Literature DB >> 21897772

Factors that may influence the classification of sleep-wake by wrist actigraphy: the MrOS Sleep Study.

Terri Blackwell1, Sonia Ancoli-Israel, Susan Redline, Katie L Stone.   

Abstract

STUDY
OBJECTIVES: Total sleep time (TST), sleep efficiency (SE), sleep latency (SOL) and wake after sleep onset (WASO) assessed by actigraphy gathered in 3 different modes were compared to polysomnography (PSG) measurements to determine which mode corresponded highest to PSG. Associations of measurement error for TST (PSG-actigraphy) with demographics, medical history, exam data, and sleep characteristics were examined.
METHODS: Participants underwent in-home 12-channel PSG. Actigraphy data were collected in 3 modes: proportional integration mode (PIM), time above threshold (TAT) and zero crossings mode (ZCM). The analysis cohort was a subgroup of 889 men (mean age 76.4 years) from the MrOS Sleep Study with concurrently measured PSG and actigraphy. Intraclass correlation coefficients (ICCs) were used to compare the association between PSG and actigraphy.
RESULTS: The PIM mode of actigraphy corresponded moderately to PSG for all measures (ICCs 0.32 to 0.57), TAT a little lower (ICCs 0.17 to 0.47), and ZCM lower still (ICCs 0.16 to 0.33). The PIM mode corresponded best to PSG (ICCs TST 0.57; SE 0.46; SOL 0.23; WASO 0.54), though the estimations from PSG and PIM mode differed significantly (p < 0.01). The PIM mode overestimated TST by 13.2 min on average, but underestimated TST for those in certain subgroups: those with excessive daytime sleepiness, less sleep fragmentation, or more sleep disordered breathing (p < 0.05).
CONCLUSIONS: Sleep parameters from the PIM and TAT modes of actigraphy corresponded reasonably well to PSG in this population, with the PIM mode correlating highest. Systematic measurement error was observed within subgroups with different sleep characteristics.

Entities:  

Keywords:  Actigraphy; polysomnography; sleep efficiency; total sleep time; validation

Mesh:

Year:  2011        PMID: 21897772      PMCID: PMC3161768          DOI: 10.5664/JCSM.1190

Source DB:  PubMed          Journal:  J Clin Sleep Med        ISSN: 1550-9389            Impact factor:   4.062


  37 in total

1.  Sleep estimation from wrist movement quantified by different actigraphic modalities.

Authors:  G Jean-Louis; D F Kripke; W J Mason; J A Elliott; S D Youngstedt
Journal:  J Neurosci Methods       Date:  2001-02-15       Impact factor: 2.390

2.  Sleep detection with an accelerometer actigraph: comparisons with polysomnography.

Authors:  G Jean-Louis; D F Kripke; R J Cole; J D Assmus; R D Langer
Journal:  Physiol Behav       Date:  2001-01

3.  Further validation of actigraphy for sleep studies.

Authors:  Luciane de Souza; Ana Amélia Benedito-Silva; Maria Laura Nogueira Pires; Dalva Poyares; Sergio Tufik; Helena Maria Calil
Journal:  Sleep       Date:  2003-02-01       Impact factor: 5.849

4.  The Modified Mini-Mental State (3MS) examination.

Authors:  E L Teng; H C Chui
Journal:  J Clin Psychiatry       Date:  1987-08       Impact factor: 4.384

5.  The Supplement on Aging to the 1984 National Health Interview Survey.

Authors:  J E Fitti; M G Kovar
Journal:  Vital Health Stat 1       Date:  1987-06

6.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

7.  Wrist-actigraphic estimation of sleep time.

Authors:  D J Mullaney; D F Kripke; S Messin
Journal:  Sleep       Date:  1980       Impact factor: 5.849

8.  Actigraphy in the assessment of insomnia.

Authors:  Annie Vallières; Charles M Morin
Journal:  Sleep       Date:  2003-11-01       Impact factor: 5.849

9.  Assessment of patient satisfaction in activities of daily living using a modified Stanford Health Assessment Questionnaire.

