Evidence map›Paper›PMID 31430260›Full record

Observational studyJCI insight2019

Predictability of individual circadian phase during daily routine for medical applications of circadian clocks.

Sandra Komarzynski, Matei Bolborea, Qi Huang, Bärbel Finkenstädt, Francis Lévi

Registry-linked trialOpen access · goldAbstract readObservational Study
In one paragraph

Observational study in JCI insight, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05159141 (The Role of Circadian Rhythm in the Effect of Sleep Intervention on Obesity Prevention in Early Childhood), which is not on this map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
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.

NCT05159141 naunknown statusnot on this mapstarted 2022, after this paper: background citation

The Role of Circadian Rhythm in the Effect of Sleep Intervention on Obesity Prevention in Early Childhood

TypeinterventionalSponsorShanghai Jiao Tong University School of MedicineRan2022 to 2024Enrolled480ConditionsInfant Sleep ProblemArmsBehavioral sleep intervention
3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 33 citations in OpenAlex.

  1. Trial
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  3. Review
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  5. Article
  6. Article
  7. Article
  8. Analysis of wearable time series data in endocrine and metabolic research.Current opinion in endocrine and metabolic research · 2022
    Review
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  10. Article
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  13. Review
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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

5 authors at 2 institutions in 2 countries.

Sandra KomarzynskiMedical School, Warwick University, Coventry, United Kingdom.
Matei BolboreaMedical School, Warwick University, Coventry, United Kingdom.
Qi HuangMedical School, Warwick University, Coventry, United Kingdom.
Bärbel FinkenstädtINSERM-Warwick European Associated Laboratory, INSERM U935, Villejuif, France.
Francis LéviMedical School, Warwick University, Coventry, United Kingdom.
Inserm · FRUniversity of Warwick · GB

Funding

Medical Research Council MR/M013170Medical Research Council MR/M013170/1
6 · The paper itself

Abstract

BACKGROUNDCircadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of core body temperature (CBT) maximum (acrophase) or minimum (bathyphase).METHODSWe aimed at circadian phase determination and readout during daily routines in volunteers stratified by sex and age. We measured (a) chronotype, (b) every minute (q1min) CBT using 2 electronic pills swallowed 24 hours apart, (c) DLMO through hourly salivary samples from 1800 hours to bedtime, and (d) q1min accelerations and surface temperature at anterior chest level for 7 days, using a teletransmitting sensor. Circadian phases were computed using cosinor and hidden Markov modeling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase.RESULTSAmong the 33 participants, individual circadian phases were spread over 5 hours, 10 minutes (DLMO); 7 hours (CBT bathyphase); and 9 hours, 10 minutes (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e., with an error less than 1 hour for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score with computed center-of-rest time and surface temperature bathyphase (adjusted R2 = 0.637).CONCLUSIONINTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalization following further validation.FUNDINGMedical Research Council, United Kingdom; AP-HP Foundation; and INSERM.

Indexed as

Drug ChronotherapyModels, BiologicalAdultAgedBody TemperatureCircadian ClocksCircadian RhythmFemaleHealthy VolunteersHumansMaleMarkov ChainsMiddle AgedMonitoring, PhysiologicPhotoperiodRemote Sensing TechnologyClinical practiceDrug therapyMedical devicesNeuroscienceTherapeutics

Identifiers

PMID31430260
PMCPMC6795290
OpenAlexW2969513967

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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 OpenQuestion graph.