Clinical prediction models for multidrug-resistant organism colonisation or infection in critically ill patients: a systematic review protocol

Abstract

IntroductionMultidrug-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 analysisWe 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 disseminationEthical 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 numberCRD42022274175.

Preventing Multidrug-Resistant Bacterial Transmission in the Intensive Care Unit with a Comprehensive Approach: A Policymaking Manual

“…We have identified two studies that provide examples of potential future directions in this research area. Çaǧlayan et al proposed a data-driven modeling framework that can be used as a clinical decision support tool for predicting MDROs colonization and could help guide infection control measures in ICUs [ 83 ], while Wang et al outlined a study protocol for a systematic review that aimed to summarize and assess existing models predicting MDROs colonization or infection in critically ill patients [ 84 ].…”

Population pharmacokinetics and individualized dosing of tigecycline for critically ill patients: a prospective study with intensive sampling

“…The prevalence in critically ill patients was even higher. In developed countries, approximately 25% of critically ill patients experience at least one healthcare-associated infection, while the rate is as high as 50% in developing countries ( Vincent et al, 2020 ; Wang et al, 2022 ). In addition, a global estimation indicated that approximately 4.95 million deaths in 2019 were associated with antimicrobial resistance, and this number is projected to increase to more than 10 million by 2050 ( Murray et al, 2022 ).…”

Development and Validation of a Nomogram Prediction Model for Multidrug-Resistant Organisms Infection in a Neurosurgical Intensive Care Unit

“…The global mortality attributed to MDROs was reported to be 700,000 in 2015, and this number is projected to surpass 10 million by 2050. 2 MDROs infections have emerged as a significant issue in nosocomial infections worldwide, 3,4 particularly in intensive care units (ICUs). [5][6][7] Numerous studies have highlighted that MDROs infections contribute substantially to morbidity and mortality among hospitalized patients, resulting in prolonged hospital stays and increased healthcare costs.…”