Bayesian methods: a potential path forward for sepsis trials.

BACKGROUND: Given the success of recent platform trials for COVID-19, Bayesian statistical methods have become an option for complex, heterogenous syndromes like sepsis. However, study design will require careful consideration of how statistical power varies using Bayesian methods across different choices for how historical data are incorporated through a prior distribution and how the analysis is ultimately conducted. Our objective with the current analysis is to assess how different uses of historical data through a prior distribution, and type of analysis influence results of a proposed trial that will be analyzed using Bayesian statistical methods. METHODS: We conducted a simulation study incorporating historical data from a published multicenter, randomized clinical trial in the US and Canada of polymyxin B hemadsorption for treatment of endotoxemic septic shock. Historical data come from a 179-patient subgroup of the previous trial of adult critically ill patients with septic shock, multiple organ failure and an endotoxin activity of 0.60-0.89. The trial intervention consisted of two polymyxin B hemoadsorption treatments (2 h each) completed within 24 h of enrollment. RESULTS: In our simulations for a new trial of 150 patients, a range of hypothetical results were observed. Across a range of baseline risks and treatment effects and four ways of including historical data, we demonstrate an increase in power with the use of clinically defensible incorporation of historical data. In one possible trial result, for example, with an observed reduction in risk of mortality from 44 to 37%, the probability of benefit is 96% with a fixed weight of 75% on prior data and 90% with a commensurate (adaptive-weighting) prior; the same data give an 80% probability of benefit if historical data are ignored. CONCLUSIONS: Using Bayesian methods and a biologically justifiable use of historical data in a prior distribution yields a study design with higher power than a conventional design that ignores relevant historical data. Bayesian methods may be a viable option for trials in critical care medicine where beneficial treatments have been elusive.

Intracranial hemorrhage surgery on patients on mechanical circulatory support: a case series.

BACKGROUND: Cardiac disease is the leading cause of death in the United States and late-stage heart failure is associated with a high level of morbidity and mortality. The ventricular assist devices and extracorporeal membrane oxygenators are the mainstay of mechanical circulatory support devices for the patients with extremely low cardiac output. However, they come at a price of significant risk factors, including intracranial hemorrhage. The incidence of intracranial hemorrhage on extracorporeal membrane oxygenators and on ventricular assist devices is 37% and 13% to 14%, respectively. METHODS/RESULTS: The cases in this series focus on the risks of ICH and the decompressive craniotomies that were carried out on patients while they were on mechanical circulatory support. The intraoperative anesthetic management for patients on mechanical circulatory support for the noncardiothoracic anesthesiologist is highlighted. CONCLUSIONS: The results of recent cardiothoracic surgery trials have led to an increase of surgical management instead of medical management in the treatment of heart failure. Although most agree with the immediate reversal of anticoagulation and antiplatelet therapy, there is no standard protocol for restarting anticoagulation or antiplatelet therapy after craniotomy in this population. The standard practices of resuscitation and ACLS including inotropes, vasopressors, and vasodilators (with the exception of chest compressions that can dislodge the devices), can be used as needed. The identification of cardiothoracic surgeons and perfusionists who are available for immediate assistance as and when required during the surgery and transportation is an important factor.