Sleep, Hypertension, and Nocturia: a Multicomponent Approach for Comorbid Illnesses
Phase: NA
Conditions: Nocturia, Hypertension, Sleep Disturbance
Sponsor: University of Pittsburgh

Sleep, Hypertension, and Nocturia: Multicomponent Approach for Comorbid 
Illnesses 
University of Pittsburgh STUDY21050132  
NCT05419830 
Protocol Date: September 1, 2021 
 
INTRODUCTION 
Elevated nighttime blood pressure (BP), poor sleep, and nocturia are comorbid, mutually 
exacerbating conditions. Both elevated nighttime systolic blood pressure (SBP), and poor sleep 
disrupt the diurnal pattern of urine excretion by increasing nighttime sodium (natriuresis) and 
water (diuresis) excretion leading to increased nighttime urine production causing nocturia. This 
increased frequency nighttime awakenings with nocturia, in turn, contributes to poor sleep and 
elevated nighttime SBP. We postulate that treatments targeted towards these etiologies will help 
break this vicious cycle. 
 
Traditionally, antihypertensive medications are dosed in the morning targeting daytime BP. 
However, some research suggests that nighttime BP best predicts risk for major cardiovascular 
events. Several clinical trials of bedtime dosing of BP medication–chronotherapy– show better 
nighttime BP control. However, no clinical studies have considered or tested chronotherapy as a 
treatment for nocturia. With respect to poor sleep, we have shown that brief behavioral 
treatment of insomnia (BBTI) significantly improves not only sleep but also self-reported nocturia 
among the elderly. Therefore, we envision a multicomponent approach with chronotherapy 
(bedtime dosing of certain antihypertensives) and behavioral sleep intervention (BBTI) to 
concurrently address the prevalent and chronic, mutually exacerbating conditions: nocturia, poor 
sleep, and hypertension. 
 
STUDY OVERVIEW 
This pilot study will provide critical preliminary data regarding the relation between sleep  
and nighttime BP in seniors In the proposed pilot study 30 community-dwelling older adults 
(aged >65) who take at ≥1 daily non-diuretic antihypertensive medication, have a mean SBP 
>135 mm Hg, and awaken ≥2 times nightly to void will be randomly assigned to one of the 3 
groups of 10 participants each to 1) morning (am) HTN medication dosing, 2) BBTI with am 
HTN medication dosing, 3) nighttime non-diuretic HTN medication dosing (chronotherapy) for 6 
weeks. At baseline and 6 weeks, participants will undergo 48-hour ambulatory BP monitoring, 
in-home sleep study, complete a 3-day bladder diary. Data from this study will provide feasibility 
and pilot data for a subsequent, larger, and more definitive trial. 
 
Outcome measures:  
1) Change in mean sleep time systolic BP dip pre- vs post-intervention- measured by 24-hour 
ambulatory BP monitor (ABPM) 
2) Change in nocturia frequency as determined by 3-day bladder diary 
3) Change in nocturnal polyuria measured by NPi- nocturnal polyuria index=(nocturnal urine  
volume/24-hour volume)*100 
4) Change in global Pittsburgh Sleep Quality Index (PSQI) scores pre- vs post-intervention 
 
Data Analysis:  
In this pilot investigation, we will perform descriptive and graphical analyses as well as 
inferential analyses. As appropriate for a pilot study, we will focus on the magnitude of effects 
rather than on the p-values. 

First, we will compare baseline characteristics between the 3 groups using analysis of variance 
(ANOVA), Kruskal-Wallis, chi-square and Fisher’s exact tests, as appropriate. Any significant 
differences will be used as additional covariates in sensitivity analyses. Second, we will fit a 
series of analysis of covariance (ANCOVA) models using the SAS® GLM procedure with pre- to 
post-intervention change in each continuous outcome as the dependent variable: BBTI (yes/no), 
chronotherapy (yes/no) and baseline value of outcome as independent variables. Third, we will 
construct means contrasts appropriate for testing the hypotheses. Magnitude of the estimate 
and/or its statistical significance of: BBTI vs usual care and chronotherapy vs usual care 
contrasts will be interpreted as a test of hypothesis 1.1. Finally, we will add changes in 
measures of sleep (decrease in WASO) and % of deep sleep to the above model as an 
additional independent variable and notice the reduction in magnitude of the above means 
contrasts.