Lucas M. Donovan

Prevalence and Characteristics of Central Compared to Obstructive Sleep Apnea: Analyses from the Sleep Heart Health Study Cohort.

STUDY OBJECTIVES Determine the prevalence of central sleep apnea (CSA) in a large community-based cohort using current definitions and contrast the clinical characteristics of subjects with CSA to those with obstructive sleep apnea (OSA) and no sleep apnea. METHODS A cross sectional analysis of baseline data from 5,804 participants of the Sleep Heart Health study was performed. Subjects meeting contemporary diagnostic criteria for CSA and Cheyne Stokes respiration (CSR) were compared to those without sleep apnea and those with OSA. Demographic data, medical comorbidities, medication use, and sleep related symptoms were compared between the groups. RESULTS The prevalences of CSA and Cheyne Stokes respiration (CSR) in this sample were 0.9 (95% confidence intervals [CI]: 0.7-1.2)% and 0.4 (95% CI: 0.3-0.6)%, respectively. Individuals with CSA were older, had lower body mass indexes (BMI), lower Epworth Sleepiness Scale scores, and were more likely to be male than individuals with obstructive sleep apnea OSA. Among those with self-reported heart failure (HF), OSA was much more common at 55.1% (95% CI: 45.6-64.6) than CSA 4.1% (95% CI: 0.3-7.9). CONCLUSIONS This is the largest community-based study of the prevalence and characteristics of CSA to date and demonstrates a prevalence of CSA that is intermediate to those previously noted. Contrary to prior data from clinic based samples, individuals with heart failure were much more likely to have OSA than CSA.

The effectiveness of an obstructive sleep apnea screening and treatment program in patients with type 2 diabetes

AIMS As recommended by current guidelines, we tested the acceptability and impact of screening patients with type 2 diabetes for obstructive sleep apnea (OSA). METHODS In a large urban primary care practice, we instituted a telephone-based OSA screening program using a validated tool (STOP-BANG) in patients with type 2 diabetes. Patients identified as high risk were referred for diagnostic sleep testing, and those diagnosed with OSA were offered positive airway pressure (PAP) therapy. We evaluated the impact of PAP on sleep-related symptoms, glycemic control, and hospitalization rates. RESULTS We identified 738 of 818 (90.1%) patients with type 2 diabetes as high risk for OSA. Only 29.2% (n = 213) of high risk patients were willing to undergo diagnostic sleep testing. The prevalence of OSA was 90.6% in this group, but only 66.0% of those with OSA initiated PAP. Patients with higher burden of sleep symptoms were more likely to pursue testing and initiate therapy. PAP use was associated with reduced sleep-related symptoms (mean Epworth sleepiness scale score declined from 8.8 to 7.3, p < .001), but did not impact hemoglobin A1c levels at one year (7.7-7.9%, p = .12). Changes in glycemic control and hospitalization rates did not differ from comparator groups. CONCLUSIONS Despite a high prevalence of OSA, willingness to pursue diagnostic testing and treatment was low in an unselected type 2 diabetes population. Furthermore, glycemic control did not improve. Future screening programs should focus on patients with substantial sleep related symptoms as this group is most likely to derive benefit from treatment.

Sleep disturbance in smokers with preserved pulmonary function and with chronic obstructive pulmonary disease

