Multicenter Study on Sleep and Circadian Alterations as Objective Markers of Mild Cognitive Impairment and Alzheimer's Disease Reveals Sex Differences.
Alzheimer’s disease
circadian rhythms
confusion matrix
mild cognitive impairment
sex differences
sleep disturbances
sleep parameters
sleep regularity index
wearable activity tracker
Journal
Journal of Alzheimer's disease : JAD
ISSN: 1875-8908
Titre abrégé: J Alzheimers Dis
Pays: Netherlands
ID NLM: 9814863
Informations de publication
Date de publication:
2020
2020
Historique:
pubmed:
14
11
2020
medline:
30
9
2021
entrez:
13
11
2020
Statut:
ppublish
Résumé
Circadian and sleep disturbances are associated with increased risk of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Wearable activity trackers could provide a new approach in diagnosis and prevention. To evaluate sleep and circadian rhythm parameters, through wearable activity trackers, in MCI and AD patients as compared to controls, focusing on sex dissimilarities. Based on minute level data from consumer wearable devices, we analyzed actigraphic sleep parameters by applying an electromedical type I registered algorithm, and the corresponding circadian variables in 158 subjects: 86 females and 72 males (42 AD, 28 MCI, and 88 controls). Moreover, we used a confusion-matrix chart method to assess accuracy, precision, sensitivity, and specificity of two decision-tree models based on actigraphic data in predicting disease or health status. Wake after sleep onset (WASO) was higher (p < 0.001) and sleep efficiency (SE) lower (p = 0.003) in MCI, and Sleep Regularity Index (SRI) was lower in AD patients compared to controls (p = 0.004). SE was lower in male AD compared to female AD (p = 0.038) and SRI lower in male AD compared to male controls (p = 0.008), male MCI (p = 0.047), but also female AD subjects (p = 0.046). Mesor was significantly lower in males in the overall population. Age reduced the dissimilarities for WASO and SE but demonstrated sex differences for amplitude (p = 0.009) in the overall population, controls (p = 0.005), and AD subjects (p = 0.034). The confusion-matrices showed good predictive power of actigraphic data. Actigraphic data could help identify disease or health status. Sex (possibly gender) differences could impact on neurodegeneration and disease trajectory with potential clinical applications.
Sections du résumé
BACKGROUND
Circadian and sleep disturbances are associated with increased risk of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Wearable activity trackers could provide a new approach in diagnosis and prevention.
OBJECTIVE
To evaluate sleep and circadian rhythm parameters, through wearable activity trackers, in MCI and AD patients as compared to controls, focusing on sex dissimilarities.
METHODS
Based on minute level data from consumer wearable devices, we analyzed actigraphic sleep parameters by applying an electromedical type I registered algorithm, and the corresponding circadian variables in 158 subjects: 86 females and 72 males (42 AD, 28 MCI, and 88 controls). Moreover, we used a confusion-matrix chart method to assess accuracy, precision, sensitivity, and specificity of two decision-tree models based on actigraphic data in predicting disease or health status.
RESULTS
Wake after sleep onset (WASO) was higher (p < 0.001) and sleep efficiency (SE) lower (p = 0.003) in MCI, and Sleep Regularity Index (SRI) was lower in AD patients compared to controls (p = 0.004). SE was lower in male AD compared to female AD (p = 0.038) and SRI lower in male AD compared to male controls (p = 0.008), male MCI (p = 0.047), but also female AD subjects (p = 0.046). Mesor was significantly lower in males in the overall population. Age reduced the dissimilarities for WASO and SE but demonstrated sex differences for amplitude (p = 0.009) in the overall population, controls (p = 0.005), and AD subjects (p = 0.034). The confusion-matrices showed good predictive power of actigraphic data.
CONCLUSION
Actigraphic data could help identify disease or health status. Sex (possibly gender) differences could impact on neurodegeneration and disease trajectory with potential clinical applications.
Identifiants
pubmed: 33185597
pii: JAD200632
doi: 10.3233/JAD-200632
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM