Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05742360 |
Other study ID # |
2022H0323 |
Secondary ID |
|
Status |
Recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
February 7, 2023 |
Est. completion date |
March 1, 2028 |
Study information
Verified date |
April 2024 |
Source |
Ohio State University |
Contact |
Alicia Gonzalez Zacarias, MD |
Phone |
6143662361 |
Email |
alicia.gonzalezzacarias[@]osumc.edu |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational
|
Clinical Trial Summary
The primary objective of this study is to determine the longer-term (6 months) effect of CPAP
therapy on change in 24-hour mean blood pressure (24hMBP) in OSA subjects with the
excessively sleepy symptom subtype.
Description:
This is a prospective, non-randomized, observational, two-center study involving newly
diagnosed subjects with moderate-severe OSA with the excessively sleepy symptom subtype.
Variables of Interest: Change in 24-hour ambulatory BP, change in sitting BP, change in
reaction time by psychomotor vigilance test (PVT)
Participants will complete questionnaires that pertain to demographics, lifestyle factors,
and co-morbidities. The blood samples will be used to determine levels of BP medications and
serum creatinine. Measurements will be collected at baseline and at 6-month follow-up visits.
Data Analysis Approach: To correct for potential bias in the non-randomized comparison, the
investigators will apply a Propensity Score (PS) Design via subclassification. Models to
derive the PS values used in this design will include a number of covariates relevant to CPAP
adherence, including age, sex, obesity (BMI, neck circumference, waist-to-hip ratio), current
smoking, history of hypertension, diabetes mellitus (history, medications), lipid profile,
hyperlipidemia (history, medications), family history of premature coronary disease, Charlson
comorbidity index, physical activity (IPAQ), diet, OSA severity (AHI, ODI4, T90), sleepiness
(Epworth Sleepiness Scale), educational attainment, socioeconomic status (postcode), insomnia
symptoms (Insomnia Symptom Questionnaire), anxiety and depression-related symptoms (Patient
Health Questionnaire-2), self-efficacy (General self-efficacy scale), and medication
adherence (Medication Adherence Report Scale [MARS-5]). Baseline values of outcome measures
will also be included in the PS model. After creating the PS design, all analyses are
performed accounting for PS subclass as a categorical stratification factor. Evaluations of
the CPAP effect on binary outcomes are performed utilizing conditional logistic regression.
Similarly, CPAP effects in the context of survival analyses (e.g., Cox Proportional Hazards
models) or on continuous outcomes (e.g., linear regression) are assessed by including PS
subclass as a categorical covariate in all models.