Rationale: Sleep disturbance frequently affects patients with chronic obstructive pulmonary disease (COPD), and is associated with reduced quality of life and poorer outcomes. Data indicate that smokers with preserved pulmonary function have clinical symptoms similar to those meeting spirometric criteria for COPD, but little is known about the driving factors for sleep disturbance in this population of emerging interest. Objectives: To compare the magnitude and correlates of sleep disturbance between smokers with preserved pulmonary function and those with airflow obstruction. Methods: Using cross‐sectional data from the COPD Outcomes‐Based Network for Clinical Effectiveness and Research Translation multicenter registry, we identified participants clinically identified as having COPD with a smoking history of at least 20 pack‐years and either preserved pulmonary function or airflow obstruction. We quantified sleep disturbance by T‐score measured in the sleep disturbance domain of the Patient‐Reported Outcomes Information System questionnaire, and defined a minimum important difference as a T‐score difference of two points. We performed univariate and multivariable linear regression to evaluate correlates within each group. Results: We identified 100 smokers with preserved pulmonary function and 476 with airflow obstruction. The sleep disturbance T‐score was 4.1 points greater among individuals with preserved pulmonary function (95% confidence interval [CI], 2.0‐6.3). In adjusted analyses, depression symptom T‐score was associated with sleep disturbance in both groups (airflow obstruction: &bgr;, 0.61 points; 95% CI, 0.27‐0.94; preserved pulmonary function: &bgr;, 0.25 points; 95% CI, 0.12‐0.38). Of note, lower percent predicted FEV1 was associated with greater sleep disturbance among those with preserved pulmonary function (&bgr;, ‐0.19 points; 95% CI, ‐0.31 to ‐0.07), whereas higher FEV1 was associated with greater sleep disturbance among individuals with airflow obstruction (&bgr;, 0.06 points; 95% CI, 0.01‐0.10). Conclusions: Among smokers with clinically identified COPD, the severity of sleep disturbance is greater among those with preserved pulmonary function compared with those with airflow obstruction. Nonrespiratory symptoms, such as depression, were associated with sleep disturbance in both groups, whereas the relationship of sleep disturbance with FEV1 differed.

Making the Most of Simplified Sleep Apnea Testing

Clinical sleep medicine emerged as a subspecialty around expertise in performing and billing for laboratory-based polysomnography. With the obesity epidemic and increasing recognition of obstructive sleep apnea (OSA), billing for overnight polysomnography has been one of the fastest-growing charges for third-party payers. In response, there has been a push for adoption of home sleep testing (HST) to reduce costs (1). In addition, the development of autotitrating continuous positive airway pressure (CPAP) has removed the need for in-laboratory CPAP titration studies, further reducing costs. Several randomized, controlled trials have shown that a strategy of HST and autotitrating CPAP is as effective as a laboratory-based strategy (26). However, these studies have focused on patients who had a high pretest probability of OSA, were diagnosed with moderate to severe disease, and were treated with CPAP only (26). On the basis of these trials, professional guidelines have recommended use of HST for OSA evaluation in patients with high pretest probability (7). No trial has evaluated the performance of a home-based diagnostic strategy in patients with low pretest probability for OSA or in selecting non-CPAP therapies (such as positional therapy or mandibular advancement devices) in patients with mild OSA. Despite this lack of data, in an effort to cut costs, a growing number of third-party payers have demanded use of HST as the initial diagnostic test for OSA in all patients, regardless of pretest probability (1). In this setting, the work by Chai-Coetzer and colleagues provides welcome insight (8). The investigators randomly assigned a broad range of patients being evaluated for OSA and undergoing full polysomnography to have interpretations based on full polysomnographic data, cardiorespiratory data only (to simulate HST), or oximetry and heart rate data only (to simulate overnight oximetry testing). All patients, including those diagnosed with mild OSA, simple snoring, or nonrespiratory disorders, were included in the outcomes analysis. This intention-to-treat design more closely reflects the real-world effect of replacing polysomnography with HST. It is reassuring that, in this broad range of patients, the authors found no difference in the distribution of initial diagnoses; clinician confidence in the diagnoses; or changes in diagnoses made after 4 months, when full data were made available for patients treated based on polysomnography versus HST-type data. Furthermore, there were no differences in CPAP compliance, daytime sleepiness, or quality of life between the groups. In fact, post hoc analyses suggested a trend toward better outcomes in patients diagnosed using HST-type data and treated with autotitrating CPAP than those diagnosed using full polysomnography and treated with fixed CPAP after in-laboratory CPAP titration. These results support the contention that a home-based diagnostic and treatment strategy leads to outcomes that are as good as, if not better than, those with a laboratory-based strategy, possibly due to improvements in time to treatment initiation. In contrast, treatment decisions based on oximetry alone led to worse outcomes. The authors ascribe these outcomes to lower physician diagnostic confidence. This may reflect a lack of training in the use of oximetry, given that no professional society has developed standards for scoring or reporting overnight oximetry testing. Worse performance with overnight oximetry occurred primarily in patients with milder disease severity, with difficulty arising in distinguishing mild OSA from simple snoring. Physicians seemed to err on the side of being more aggressive with treatment in these milder cases. Chai-Coetzer and colleagues demonstrate that the oxygen desaturation index (ODI), derived from oximetry, performs well in predicting moderate to severe OSA, supporting the notion that oximetry alone can be used in this setting. Understanding the performance of the ODI in distinguishing mild OSA from simple snoring would be instructive because diagnostic difficulties were encountered in this area. Some weaknesses of the study should be noted. Because all testing was done in a sleep laboratory, signal quality was likely better than it would have been with true HST. Further, the cardiovascular effect of treatment was not assessed; in fact, patients with active cardiovascular disease were excluded from the study. Given how frequently OSA coexists with cardiovascular disease, future studies need to include these patients to ensure clinical relevance. Despite these limitations, Chai-Coetzer and colleagues have shown that it is reasonable to use HST in a broad range of patients being evaluated for OSA. This is welcome news to providers and other stakeholders interested in delivering cost-effective care. Furthermore, the lack of infrastructure required for HST allows for easy scalability to reduce long wait times for testing and to expand access to underserved groups, such as rural populations and those without resources for transportation or overnight child care. Nevertheless, measures will need to be taken to ensure that care is delivered in an equitable and sustainable way. Economic modeling suggests that under current reimbursement policies, adoption of HST results in a negative operating margin for providers (9). Furthermore, many third-party payers have developed administrative barriers restricting access to both in-laboratory testing and HST, suggesting an underlying desire to reduce all sleep care, not just low-value care (1). In response to these financial pressures, sleep laboratories have minimized or eliminated technician time for patient education on OSA and the application of HST equipment, likely reducing both diagnostic test performance and long-term adherence to OSA therapy. It will be of paramount importance for professional medical societies to work with payers and other stakeholders to ensure an economically viable strategy of replacing in-laboratory polysomnography with HST in the routine evaluation of OSA in order to provide high-value care for patients with this common disease.

