Intraosseous Versus Intravenous Vascular Access During Resuscitation Following Out-of-Hospital Cardiac Arrest

1. Background: Intraosseous (IO) access is a new, fast, safe and efficient route of rescue of critically ill patients. Studies found drug pharmacokinetics and pharmacodynamics of IO are similar to IV route. Compared with IV and CVC, IO is time-consuming, easy to grasp, and has high operation success rate. Guidelines recommend IO when the establishment of vascular access is difficult or impossible. Recent animal studies suggest that IO access have better ventricular fibrillation termination rates, ROSC rates and survival compared with IV route. However, recent retrospective clinical studies found that IO versus IV treatment was associated with a lower likelihood of ROSC and hospitalization. How routes of vascular access influence clinical outcomes after OHCA merits multicenter randomized controlled trial. We suppose IO versus IV treatment is associated with a higher likelihood of ROSC and hospital and discharge survival. 2. Materials and methods: Study design This study is a prospective, open, two-arm, multicenter randomized controlled trial. The study will be conducted by 22 medical centers or affiliated hospitals in China. We will enroll nearly 2356 OHCA patients by the eligibility and exclusion criteria during January 2020 to December 2022. All of the patients will be randomized to one of 2 routes of vascular access: tibial intraosseous or peripheral intravenous. Other treatment measures of two groups refer to 2015 AHA Advanced Cardiovascular Life Support guidelines. Statistical analysis Intention-to-treat analysis (ITT) and per-protocol set (PPS) sensitivity analysis will be conducted in our study. Categorical variables are presented as counts and percentages, and differences are analyzed using the χ2 test. Continuous variables are presented as means with standard deviations or median (interquartile range \[IQR\]), and analysis is done by the Student t test or the Mann-Whitney U test according to normal or non-normal distributions. 3. Sample Size