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Mechanical life support algorithm for emergency management of patient receiving extracorporeal membrane oxygenation
Waqas Akhtar1, Sofia Pinto1, Emanuele Gerlando1
1Harefield Hospital, Royal Brompton and Harefield Hospitals, Guys and St Thomas' NHS Foundation Trust, London, UK.
Background:
There are limited practical advanced life support algorithms to aid teams in the management of cardiac arrest in patients on extracorporeal membrane oxygenation (ECMO).
Methods:
In our specialist tertiary referral centre we developed, by iteration, a novel resuscitation algorithm for ECMO emergencies which we validated through simulation and assessment of our multi-disciplinary team. A Mechanical Life Support course was established to provide theoretical and practical education combined with simulation to consolidate knowledge and confidence in algorithm use. We assessed these measures using confidence scoring, a key performance indicator (the time taken to resolve gas line disconnection) and a multiple choice question (MCQ) examination.
Results:
Following this intervention the median confidence scores increased from 2 (Interquartile range IQR 2, 3) to 4 (IQR 4, 4) out of maximum 5 (n = 53, p < 0.0001). Theoretical knowledge assessed by median MCQ score increased from 8 (6, 9) to 9 (7, 10) out of maximum 11 (n = 53, p0.0001). The use of the ECMO algorithm reduced the time taken by teams in a simulated emergency to identify a gas line disconnection and resolve the problem from median 128 s (65, 180) to 44 s (31, 59) (n = 36, p 0.001) and by a mean of 81.5 s (CI 34, 116, p = 0.001).
Conclusions:
We present an evidence based practical ECMO resuscitation algorithm that provides guidance to clinical teams responding to cardiac arrest in ECMO patients covering both patient and ECMO troubleshooting.
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