Background A systematic review of the pooled effect of articles presenting current basic life support (BLS) algorithms for the treatment of cardiac arrest has never been carried.
Aims We aimed to record and classify potential inherent factors influencing simplicity negatively in teaching, learning and retention of cardiopulmonary resuscitation (CPR) delivered by health care providers or lay persons.
Methods We performed a search of the relevant literature exploring MEDLINE, COCHRANE LIBRARY and SCOPUS databases. Potential inhibitory factors in the structure of available algorithms influencing simplicity in teaching, learning and retention of BLS were recorded and stratified accordingly. In a second phase of this study, we tested the hypothesis that different options of a BLS algorithm might influence CPR retention negatively, by asking 348 health care provider participants of our CPR seminars to describe their predicted response in an emergency to: (1) a real-time model implicating the various victims and rescuers; and (2) a hypothetical challenging ‘all-in-one’ BLS algorithm model.
Results Fifteen articles presenting current BLS algorithms evidenced 163 suggestions that produced 23 different CPR options: five contrasting algorithms (21.8%); three two-option models (13%); six vague technical or scientific suggestions (26%); and nine multiple choices of action (39.1%). Identified references contributed differently in the development of educationally polymorphic BLS options in each of the four categories (P < 0.0001) and were all brought about by variants of victims and rescuers. Participants of CPR seminars answered that in an emergency they could remember the hypothetical BLS model (90%, P = 0.007) rather than a current BLS algorithm for adults (42.2%) or children (36%).
Conclusions Educational polymorphisms of BLS algorithms could build unpredictable barriers between rescuers and cardiac arrest victims and might seriously limit instructors' educational effectiveness. These findings might support an alternative trial hypothesis of a simple ‘all-in-one algorithm’ educational approach in future.