Urosepsis is a common postoperative complication in patients with upper urinary calculi, leading to prolonged hospital stays and increased health care costs. Despite the development of several predictive models, no systematic review or meta-analysis has comprehensively evaluated the risk factors for urosepsis in this patient population to date. A total of seven databases, including the China National Knowledge Infrastructure (CNKI), Wanfang, PubMed, EMBASE, Web of Science, the Cochrane Library, and EBSCO, were searched from inception to October 17, 2024. The literature was independently screened, and two researchers extracted profile information. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was used to assess the risk of bias and applicability. Meta-analyses were conducted using Stata 17.0. A total of 573 studies were retrieved. Of these, 25 studies met the inclusion criteria for systematic evaluation, and 12 studies were eligible for meta-analysis of predictive models. All studies were found to have a high risk of bias, primarily because of inappropriate data sources and poor reporting in the analysis domain. Meta-analysis of the models combined resulted in an AUC of 0.90 (95% CI: 0.87, 0.93), identifying 14 statistically significant independent predictors. Research on risk prediction models for postoperative urosepsis complications remains in the developmental stage, with an overall high risk of bias and a lack of clinical application. Predictors may play a significant role in preventing urosepsis after upper urinary calculi. The development of new models with larger sample sizes, rigorous study designs, and multicentre external validation are crucial for future studies. A systematic review and meta-analysis were conducted with the systematic review protocol registered in PROSPERO (registration number: CRD42024596003). Not applicable.
Wang et al. (Mon,) studied this question.