Neighborhood of Residence is Associated with Daily Adherence to CPAP Therapy

Platt, Alec B.; Field, Samuel; Asch, David A.; Chen, Zhe; Patel, Nirav P.; Gupta, Rajesh Kumar; Roche, Dominic; Gurubhagavatula, Indira; Christie, Jason D.; Kuna, Samuel T.

doi:10.1093/sleep/32.6.799

Cited by 118 publications

(115 citation statements)

References 48 publications

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“…13,20,[44][45][46][47][48] Our data, which include subjects with a wide range of SDB severity and sleepiness as well as wide ranging racial and gender distribution, are in agreement with studies that showed no relationship between these demographic variables and short-term or long-term CPAP use. In our dataset with 27% Black subjects, we failed to show a difference in ST CPAP adherence based on race (Black subjects: 3.2 ± 2.0 h/night vs White subjects: 3.2 ± 2.4 h/night, p = 0.99).…”

Section: 3839supporting

confidence: 90%

“…Social factors such as socioeconomic status, social support, and partner involvement have been shown in some studies to affect adherence, although not in a simple manner. 42,45,53 Similarly, psychological factors have also been shown to predict adherence in many studies, [18][19][20] although not in all. 47,49 Most of the current literature focuses on the use of psychological interventions to promote CPAP usage (CBT, 54 motivational interviewing 55 ), but these are time and resource intensive, so that identifying who would or would not benefit from these interventions may be useful.…”

Section: 49mentioning

confidence: 99%

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Sleep Quality, Short-Term and Long-Term CPAP Adherence

Somiah

Taxin

Keating

et al. 2012

Journal of Clinical Sleep Medicine

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S C I E N T I F I C I N V E S T I G A T I O N SU ntreated obstructive sleep apnea/hypopnea syndrome (OSAHS) signifi cantly affects quality of life and cardiovascular/cerebrovascular morbidities and mortality.1-4 CPAP therapy has been shown to be effective in treating sleep disordered breathing (SDB) by reducing the apnea/hypopnea index (AHI) 5 and by reducing excessive daytime somnolence (EDS). 6Despite this, CPAP acceptance and adherence are disappointingly low. A signifi cant number of patients (ranging from 30% to 80% in various studies) demonstrate an average CPAP usage of less than 4 hours per night. 7,8 Several reviews have emphasized the need to identify patients who are at the greatest risk for non-adherence, with the goal of developing techniques to maximize overall adherence. 9,10Studies have suggested that CPAP adherence can be correlated to characteristics of patients at baseline, such as the severity of OSAHS, 11-13 the level of EDS, 14 and anatomical factors (smaller nasal cross-sectional area, reduced nasal volume, and high nasal resistance 15,16 ), but the strength of these correlations has been weak. Drake et al. showed that patients whose sleep effi ciency on the CPAP titration night improved most had the greatest CPAP compliance at 47 days.17 More recently, studies using social cognitive theory 18-20 and health BRIEF SUMMARYCurrent knowledge/Study Rationale: Despite its efficacy, adherence to CPAP therapy is highly variable amongst patients with obstructive sleep apnea with large numbers of patients demonstrating inadequate adherence to CPAP. The present study is aimed at identifying early predictors of CPAP adherence from variables obtained at the time of diagnosis and titration of CPAP, thereby providing potential for early intervention. Study Impact: Our data show that better sleep quality (greater % REM) was seen in patients with higher CPAP adherence and confi rm that long term adherence was largely predicted by short term adherence. This suggests that interventions that improve sleep during or prior to the CPAP titration study may be useful in improving CPAP adherence.

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Section: 3839supporting

confidence: 90%

Section: 49mentioning

confidence: 99%

Sleep Quality, Short-Term and Long-Term CPAP Adherence

Somiah

Taxin

Keating

et al. 2012

Journal of Clinical Sleep Medicine

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“…The higher rate of delays in filling prescriptions observed in respondents living in unsafe neighborhoods has not been previously demonstrated in the literature, but is consistent with other work linking neighborhood safety to general health behaviors [21][22][23] and a study linking neighborhood-level socioeconomic disadvantage with adherence to CPAP therapy for obstructive sleep apnea. 32 In the current study, approximately half of the respondents who reported delays in filling prescriptions and obtaining needed care cited cost as the reason for the delay. This suggests that perceived safety and adherence may be linked by mechanisms other than financial pressures alone.…”

