Wohlgemuth William K, Chirinos Diana A, Domingo Samantha, Wallace Douglas M
Sleep Disorders Center, Bruce W. Carter VA Medical Center, Miami, FL, USA.
Psychology, University of Miami, Coral Gables, FL, USA.
Sleep Med. 2015 Mar;16(3):336-42. doi: 10.1016/j.sleep.2014.08.013. Epub 2014 Sep 17.
To examine whether subtypes of continuous positive airway pressure (CPAP) user profiles could be identified, and to determine predictors of CPAP subgroup membership.
A retrospective, correlational approach was used. Subjects attended clinic where a CPAP download was performed and questionnaires were completed. Additional information was obtained from the electronic medical record.
Miami VA Sleep Clinic.
Obstructive sleep apnea patients (N = 207).
Three adherence variables comprised the profile: % of nights of CPAP use, % of nights of CPAP use > 4 hours and average nightly use in minutes. Predictors included age, AHI, time since CPAP therapy was initiated, CPAP pressure, residual AHI, BMI, social-cognitive variables, insomnia, sleepiness, and psychiatric and medical comorbidities.
Latent profile analysis was used to identify CPAP user profiles. Three subgroups were identified and labeled "Non-Adherers," "Attempters," and "Adherers". Non-Adherers (37.6% of the sample) used CPAP for an average of 37 minutes nightly, used CPAP 18.2% of nights and used CPAP > 4 hour 6.2 % of nights. Attempters (32.9%) used CPAP for 156 minutes on average, used CPAP 68.2% of nights and used CPAP > 4 hour 29.3% of nights. Adherers (29.5%) used CPAP for 392 minutes, used CPAP 95.4% of nights and used CPAP >4 hour 86.2% of nights. Self-efficacy, insomnia, AHI, time since CPAP was initiated, and CPAP pressure predicted CPAP subgroup membership.
Sixty-seven percent of users (Non-Adherers, Attempters) had suboptimal adherence. Understanding CPAP use profiles and their predictors enable identification of those who may require additional intervention to improve adherence.
探讨是否能够识别持续气道正压通气(CPAP)使用者的不同类型,并确定CPAP亚组成员的预测因素。
采用回顾性、相关性研究方法。受试者到诊所进行CPAP数据下载并完成问卷调查。从电子病历中获取其他信息。
迈阿密退伍军人事务部睡眠诊所。
阻塞性睡眠呼吸暂停患者(N = 207)。
三个依从性变量构成了该类型:CPAP使用天数的百分比、CPAP使用时间>4小时的天数百分比以及每晚平均使用分钟数。预测因素包括年龄、呼吸暂停低通气指数(AHI)、开始CPAP治疗后的时间、CPAP压力、残余AHI、体重指数(BMI)、社会认知变量、失眠、嗜睡以及精神和内科合并症。
采用潜在类别分析来识别CPAP使用者类型。确定了三个亚组,分别标记为“不依从者”、“尝试者”和“依从者”。不依从者(占样本的37.6%)每晚平均使用CPAP 37分钟,使用CPAP的天数占18.2%,使用CPAP>4小时的天数占6.2%。尝试者(32.9%)平均使用CPAP 156分钟,使用CPAP的天数占68.2%,使用CPAP>4小时的天数占29.3%。依从者(29.5%)使用CPAP 392分钟,使用CPAP的天数占95.4%,使用CPAP>4小时的天数占86.2%。自我效能感、失眠、AHI、开始CPAP治疗后的时间以及CPAP压力可预测CPAP亚组成员身份。
67%的使用者(不依从者、尝试者)依从性欠佳。了解CPAP使用类型及其预测因素有助于识别那些可能需要额外干预以提高依从性的患者。