背景:预测模型有助于针对具有多重耐药菌(MDRO)定植或感染风险的患者,并且可以作为指导临床实践的工具,以防止MDRO传播和不适当的经验性抗生素治疗。然而,有限的证据确定可用模型中哪些具有低偏倚风险且适合临床应用.
目的:确定,描述,评价,并总结了为预测MDRO定植或感染而开发或验证的所有预后和诊断模型的性能。
方法:搜索了6个电子文献数据库和临床注册数据库,直至2022年4月。
方法:任何多变量预后和诊断模型的开发和验证研究,以预测成人MDRO定植或感染。
■使用偏差风险预测模型评估工具评估偏差风险。使用等级方法评估证据确定性。
进行荟萃分析,以总结在至少两个非重叠数据集中进行的模型外部验证的辨别和校准。
结果:我们纳入了162个模型(108个研究),用于诊断(n=135)和预测(n=27)MDRO定植或感染。模型表现出很高的偏差风险,尤其是统计分析。高频预测因素是年龄,最近的侵入性程序,抗生素的使用,和事先住院。不到25%的模型经过了外部验证,只有七个独立团队。对一种诊断模型和两种预后模型的荟萃分析仅产生了非常低至低确定性的证据。
结论:本综述全面描述了识别有MDRO定植或感染风险的患者的模型。由于偏差的高风险,我们不能推荐哪些模型已经准备好应用,有限的验证,以及荟萃分析证据的低确定性,表明明确需要改进模型开发和外部验证研究的进行和报告,以促进临床应用。
BACKGROUND: Prediction models help to target patients at risk of multidrug-resistant organism (MDRO) colonization or infection and could serve as tools informing clinical practices to prevent MDRO transmission and inappropriate empiric antibiotic therapy. However, there is limited evidence to identify which among the available models are of low risk of bias and suitable for clinical application.
OBJECTIVE: To identify, describe, appraise, and summarise the performance of all prognostic and diagnostic models developed or validated for predicting MDRO colonization or infection.
METHODS: Six electronic literature databases and clinical registration databases were searched until April 2022.
METHODS: Development and validation studies of any multivariable prognostic and diagnostic models to predict MDRO colonization or infection in adults.
METHODS: Adults (≥ 18 years old) without MDRO colonization or infection (in prognostic models) or with unknown or suspected MDRO colonization or infection (in diagnostic models).
UNASSIGNED: The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias. Evidence certainty was assessed using the Grading of Recommendations Assessment, Development, and Evaluation approach.
UNASSIGNED: Meta-analyses were conducted to summarize the discrimination and calibration of the models\' external validations conducted in at least two non-overlapping datasets.
RESULTS: We included 162 models (108 studies) developed for diagnosing (n = 135) and predicting (n = 27) MDRO colonization or infection. Models exhibited a high-risk of bias, especially in statistical analysis. High-frequency predictors were age, recent invasive procedures, antibiotic usage, and prior hospitalization. Less than 25% of the models underwent external validations, with only seven by independent teams. Meta-analyses for one diagnostic and two prognostic models only produced very low to low certainty of evidence.
CONCLUSIONS: The review comprehensively described the models for identifying patients at risk of MDRO colonization or infection. We cannot recommend which models are ready for application because of the high-risk of bias, limited validations, and low certainty of evidence from meta-analyses, indicating a clear need to improve the conducting and reporting of model development and external validation studies to facilitate clinical application.