Step-by-step guide to creating the best syncope units: From combined United States and European experiences

Diagnostic and societal impact of implementing the syncope guidelines of the European Society of Cardiology (SYNERGY study)

BACKGROUND

Syncope management is fraught with unnecessary tests and frequent failure to establish a diagnosis. We evaluated the potential of implementing the 2018 European Society of Cardiology (ESC) Syncope Guidelines regarding diagnostic yield, accuracy and costs.

METHODS

A multicentre pre-post study in five Dutch hospitals comparing two groups of syncope patients visiting the emergency department: one before intervention (usual care; from March 2017 to February 2019) and one afterwards (from October 2017 to September 2019). The intervention consisted of the simultaneous implementation of the ESC Syncope Guidelines with quick referral routes to a syncope unit when indicated. The primary objective was to compare diagnostic accuracy using logistic regression analysis accounting for the study site. Secondary outcome measures included diagnostic yield, syncope-related healthcare and societal costs. One-year follow-up data were used to define a gold standard reference diagnosis by applying ESC criteria or, if not possible, evaluation by an expert committee. We determined the accuracy by comparing the treating physician's diagnosis with the reference diagnosis.

RESULTS

We included 521 patients (usual care, n = 275; syncope guidelines intervention, n = 246). The syncope guidelines intervention resulted in a higher diagnostic accuracy in the syncope guidelines group than in the usual care group (86% vs.69%; risk ratio 1.15; 95% CI 1.07 to 1.23) and a higher diagnostic yield (89% vs. 76%, 95% CI of the difference 6 to 19%). Syncope-related healthcare costs did not differ between the groups, yet the syncope guideline implementation resulted in lower total syncope-related societal costs compared to usual care (saving €908 per patient; 95% CI €34 to €1782).

CONCLUSIONS

ESC Syncope Guidelines implementation in the emergency department with quick referral routes to a syncope unit improved diagnostic yield and accuracy and lowered societal costs.

TRIAL REGISTRATION

Netherlands Trial Register, NTR6268.

Can Artificial Intelligence Enhance Syncope Management?: A JACC: Advances Multidisciplinary Collaborative Statement

Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs.