this study is to systematically review and evaluate predictive models for acute kidney injury in acute pancreatitis. A comprehensive search of relevant databases was conducted, encompassing China National Knowledge Infrastructure (CNKI), Wanfang, VIP, Chinese Medical Association, PubMed, Web of Sci-ence, Scopus, and Cochrane Library, with the search extending from database inception to 26 November 2024. The data from a number of selected studies was extracted using the CHARMS form, whilst the quality of predictive modelling studies was assessed using the PROBAST tool. A meta-analysis of the area under the curve (AUC) for predictive models and relevant predictors (≥2) was conducted using Stata 17.0 and MedCalc software. The total number of studies included in the review was 17, with a total of 9,949 patients and 37 predictive models. Of these, 32 models underwent internal validation, with an area under the curve (AUC) > 0.7. The overall risk of bias was high across all 17 studies, yet the overall applicability was deemed satisfactory. The results of the meta-analysis indicated that the pooled area under the curve (AUC) for internal validation across 20 predictive models for acute renal injury in acute pancreatitis was 0.790 (95% CI = 0.761–0.818); and the pooled external validation AUC for five models was 0.766 (95% CI = 0.684–0.845). The overall risk of bias was high across all 17 studies, with significant heterogeneity observed. How-ever, the overall applicability was deemed satisfactory. The predictive model for acute kidney injury complicating acute pancreatitis demonstrates moderate predictive efficacy. Nevertheless, given the elevated risk of bias in the majority of studies and the absence of adequate external validation, its clinical applicability merits further investigation.