Sleep Measurement Study

NCT ID: NCT04288557

Last Updated: 2021-05-05

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 31 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2020-01-23
• Study Completion Date: 2021-02-28

Brief Summary

Sleep behaviour has critical importance to health and wellbeing. A large body of evidence has implicated poor sleep in all-cause mortality, and in cardiovascular and cardiometabolic risk factors. Given the importance of sleep to health, the importance of accurately monitoring sleep duration and quality is becoming more evident. Polysomnography (PSG) is considered the gold standard for sleep assessment. Nevertheless, PSG is impractical, expensive and labour-intensive. Another method to quantify indices of sleep is based on actigraphic measures. Wrist worn actigraphy devices provide an indirect measure of sleep parameters e.g. total sleep time, sleep onset latency and waking time. However, the data is in the form of manufacturer-specific activity 'counts', making it difficult to compare the data with different accelerometer brands. Recently wrist-worn accelerometers have become increasingly used for objective measurement of physical activity in large population studies where participants are often asked to wear them for 24 hours continuously. These devices therefore collect data that could be used to estimate sleep parameters, and now there is a sleep algorithm that can be applied to raw data from accelerometers. The three widely used raw-data accelerometer brands are the Axivity, ActiGraph and GENEActiv and ActivPAL which is a thigh-worn accelerometer that provides a measure of posture. Studies that examined accuracy of estimating sleep parameters from different brands of accelerometers compared to PSG have reported conflicting results which could be due to the use of different sleep algorithms and accelerometer placement (dominant vs. non-dominant wrist vs. hip). Therefore this study will aim to validate automated sleep algorithms for research grade accelerometers against PSG in a clinical and healthy adult population.

Detailed Description

Sleep behaviour has critical importance to health and wellbeing. Insufficient sleep duration and poor sleep quality are independent contributors to high blood pressure and cardiovascular disease, depression, obesity and diabetes. Given the importance of sleep duration and quality to health, the importance of accurately monitoring sleep duration and quality in everyday clinical practice is becoming more evident.

The 'gold standard' physiological measure of sleep is sleep polysomnography (PSG). PSG is used to quantify measures of sleep, including length of sleep, time taken to fall asleep, sleep efficiency. The disadvantages of sleep PSG include the need to attend a laboratory, use of expensive equipment, specialised staff to administer PSG, and to score and interpret the PSG outputs, which limit its use in larger, or free-living studies.

Another method to quantify indices of sleep is based on actigraphy, demonstrating 90% agreement with polysomnography. Wrist actigraphy allows sleep assessment over several days and measures daily sleep-wake cycles. However, the data is in the form of manufacturer-specific activity 'counts' over a specific time window, making it difficult to compare the data with different accelerometer brands. Recently wrist-worn accelerometers have become increasingly used for objective measurement of physical activity in large population studies where participants are often asked to wear them for 24 hours continuously, to maximise compliance. These devices therefore collect data that could be used to estimate sleep parameters, however to be able to use, pool or compare these data there is a need for sleep algorithms that can be applied to datasets from different accelerometer brands. The latest generation of accelerometers measure acceleration in universal units improving comparability among different brands of accelerometers and allowing more control in the data processing. Moreover, now there is a sleep detection algorithm that can applied to data from different raw-data accelerometer brands and is freely available as a part of GGIR package in R (software environment for statistical computing and graphics). The three widely used raw-data accelerometer brands are the Axivity, ActiGraph and GENEActiv and ActivPAL which is a thigh-worn accelerometer that provides a measure of posture using proprietary algorithms; however, raw data are now available.

Studies that have validated the accelerometers with the PSG produced mixed results which can be attributed to use of manufacturer specific sleep algorithms and different accelerometer placement (dominant vs. non-dominant wrist vs. hip). Therefore validation of a sleep algorithm that can be applied to different accelerometer brands against PSG warrants investigation.

Conditions

Sleep

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Sleep clinic patients

All adult patients, from 18 years and up to and including 65 years of age, on the waiting list for overnight polysomnography (PSG) recording at Leicester General Hospital.

No interventions assigned to this group

Healthy volunteers

All adults, from 18 and up to and including 65 years of age without a known sleep disorder.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

Clinical population:

1. Participants willing and able to give informed consent for participation in the study

2. Male or Female

3. Aged 18-65 years inclusive

4. Patients on the waiting list for overnight PSG recording at Leicester General Hospital Healthy volunteers

1. Participants willing and able to give informed consent for participation in the study 2. Male or Female 3. Aged 18-65 years inclusive 4. No known sleep disorder (This will be self-reported by the participants)

Exclusion Criteria

1. Participant is unwilling or unable to give informed consent

2. Anyone without a good command of the English language

3. Anyone <18 years of age and >65 years of age

4. Patients suspected of having a movement disorder in sleep (e.g. Periodic Limb Movement in Sleep or REM-Sleep Behaviour Disorder).

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 65 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

University of Leicester

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Charlotte Edwardson

Role: STUDY_DIRECTOR

University of Leicester

Andrew Hall

Role: PRINCIPAL_INVESTIGATOR

University Hospitals, Leicester

Locations

Leicester Diabetes Centre

Leicester, , United Kingdom

Countries

United Kingdom

Other Identifiers

0713

Identifier Type: -

Identifier Source: org_study_id