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Clinical prediction models for multidrug-resistant organism colonisation or infection in critically ill patients: a
Yi Wang1, Yanyan Xiao1, Qidi Yang1
1Intensive Care Unit, Peking University First Hospital, Beijing, China.
Introduction:
Multidrug-resistant organisms (MDROs) are pathogenic bacteria that are the leading cause of hospital-acquired infection which is associated with high morbidity and mortality rates in intensive care units, increasing hospitalisation duration and cost. Predicting the risk of MDRO colonisation or infection for critically ill patients supports clinical decision-making. Several models predicting MDRO colonisation or infection have been developed; however, owing to different disease scenarios, bacterial species and few externally validated cohorts in different prediction models; the stability and applicability of these models for MDRO colonisation or infection in critically ill patients are controversial. In addition, there are currently no standardised risk scoring systems to predict MDRO colonisation or infection in critically ill patients. The aim of this systematic review is to summarise and assess models predicting MDRO colonisation or infection in critically ill patients and to compare their predictive performance.
Methods And Analysis:
We will perform a systematic search of PubMed, Cochrane Library, CINAHL, Embase, Web of science, China National Knowledge Infrastructure and Wanfang databases to identify all studies describing the development and/or external validation of models predicting MDRO colonisation or infection in critically ill patients. Two reviewers will independently extract and review the data using the Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist; they will also assess the risk of bias using the Prediction Model Risk of Bias Assessment Tool. Quantitative data on model predictive performance will be synthesised in meta-analyses, as applicable.
Ethics And Dissemination:
Ethical permissions will not be required because all data will be extracted from published studies. We intend to publish our results in peer-reviewed scientific journals and to present them at international conferences on critical care.
Prospero Registration Number:
CRD42022274175.
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