Komarzynski · JCI insight 2019 · prospective observational cohort study · n=33

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

Cited 33 times in the scientific literature.

Level 4 - case-series / case-control

Exploratory observational study developing a predictive algorithm in a single small cohort without external validation.

PubMed 31430260 · doi:10.1172/jci.insight.130423 · record verified 2026-08-28

What was done

In 33 volunteers stratified by sex and age, researchers monitored circadian phase biomarkers during daily routines. Measurements included questionnaire-based chronotype, core body temperature (CBT) measured every minute via two ingestible electronic capsules swallowed 24 hours apart, dim light melatonin onset (DLMO) from hourly evening saliva samples, and 7 days of continuous chest acceleration and surface temperature tracking via a wearable sensor. Cosinor analysis, hidden Markov modeling, and multivariate regression were used to develop a predictive algorithm (INTime) for CBT bathyphase (temperature minimum).

What was found

Circadian phases varied widely across the 33 participants, spanning 5 hours and 10 minutes for DLMO, 7 hours for CBT bathyphase, and 9 hours and 10 minutes for surface temperature peak (acrophase). The INTime model—combining sex, chronotype score, center-of-rest time, and surface temperature bathyphase—predicted CBT bathyphase with an adjusted R² of 0.637 and achieved an estimation error of under 1 hour in 78.8% of subjects.

Why it matters

Accurately estimating individual circadian phase using non-invasive wearable sensors and baseline chronotype could enable practical personalized timing of drug delivery (chronotherapy) without burdensome core temperature pills or repeated saliva collections.

Limits

The study included only 33 participants and developed the predictive model without an independent external validation dataset. The abstract does not specify participant health status, and whether the algorithm maintains accuracy in shift workers or patients with clinical illnesses receiving active therapies was not evaluated.

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