Evidence map›Paper›PMID 40286232›Full record

ArticleEpilepsia2025

More variable circadian rhythms in epilepsy captured by long-term heart rate recordings from wearable sensors.

Billy C Smith, Christopher Thornton, Rachel E Stirling, Guillermo M Besné, Sarah J Gascoigne, Nathan Evans, Peter N Taylor, Karoline Leiberg, Philippa J Karoly, Yujiang Wang

Abstract read
In one paragraph

Article in Epilepsia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Billy C SmithComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Christopher ThorntonComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Rachel E StirlingGraeme Clark Institute and Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
Guillermo M BesnéComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Sarah J GascoigneComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID https://orcid.org/0000-0003-1013-1875
Nathan EvansComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Peter N TaylorComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.ORCID https://orcid.org/0000-0003-2144-9838
Karoline LeibergComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Philippa J KarolyGraeme Clark Institute and Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
Yujiang WangComputational Neurology, Neuroscience and Psychiatry Lab, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.

Funding

Engineering and Physical Sciences Research Council EP/L015358/1National Health and Medical Research Council (Australia) #1178220UK Research and Innovation MR/T04294X//1UK Research and Innovation MR/V026569/1
6 · The paper itself

Abstract

objectiveThe circadian rhythm synchronizes physiological and behavioral patterns with the 24-h light-dark cycle. Disruption to the circadian rhythm is linked to various health conditions, although optimal methods to describe these disruptions remain unclear. An emerging approach is to examine the intraindividual variability in measurable properties of the circadian rhythm over extended periods. Epileptic seizures are modulated by circadian rhythms, but the relevance of circadian rhythm disruption in epilepsy remains unexplored. Our study investigates intraindividual circadian variability in epilepsy and its relationship with seizures.

methodsWe retrospectively analyzed >70 000 h of wearable smartwatch data (Fitbit) from 143 people with epilepsy (PWE) and 31 healthy controls. Circadian oscillations in heart rate time series were extracted, daily estimates of circadian period, acrophase, and amplitude properties were produced, and estimates of the intraindividual variability of these properties over an entire recording were calculated.

resultsPWE exhibited greater intraindividual variability in period (76 vs. 57 min, d = .66, p < .001) and acrophase (64 vs. 48 min, d = .49, p = .004) compared to controls, but not in amplitude (2 beats per minute, d = -.15, p = .49). Variability in circadian properties showed no correlation with seizure frequency nor any differences between weeks with and without seizures. SIGNIFICANCE: For the first time, we show that heart rate circadian rhythms are more variable in PWE, detectable via consumer wearable devices. However, no association with seizure frequency or occurrence was found, suggesting that this variability might be underpinned by the epilepsy etiology rather than being a seizure-driven effect.

Indexed as

Circadian RhythmEpilepsyHeart RateWearable Electronic DevicesAdolescentAdultFemaleHumansMaleMiddle AgedRetrospective StudiesYoung Adultcircadian disruptionday‐to‐dayintraindividualseizurevariability

Identifiers

PMID40286232
PMCPMC12371681

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.