Temporal variation in out-of-hospital cardiac arrest occurrence in individuals with or without diabetes

L H van Dongen, P de Goede, S Moeller, T E Eroglu, F Folke, G Gislason, M T Blom, P J M Elders, C Torp-Pedersen, H L Tan

Research output: Contribution to journal/periodicalArticleScientificpeer-review


Objective: Out-of-hospital cardiac arrest (OHCA) occurrence has been shown to exhibit a circadian rhythm, following the circadian rhythm of acute myocardial infarction (AMI) occurrence. Diabetes mellitus (DM) is associated with changes in circadian rhythm. We aimed to compare the temporal variation of OHCA occurrence over the day and week between OHCA patients with DM and those without.

Methods: In two population-based OHCA registries (Amsterdam Resuscitation Studies [ARREST] 2010-2016, n = 4163, and Danish Cardiac Arrest Registry [DANCAR], 2010-2014, n = 12,734), adults (≥18y) with presumed cardiac cause of OHCA and available medical history were included. Single and double cosinor analysis was performed to model circadian variation of OHCA occurrence. Stratified analysis of circadian variation was performed in patients with AMI as immediate cause of OHCA.

Results: DM patients (22.8% in ARREST, 24.2% in DANCAR) were older and more frequently had cardiovascular risk factors or previous cardiovascular disease. Both cohorts showed 24 h-rhythmicity, with significant amplitudes in single and double cosinor functions (P-range < 0.001). In both registries, a morning peak (10:00-11:00) and an evening peak (20:00-21:00) was observed in both DM and non-DM patients. No septadian variation was observed in either DM or non-DM patients (P-range 0.13-84).

Conclusions: In these two population-based OHCA registries, we observed a similar circadian rhythm of OHCA occurrence in DM and non-DM patients.

Original languageEnglish
Pages (from-to)100167
JournalResuscitation plus
Publication statusPublished - Dec 2021


Dive into the research topics of 'Temporal variation in out-of-hospital cardiac arrest occurrence in individuals with or without diabetes'. Together they form a unique fingerprint.

Cite this