Bharati Prasad1,2,3, Sarah Usmani1, Alana D Steffen4, Hans P A Van Dongen5, Francis M Pack6, Inna Strakovsky6, Bethany Staley6, David Dinges6,7, Greg Maislin6, Allan I Pack6, Terri E Weaver1,2,8. 1. Section of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, IL. 2. Center for Narcolepsy, Sleep and Health Research, College of Nursing, University of Illinois at Chicago. 3. Jesse Brown VA Medical Center, Chicago, IL. 4. Department of Health System Science, College of Nursing, University of Illinois at Chicago. 5. Sleep and Performance Research Center, Washington State University, Spokane, WA. 6. Center for Sleep and Circadian Neurobiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. 7. Unit for Experimental Psychiatry, Division of Sleep and Chronobiology, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. 8. Department of Biobehavioral Health Science, College of Nursing, University of Illinois at Chicago, Chicago, IL.
Abstract
STUDY OBJECTIVES: Apnea-hypopnea index (AHI) is the primary measure used to confirm a diagnosis of obstructive sleep apnea (OSA). However, there may be significant night-to-night variability (NNV) in AHI, limiting the value of AHI in clinical decision-making related to OSA management. We examined short-term NNV in AHI and its predictors during home portable monitoring (PM). METHODS: Single center prospective observational study of patients (n = 84) with newly diagnosed OSA by polysomnography (PSG) AHI ≥ 5/h. All participants underwent 2 to 8 consecutive nights of PM. RESULTS: Participants (n = 84) were middle-aged (47 ± 8.3 y, mean ± standard deviation; SD), including 28 women, with mean AHI on baseline PSG (AHIPSG) of 30.1 ± 31.8. Mean AHI on PM (AHIPM) was 27.4 ± 23.7. Intraclass correlation coefficient (ICC) for AHIPM in the entire sample was 0.73 (95% CI 0.66-0.8), indicating that 27% of the variability in AHIPM was due to intra-individual factors. Mild severity of OSA, defined by AHIPSG 5-15/h, was associated with higher NNV (likelihood ratio, -0.4 ± 0.14; p = 0.006) and absence of comorbidity showed a trend towards higher NNV (-0.54 ± 0.27, p = 0.05) on AHIPM. CONCLUSIONS: The intraindividual short-term NNV in AHIPM is higher in mild versus moderately severe OSA, even in the home setting, where first-night effect is not expected. Larger studies of NNV focused on patients with mild OSA are needed to identify characteristics that predict need and timing for repeated diagnostic testing and treatment. COMMENTARY: A commentary on this article appears in this issue on page 787.
STUDY OBJECTIVES:Apnea-hypopnea index (AHI) is the primary measure used to confirm a diagnosis of obstructive sleep apnea (OSA). However, there may be significant night-to-night variability (NNV) in AHI, limiting the value of AHI in clinical decision-making related to OSA management. We examined short-term NNV in AHI and its predictors during home portable monitoring (PM). METHODS: Single center prospective observational study of patients (n = 84) with newly diagnosed OSA by polysomnography (PSG) AHI ≥ 5/h. All participants underwent 2 to 8 consecutive nights of PM. RESULTS:Participants (n = 84) were middle-aged (47 ± 8.3 y, mean ± standard deviation; SD), including 28 women, with mean AHI on baseline PSG (AHIPSG) of 30.1 ± 31.8. Mean AHI on PM (AHIPM) was 27.4 ± 23.7. Intraclass correlation coefficient (ICC) for AHIPM in the entire sample was 0.73 (95% CI 0.66-0.8), indicating that 27% of the variability in AHIPM was due to intra-individual factors. Mild severity of OSA, defined by AHIPSG 5-15/h, was associated with higher NNV (likelihood ratio, -0.4 ± 0.14; p = 0.006) and absence of comorbidity showed a trend towards higher NNV (-0.54 ± 0.27, p = 0.05) on AHIPM. CONCLUSIONS: The intraindividual short-term NNV in AHIPM is higher in mild versus moderately severe OSA, even in the home setting, where first-night effect is not expected. Larger studies of NNV focused on patients with mild OSA are needed to identify characteristics that predict need and timing for repeated diagnostic testing and treatment. COMMENTARY: A commentary on this article appears in this issue on page 787.
Authors: P R Stanforth; J Gagnon; T Rice; C Bouchard; A S Leon; D C Rao; J S Skinner; J H Wilmore Journal: Ann Epidemiol Date: 2000-07 Impact factor: 3.797
Authors: Terri E Weaver; Cristina Mancini; Greg Maislin; Jacqueline Cater; Bethany Staley; J Richard Landis; Kathleen A Ferguson; Charles F P George; David A Schulman; Harly Greenberg; David M Rapoport; Joyce A Walsleben; Teofilo Lee-Chiong; Indira Gurubhagavatula; Samuel T Kuna Journal: Am J Respir Crit Care Med Date: 2012-07-26 Impact factor: 21.405
Authors: Armin Steffen; Julia T Hartmann; Inke R König; Madeline J L Ravesloot; Benedikt Hofauer; Clemens Heiser Journal: Sleep Breath Date: 2018-09-05 Impact factor: 2.816
Authors: Jennifer N Miller; Paula Schulz; Bunny Pozehl; Douglas Fiedler; Alissa Fial; Ann M Berger Journal: Sleep Breath Date: 2017-11-14 Impact factor: 2.816