Authors:  T Pincus; J A Summey; S A Soraci; K A Wallston; N P Hummon
Journal:  Arthritis Rheum       Date:  1983-11

Review 10.  The role of actigraphy in the study of sleep and circadian rhythms.

Authors:  Sonia Ancoli-Israel; Roger Cole; Cathy Alessi; Mark Chambers; William Moorcroft; Charles P Pollak
Journal:  Sleep       Date:  2003-05-01       Impact factor: 5.849

View more
  45 in total

1.  Assessment of sleep in the National Social Life, Health, and Aging Project.

Authors:  Diane S Lauderdale; L Philip Schumm; Lianne M Kurina; Martha McClintock; Ronald A Thisted; Jen-Hao Chen; Linda Waite
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2014-11       Impact factor: 4.077

2.  Are We There Yet? Getting Closer to Certainty in Idiopathic Hypersomnia Diagnosis.

Authors:  Lynn Marie Trotti
Journal:  J Clin Sleep Med       Date:  2019-04-15       Impact factor: 4.062

3.  Natural sleep and its seasonal variations in three pre-industrial societies.

Authors:  Gandhi Yetish; Hillard Kaplan; Michael Gurven; Brian Wood; Herman Pontzer; Paul R Manger; Charles Wilson; Ronald McGregor; Jerome M Siegel
Journal:  Curr Biol       Date:  2015-10-17       Impact factor: 10.834

4.  Circadian rest-activity rhythms predict future increases in depressive symptoms among community-dwelling older men.

Authors:  Stephen F Smagula; Sonia Ancoli-Israel; Terri Blackwell; Robert Boudreau; Marcia L Stefanick; Misti L Paudel; Katie L Stone; Jane A Cauley
Journal:  Am J Geriatr Psychiatry       Date:  2014-06-26       Impact factor: 4.105

5.  A comparison of radio-frequency biomotion sensors and actigraphy versus polysomnography for the assessment of sleep in normal subjects.

Authors:  Emer O'Hare; David Flanagan; Thomas Penzel; Carmen Garcia; Daniela Frohberg; Conor Heneghan
Journal:  Sleep Breath       Date:  2014-03-11       Impact factor: 2.816

Review 6.  Sleep and Fatigue in IBD: an Unrecognized but Important Extra-intestinal Manifestation.

Authors:  Andrew Canakis; Taha Qazi
Journal:  Curr Gastroenterol Rep       Date:  2020-01-30

7.  Discrepancy between wrist-actigraph and polysomnographic measures of sleep in patients with stable heart failure and a novel approach to evaluating discrepancy.

Authors:  Sangchoon Jeon; Samantha Conley; Nancy S Redeker
Journal:  J Sleep Res       Date:  2018-06-25       Impact factor: 3.981

8.  Cross-sectional and Prospective Associations of Rest-Activity Rhythms With Metabolic Markers and Type 2 Diabetes in Older Men.

Authors:  Qian Xiao; Jingyi Qian; Daniel S Evans; Susan Redline; Nancy E Lane; Sonia Ancoli-Israel; Frank A J L Scheer; Katie Stone
Journal:  Diabetes Care       Date:  2020-09-04       Impact factor: 19.112

9.  Sleep Architecture and Mental Health Among Community-Dwelling Older Men.

Authors:  Stephen F Smagula; Charles F Reynolds; Sonia Ancoli-Israel; Elizabeth Barrett-Connor; Thuy-Tien Dam; Jan M Hughes-Austin; Misti Paudel; Susan Redline; Katie L Stone; Jane A Cauley
Journal:  J Gerontol B Psychol Sci Soc Sci       Date:  2013-12-10       Impact factor: 4.077

10.  Common genetic variants in ARNTL and NPAS2 and at chromosome 12p13 are associated with objectively measured sleep traits in the elderly.

Authors:  Daniel S Evans; Neeta Parimi; Caroline M Nievergelt; Terri Blackwell; Susan Redline; Sonia Ancoli-Israel; Eric S Orwoll; Steven R Cummings; Katie L Stone; Gregory J Tranah
Journal:  Sleep       Date:  2013-03-01       Impact factor: 5.849

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.