International Perfusion Association
This study analyzed adult patients with cardiogenic shock receiving venoarterial ECMO, using data from the ELSO registry between 2009 and 2019. It found that initiating ECMO more than 24 hours after admission was associated with increased in-hospital mortality, suggesting the importance of timely ECMO initiation to improve survival outcomes.
This retrospective cohort study compared unilateral and bilateral femoral cannulation strategies for peripheral venoarterial ECMO and found no significant difference in overall limb ischemia risk. However, bilateral cannulation was associated with lower incidences of compartment syndrome, cannulation site bleeding, vessel repair, and in-hospital mortality.
In a study comparing the effectiveness of Impella and intra-aortic balloon pump (IABP) in patients with refractory cardiogenic shock requiring veno-arterial extracorporeal membrane oxygenation (VA-ECMO), no significant difference in in-hospital mortality was found between the two groups. However, the Impella group experienced longer mechanical ventilation support and hospital stays, and incurred higher medical costs than the IABP group, suggesting a need for further research to optimize the use of Impella in such clinical scenarios.
During the SARS-CoV-2 pandemic, a study compared clinical outcomes of patients on ECMO support using polypropylene (PP) oxygenation membranes versus poly-methylpentene (PMP) membranes. It found that PP membranes required more changes and had a higher frequency of renal replacement therapy as a complication, yet were a feasible alternative during supply shortages, without significant differences in mortality.
This study utilized machine learning algorithms to predict acute brain injury (ABI) in patients on venoarterial extracorporeal membrane oxygenation (VA-ECMO), analyzing data from the Extracorporeal Life Support Organization Registry. It found that longer ECMO duration and higher 24-hour pump flow were associated with ABI in both non-ECPR and ECPR VA-ECMO patient groups, highlighting key risk factors for neurological complications in these patients.
In lung transplantation, the use of intraoperative mechanical support, particularly cardiopulmonary bypass (CPB) and extracorporeal membrane oxygenation (ECMO), has evolved over time due to their respective advantages and disadvantages. While CPB was traditionally preferred for its full hemodynamic support, it poses risks like systemic inflammation and coagulopathy; ECMO, on the other hand, offers many benefits of CPB with fewer risks, leading to better outcomes such as reduced primary graft dysfunction and overall improved survival, suggesting its potential as a standard protocol in lung transplants.
This systematic review and meta-analysis of 39 studies involving 6409 patients reveal that more than 50% of patients with high-risk pulmonary embolism (HRPE) treated with extracorporeal membrane oxygenation (ECMO) survive, with mortality significantly lower in those receiving ECMO combined with catheter-directed therapy compared to systemic thrombolysis. Factors like cardiac arrest prior to ECMO and pre-ECMO heart rate are associated with mortality, highlighting the need for further research to compare ECMO with non-ECMO therapies.
This study surveys clinicians across seven U.S. hospitals to understand the informed consent process for Extracorporeal Membrane Oxygenation (ECMO) and ethical complexities in its application. Results reveal variability in the time spent on obtaining consent, use of exclusion criteria for ECMO, and differences in approaches to withdrawing ECMO, highlighting significant ethical challenges and inconsistencies in practice.
This study investigates the impact of different operational modes of an extracorporeal blood pump (CentriMag) on blood flow patterns and the associated risks of bleeding, thrombosis, and hemolysis using computational fluid dynamics and hemocompatibility models. It finds that venous-arterial (V-A) ECMO mode results in the highest risk of these complications, with heart failure (HF) mode being the least risky, largely due to variations in flow patterns affecting cell and protein functions.
The study developed and validated RIETS, a machine learning-based system using 11 routine clinical and laboratory biomarkers to predict COVID-19 severity upon hospitalization, showing high accuracy and low bias risk. RIETS demonstrated excellent predictive performance, including during the Omicron variant period, and provided interpretable data for clinical use, suggesting its potential for improving patient triaging and resource allocation in hospitals.