Section: Discussionmentioning

confidence: 63%

Self-reported Neighborhood Safety and Nonadherence to Treatment Regimens Among Patients with Type 2 Diabetes

Billimek

Sorkin

2011

J GEN INTERN MED

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“…CPAP adherence has been shown to be related to socioeconomic class, marital status, race, and psychiatric disease (84)(85)(86). These patients may have a difficult time achieving the Medicare adherence patterns and thus certain segments of the population are potentially targets of governmentmandated reimbursement discrimination (87,88).…”

Section: -69)mentioning

confidence: 99%

An Official American Thoracic Society Statement: Continuous Positive Airway Pressure Adherence Tracking Systems. The Optimal Monitoring Strategies and Outcome Measures in Adults

Schwab

Badr

Epstein

et al. 2013

Am J Respir Crit Care Med

250

196

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Background: Continuous positive airway pressure (CPAP) is considered the treatment of choice for obstructive sleep apnea (OSA), and studies have shown that there is a correlation between patient adherence and treatment outcomes. Newer CPAP machines can track adherence, hours of use, mask leak, and residual apnea-hypopnea index (AHI). Such data provide a strong platform to examine OSA outcomes in a chronic disease management model. However, there are no standards for capturing CPAP adherence data, scoring flow signals, or measuring mask leak, or for how clinicians should use these data. Methods: American Thoracic Society (ATS) committee members were invited, based on their expertise in OSA and CPAP monitoring. Their conclusions were based on both empirical evidence identified by a comprehensive literature review and clinical experience. Results: CPAP usage can be reliably determined from CPAP tracking systems, but the residual events (apnea/hypopnea) and leak data are not as easy to interpret as CPAP usage and the definitions of these parameters differ among CPAP manufacturers. Nonetheless, ends of the spectrum (very high or low values for residual events or mask leak) appear to be clinically meaningful. Conclusions: Providers need to understand how to interpret CPAP adherence tracking data. CPAP tracking systems are able to reliably track CPAP adherence. Nomenclature on the CPAP adherence tracking reports needs to be standardized between manufacturers and AHI Flow should be used to describe residual events. Studies should be performed examining the usefulness of the CPAP tracking systems and how these systems affect OSA outcomes.Keywords: CPAP adherence; sleep apnea; CPAP tracking systems EXECUTIVE SUMMARYObstructive sleep apnea (OSA) is an extremely common condition and is associated with significant morbidity and mortality (1-18). Optimal treatment of sleep apnea is critical because sleepdisordered breathing is associated with the increased risk of vehicular crashes and cardiovascular morbidity and mortality (6, 9-18). Continuous positive airway pressure (CPAP) is the treatment of choice for sleep apnea (19)(20)(21)(22). Increased CPAP adherence has been shown to improve outcomes such as daytime sleepiness, quality of life, and mortality (23-25). OSA should be considered in a chronic disease management model in which CPAP adherence is tracked over time. To assess CPAP adherence and efficacy, tracking systems have been implemented. Such systems monitor CPAP efficacy (residual sleep-disordered breathing), hours of CPAP use, mask leak, and a number of different flow signals. However, there are no standards on how to use the data from these new CPAP tracking systems nor do we have evidence that these systems ultimately improve outcomes. See the online supplement for full discussion of the literature on the accuracy of the residual AHI and mask leak.The purpose of this document is to (1) review the data (adherence, leak, efficacy, flow signals) obtained from CPAP adherence tracking systems and the reliability of th...

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Neighborhood of Residence is Associated with Daily Adherence to CPAP Therapy

Abstract: In a retrospective cohort of veterans, initial CPAP adherence was closely associated with higher neighborhood socioeconomic factors. Future investigation should target specific impediments to adherence in the home and neighborhood environment.

Cited by 118 publications

References 48 publications

Sleep Quality, Short-Term and Long-Term CPAP Adherence

Sleep Quality, Short-Term and Long-Term CPAP Adherence

Self-reported Neighborhood Safety and Nonadherence to Treatment Regimens Among Patients with Type 2 Diabetes

An Official American Thoracic Society Statement: Continuous Positive Airway Pressure Adherence Tracking Systems. The Optimal Monitoring Strategies and Outcome Measures in Adults

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