Background: Ambulatory blood pressure monitoring (ABPM) is considered the gold standard for assessing blood pressure; however, its use may potentially disrupt sleep. Previous studies have produced mixed results on the impact of ABPM on sleep parameters and used actigraphy as the evaluating tool. To date, no studies have investigated the effects of ABPM on sleep parameters evaluated through polysomnography.
Purpose: This study aimed to examine the effects of ABPM on objectively assessed sleep parameters.
Methods: We evaluated five women and five men (age: 38.0 ± 15.0 years; BMI: 27.0 ± 3.5 kg/m²) using full polysomnography over two nights in a sleep laboratory-one night with ABPM and one night without it, with nocturnal assessments every 30 min. The order of the conditions was randomized, with intervals between nights ranging from 3 to 10 days.
Results: N2 sleep was significantly longer during the night with ABPM compared to the night without it (66.4 ± 12.4% vs. 57.7 ± 11.3%, p < 0.003). Conversely, the apnea-hypopnea index was higher on the night without ABPM (13.1 ± 21.2 vs. 10.5 ± 19.8 events/hour, p < 0.005). Participants did not rate the night with ABPM as worse than the night without, and no significant differences were observed in total sleep time, sleep latency, sleep efficiency, number of awakenings, or time awake after sleep onset.
Conclusions: ABPM does not appear to adversely affect significant objective sleep parameters or subjective evaluations of sleep quality.
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http://dx.doi.org/10.1007/s11325-024-03181-3 | DOI Listing |
J Therm Biol
December 2024
Laboratory of Sport, Expertise and Performance (EA 7370), French National Institute of Sport (INSEP), Paris, France. Electronic address:
Introduction: The relationship between blood distribution, body temperature, and sleep/wakefulness states is still unclear. The aim of the present study is to systematically review the potential beneficial effects of bedding strategies (e.g.
View Article and Find Full Text PDFBMC Med Res Methodol
December 2024
Division of Biostatistics, Department of Population Health, New York University Grossman School of Medicine, 180 Madison Avenue, New York, NY, USA.
Background: In cohort studies with time-to-event outcomes, covariates of interest often have values that change over time. The classical Cox regression model can handle time-dependent covariates but assumes linear effects on the log hazard function, which can be limiting in practice. Furthermore, when multiple correlated covariates are studied, it is of great interest to model their joint effects by allowing a flexible functional form and to delineate their relative contributions to survival risk.
View Article and Find Full Text PDFSleep Med
December 2024
Otto-von-guerricke-university Magdeburg, Medical Faculty, Clinic of Pneumology, leipziger straße 44, 39120, Magdeburg, Germany.
Objective/background: Obstructive sleep apnea (OSA) is a common disease, which poses a significant health threat. Initial diagnostics with polygraphy or polysomnography are time consuming and expensive. Therefore, there is an unmet medical need for simplification, especially to exclude healthy patients from elaborate and unnecessary diagnostics.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Sleep Medicine Center, Taipei Veterans General Hospital, Taipei, Taiwan.
Background: Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by frequent pauses or shallow breathing during sleep. Polysomnography, the gold standard for OSA assessment, is time consuming and labor intensive, thus limiting diagnostic efficiency.
Objective: This study aims to develop 2 sequential machine learning models to efficiently screen and differentiate OSA.
Rev Bras Epidemiol
December 2024
Universidade do Vale do Rio dos Sinos, Postgraduate Programme in Collective Health - São Leopoldo (RS), Brazil.
Objective: To explore the relationship between different patterns of multimorbidity and the use of sleeping medications in women.
Methods: Population-based cross-sectional study with 1,128 women (aged 20-69 years) in Southern Brazil. Data on sleeping medications were obtained from the question "Do you take/use any medication to be able to sleep?" and identified by the Anatomical Therapeutic and Chemical classification.
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