Getting to the Root of the Matter

‘Massive efforts are underway to understand variation in root traits with the goal of selecting beneficial characteristics that enhance resource acquisition and productivity for meeting global food demands’, says Dr Powell. ‘These efforts are usually conducted without taking into account the beneficial arbuscular mycorrhizal (AM) partnerships, which are relationships between higher plants and fungi. The outcomes of strictly plant-focussed efforts are likely to be incomplete unless the modifying effects of broader plant-soil interactions are considered.’

Role of Comorbidities in Treatment and Outcomes after Chronic Obstructive Pulmonary Disease Exacerbations

Rationale: Hospital readmissions are an important cause of morbidity and mortality among patients with chronic obstructive pulmonary disease (COPD). Although comorbidities are associated with outcomes in COPD, it is unknown how they affect treatment choices. Objectives: We sought to examine whether comorbidity was associated with readmission, mortality, and delivery of in‐hospital treatment for COPD exacerbations. Methods: We performed a cohort study of veterans hospitalized with a COPD exacerbation to six Veterans Affairs hospitals between 2005 and 2011. We collected comorbidities in the year before hospitalization. We defined our primary outcome as readmission and/or mortality within 30 days of discharge, and treatment quality as receipt of systemic corticosteroids and respiratory antibiotics during the index hospitalization. Results: A total of 2,391 patients were included. Each one‐point increase in Charlson index was associated with greater odds of readmission or death (adjusted odds ratio [aOR], 1.24; 95% confidence interval [CI], 1.18‐1.30) and reduced odds of receiving treatment with steroids and antibiotics (aOR, 0.90; 95% CI, 0.85‐0.95), in adjusted analyses. Patients with comorbid congestive heart failure (aOR, 0.64; 95% CI, 0.52‐0.79), coronary artery disease (aOR, 0.73; 95% CI, 0.60‐0.89), and chronic kidney disease (aOR, 0.74; 95% CI, 0.55‐0.99) were less likely to receive corticosteroids and antibiotic treatment than patients without those comorbidities. We did not identify any comorbidity that was associated with increased odds of receiving appropriate therapies. Conclusions: Comorbidity was associated with 30‐day readmission and mortality, and with delivery of fewer treatments known to be beneficial among patients with COPD exacerbation.