BACKGROUND:CPAP is considered to be the cornerstone of therapy for obstructive sleep apnea. However, adherence to this treatment is frequently poor, which may lead to ongoing symptoms, including daytime sleepiness and poor cognitive function. We aimed to determine the efficacy of showing patients their raw graphic polysomnography (PSG) data in increasing their CPAP adherence. METHODS: The subjects were patients with obstructive sleep apnea (n = 37, diagnosed on prior PSG), who were prospectively randomized into an experimental arm or a control arm. The patients in the experimental arm (n = 18) were shown detailed PSG data, including graphic data from PSG prior to prescription of CPAP. The patients in the control arm (n = 19) were shown the non-graphic paper report of the PSG. Adherence data, collected using CPAP devices with internal microprocessors (adherence cards), was read at 4 weeks after treatment initiation. RESULTS: There was no difference in age (57.3 ± 11.8 y vs 55.5 ± 11.6 y, P = .64), body mass index (BMI) (32.7 ± 6.3 kg/m(2) vs 32.3 ± 6.6 kg/m(2), P = .85), and apnea-hypopnea index (36.0 ± 27.8 events/h vs 30.5 ± 19.1 events/h, P = .48) between the experimental and control arms. There was no difference in percent of days CPAP was used (58% vs 64%, P = .59) and average number of hours each night CPAP was used (3.9 ± 2.1 h vs 4.1 ± 2.5 h, P = .76) between the experimental and control arms, respectively. In multi logistic regression models, which included age, BMI > 30 kg/m(2), apnea-hypopnea index, and experimental intervention, only BMI was found to increase likelihood of improved adherence (odds ratio = 13.3, P = .007). CONCLUSIONS: Showing patients raw graphic PSG data does not seem to improve adherence to CPAP. BMI is a very strong predictor of CPAP adherence.
RCT Entities:
BACKGROUND:CPAP is considered to be the cornerstone of therapy for obstructive sleep apnea. However, adherence to this treatment is frequently poor, which may lead to ongoing symptoms, including daytime sleepiness and poor cognitive function. We aimed to determine the efficacy of showing patients their raw graphic polysomnography (PSG) data in increasing their CPAP adherence. METHODS: The subjects were patients with obstructive sleep apnea (n = 37, diagnosed on prior PSG), who were prospectively randomized into an experimental arm or a control arm. The patients in the experimental arm (n = 18) were shown detailed PSG data, including graphic data from PSG prior to prescription of CPAP. The patients in the control arm (n = 19) were shown the non-graphic paper report of the PSG. Adherence data, collected using CPAP devices with internal microprocessors (adherence cards), was read at 4 weeks after treatment initiation. RESULTS: There was no difference in age (57.3 ± 11.8 y vs 55.5 ± 11.6 y, P = .64), body mass index (BMI) (32.7 ± 6.3 kg/m(2) vs 32.3 ± 6.6 kg/m(2), P = .85), and apnea-hypopnea index (36.0 ± 27.8 events/h vs 30.5 ± 19.1 events/h, P = .48) between the experimental and control arms. There was no difference in percent of days CPAP was used (58% vs 64%, P = .59) and average number of hours each night CPAP was used (3.9 ± 2.1 h vs 4.1 ± 2.5 h, P = .76) between the experimental and control arms, respectively. In multi logistic regression models, which included age, BMI > 30 kg/m(2), apnea-hypopnea index, and experimental intervention, only BMI was found to increase likelihood of improved adherence (odds ratio = 13.3, P = .007). CONCLUSIONS: Showing patients raw graphic PSG data does not seem to improve adherence to CPAP. BMI is a very strong predictor of CPAP adherence.