Circadian Rhythm
Conditions
Keywords
wavelet analysis, ICU, vital oscillations, rhythms, clinical outcomes, chrono-apps, biodynamic lighting
Brief summary
The goal of this retrospective exploratory study is to examine how the body's natural day-and-night rhythms and oscillatory patterns behave in people who were treated in the Intensive Care Unit (ICU). The study uses routine clinical data that were already collected during and after the ICU stay, including post-discharge follow-up measurements (where available), such as heart rate, temperature, blood pressure, blood sugar, and insulin. The researchers want to learn whether these measurements show daily patterns and whether patients can be grouped based on their oscillatory profiles. The study also examines whether certain clinical factors such as illness severity scores, sedation levels, organ support treatments, or medications are associated with changes in these oscillatory rhythms. The team will explore whether conditions that can develop during or after critical illness, such as delirium, muscle weakness, or Post-Intensive Care Syndrome (PICS), are linked to disturbed physiological rhythms. Another goal is to test whether it is technically possible to show a patient's rhythm profile in real time using routine data from the ICU information system, evaluated retrospectively. Digital tools called "Chrono-Apps" will be developed to display rhythmic information and may help clinicians adjust lighting to patient needs.
Detailed description
The investigators will retrospectively analyze periodic oscillations in clinical data, such as heart rate, temperature, blood glucose, insulin, or blood pressure, to identify parameters suitable for characterizing the physiological rhythms in hospitalized Intensive Care Unit (ICU) patients. While these measurements typically show regular daily changes, also called oscillatory patterns, critical illness, continuous monitoring, and frequent medical interventions can disrupt them. The study will investigate whether these patterns can be used to group patients into distinct temporal or rhythmic profiles. The study will also examine whether certain clinical factors are linked to functioning or disrupted oscillatory patterns. These factors include illness severity scores, sedation levels, organ support treatments, and medications. Additionally, the researchers will explore whether temporal disruption is associated with key ICU complications, including delirium, ICU-acquired muscle weakness, and Post-Intensive Care Syndrome (PICS). Finally, in a small cohort of ICU patients, the investigators will test personalized lighting regimens adapted to individual chronotypes. This phase of the study aims to assess the robustness of routine clinical data for tailoring light exposure, validate a circadian entrainment algorithm, and evaluate potential sources of bias. Real-time analyses of clinical data will be visualized as rhythm profiles via digital "Chrono-Apps" integrated into the electronic patient record. These visualizations will support the day-to-day implementation of personalized lighting regimens that adapt dynamically to each patient's current rhythm status and clinical condition.
Interventions
OTHERExposure to routine clinical parameters
These are the primary exposures and are used to detect oscillatory patterns and characterize circadian rhythms. They include heart rate, body temperature, blood pressure, blood glucose, and insulin.
OTHERExposure to ICU clinical factors and treatments
These are secondary exposures that may influence circadian rhythms: illness severity (e.g., Sequential Organ Failure Assessment (SOFA) score), sedation levels, organ support therapies (e.g., ventilation, dialysis, Extracorporeal Membrane Oxygenation (ECMO)), and medications administered during ICU stay (e.g., sedatives, vasopressors, corticosteroids).
OTHERExposure to critical illness-related conditions
These exposures represent complications that may be associated with circadian disruption: delirium, deep sedation, ICU-acquired muscle weakness, and post-intensive care syndrome.
OTHERExposure to molecular and hormonal circadian markers
These exposures reflect biological clock function: clock gene expression (if available in some cases), and melatonin levels.
OTHERExposure to metabolic changes related to critical illness
These exposures represent metabolic consequences of critical illness: insulin sensitivity, muscle atrophy, and critical illness myopathy or ICU-acquired weakness.
Sponsors
Charite University, Berlin, Germany
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
Primary Retrospective Cohort: * Admitted to and treated in a participating Intensive Care Unit (ICU) between 2017 and 2024 * Minimum ICU length of stay of 3 days (≥ 72 hours) * Age ≥ 18 years at the time of ICU admission * All genders (male, female, diverse) Cohorts from previous studies: * Prior enrollment in one of the designated parent study protocols * Availability of supplementary biological or metabolic data (e.g., clock gene expression, melatonin levels) suitable for exploratory association analyses
Exclusion criteria
* None
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Characterization of circadian periodicities and classification of time-varying patterns based on routine clinical data | From ICU admission to ICU discharge or death, whichever comes first (expected average duration of 4 weeks). | Assessment of periodicities and time-varying patterns in routine clinical parameters, including heart rate, body temperature, blood pressure, blood glucose, and insulin levels. Time-series analysis will be conducted to extract continuous metrics (amplitude, period, and phase). Based on these metrics, patients will be classified into distinct categorical groups according to their periodic oscillation profiles. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Association between circadian rhythm category and clinical severity scores | From ICU admission to ICU discharge or death, whichever comes first (expected average duration of 4 weeks). | Relationship between circadian rhythm classification and illness severity (e.g., SOFA score), sedation level, and use of organ support therapies. |
| Association between circadian rhythm disruption and critical illness-related conditions | From ICU admission to ICU discharge or death, whichever comes first (expected average duration of 4 weeks), and post-ICU period (up to 3 and 6 months). | Presence of delirium, ICU-acquired muscle weakness/critical illness myopathy, and PICS in relation to circadian rhythm category. Delirium will be measured with the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) binary scale (Positive/Negative). |
| Association between time-varying clinical patterns and external biological markers (from other studies) | Depending on individual study protocols, from ICU admission through 24 months post-discharge. Sampled daily to weekly during the ICU stay, followed by post-discharge examinations conducted at variable monthly intervals (a maximum of 5 visits). | Exploratory associations between oscillatory trends in routine clinical data and biological markers reported in other studies, such as clock gene expression, melatonin levels, insulin sensitivity, muscle atrophy, and critical illness myopathy. Only associations will be evaluated. |
| Feasibility and Data Infrastructure for Real-Time Circadian Visualization (Chrono-Apps) | From ICU admission to ICU discharge or death, whichever comes first (expected average duration of 4 weeks). | Evaluation of the technical feasibility and data integration requirements for generating real-time circadian visualizations within the Patient Data Management System (PDMS). Feasibility will be assessed based on data completeness, sampling frequency compliance, latency of time-series data streaming from routine ICU monitors, and system stability required to display continuous circadian profiles via Chrono-Apps. |
| Performance of Algorithm-Based Light Therapy Recommendations | From ICU admission to ICU discharge or death, whichever comes first (expected average duration of 4 weeks). | Retrospective evaluation of the accuracy and stability of the time-series analysis designed to estimate circadian phase of routine clinical data (vital signs) and generate individualized lighting schedules. |
Countries
Germany
Outcome results
None listed