Pre- and in-therapy predictive score models of adult OSAS patients with poor adherence pattern on nCPAP therapy

被引:7
作者
Wang, Yeying [1 ,2 ]
Geater, Alan F. [3 ]
Chai, Yanling [1 ]
Luo, Jiahong [2 ]
Niu, Xiaoqun [1 ]
Hai, Bing [1 ]
Qin, Jingting [1 ]
Li, Yongxia [1 ]
机构
[1] Kunming Med Univ, Affiliated Hosp 2, Dept Resp Med, Kunming 650101, Yunnan, Peoples R China
[2] Kunming Med Univ, Sch Publ Hlth, Dept Epidemiol & Biostat, Kunming 650101, Yunnan, Peoples R China
[3] Prince Songkla Univ, Fac Med, Epidemiol Unit, Hat Yai, Songkhla, Thailand
基金
中国国家自然科学基金;
关键词
OSAS; adherence; nCPAP; predictive model; K-means cluster analysis; bootstrap analysis; POSITIVE AIRWAY PRESSURE; OBSTRUCTIVE SLEEP-APNEA; LONG-TERM COMPLIANCE; CPAP USE; DAYTIME SLEEPINESS; SOCIOECONOMIC-STATUS; DEPRESSIVE SYMPTOMS; CANCER-PATIENTS; RISK-FACTOR; PREVALENCE;
D O I
10.2147/PPA.S83105
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objectives: To identify patterns of adherence to nasal continuous positive airway pressure (nCPAP) use in the first 3 months of therapy among newly diagnosed adult patients with obstructive sleep apnea/hypopnea syndrome (OSAS) and their predictors. To develop pretherapy and in-therapy scores to predict adherence pattern. Methods: Newly diagnosed adult OSAS patients were consecutively recruited from March to August 2013. Baseline clinical information and measures such as Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), Zung's Self-Rating Depression Scale (SDS), and The Pittsburgh Sleep Quality Index (PSQI) at baseline and at the end of 3rd-week therapy were collected. Twelve weeks' adherence data were collected from the nCPAP memory card, and K-means cluster analysis was used to explore adherence patterns. Predictive scores were developed from the coefficients of cumulative logit models of adherence patterns using variables available at baseline and after 3 weeks of therapy. Performance of the score was validated using 500 bootstrap resamples. Results: Seventy six patients completed a 12-week follow-up. Three patterns were revealed. Patients were identified as developing an adherence pattern that was poor (n=14, mean +/- SD, 2.3 +/- 0.9 hours per night), moderate (n=19, 5.3 +/- 0.6 hours per night), or good (n=43, 6.8 +/- 0.3 hours per night). Cumulative logit regression models (good -> moderate -> poor) revealed independent baseline predictors to be ESS (per unit increase) (OR [95% CI], 0.763 [0.651, 0.893]), SDS (1.461 [1.238, 1.724]), and PSQI (2.261 [1.427, 3.584]); and 3-week therapy predictors to be ESS (0.554 [0.331, 0.926]), PSQI (2.548 [1.454, 4.465]), and the changes (3rd week-baseline data) in ESS (0.459 [0.243, 0.868]), FSS (3.556 [1.788, 7.070]), and PSQI (2.937 [1.273, 6.773]). Two predictive score formulas for poor adherence were developed. The area under the curve (AUC) of the receiver operating characteristics (ROC) curves for baseline and 3-week formulas were 0.989 and 0.999, respectively. Bootstrap analysis indicated positive predictive values of baseline and 3-week predictive scores in our patient population of 0.82 (95% CI [0.82, 0.83]) and 0.94 (95% CI [0.93, 0.94]), respectively. Conclusion: A high level of prediction of poor adherence pattern is possible both before and at the first 3 weeks of therapy. The predictive scores should be further evaluated for external validity.
引用
收藏
页码:715 / 723
页数:9
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