ECG characteristics as indicators of the aetiology of pulseless electrical activity: a systematic review

Introduction: The incidence of pulseless electrical activity (PEA) as a presenting rhythm in out-of-hospital cardiac arrest is rising in comparison with other rhythms. Prompt recognition of the cause of PEA can improve outcomes. The assessment of electrocardiogram (ECG) characteristics during resuscitation has been suggested as a source of diagnostic information for clinicians. The aim of this systematic review was to identify literature evaluating the use of ECG characteristics as indicators of the aetiology of PEA and to consider how their findings may be utilised in clinical practice. Methods: Case series, observational studies, randomised controlled trials and empirical research investigating the ECG characteristics of adult patients and reporting the aetiology of PEA were searched for via a systematic literature search of the MEDLINE, CINAHL Plus and EMBASE databases. Searches for grey literature were performed, as well as reference screening. A risk-of-bias assessment was undertaken for each included study. Results: A total of four articles were selected for final inclusion. One study reported a statistically significant correlation between the presence of wide QRS complexes and hyperkalaemia. No further associations between ECG characteristics and the aetiology of cardiac arrest were reported. Three studies were found to be at moderate risk of bias due to incomplete inclusion of patients. Studies often assessed groups of aetiologies, rather than specific causes. Consequently, this limits their application in clinical practice. Conclusion: ECG characteristics should not be used in isolation as an indicator of the aetiology of cardiac arrest in patients with PEA. The included studies often employed broad categorisations of aetiologies, limiting their ability to identify specific characteristics associated with individual causes. Future research should include analysis of specific aetiologies and the evaluation of ECG characteristics to augment other diagnostic tools.