Nasal continuous positive airway pressure (CPAP) is presently considered as the “treatment of choice” for obstructive sleep apnea (OSA). Though some OSA patients adhere to treatment recommendations ...and ultimately respond quite well to CPAP therapy, there is a substantial subgroup for which compliance is a particularly difficult issue. Despite receiving recommendations to the contrary and for reasons that are incompletely understood, the majority of OSA patients settle for a partial compliance pattern. Whether a partial compliance schedule is beneficial or harmful is virtually unexamined: Unlike other medical treatments, there are few data concerning the “dose–response relationship” of CPAP to its desired effects. We argue that CPAP “dose” is a function not only of CPAP pressure but of time-on-CPAP as well. Critical questions that remain unanswered are what “dose” of CPAP is needed to effect an appropriate treatment outcome and which treatment outcomes should form the basis of our recommendations. Recent placebo-controlled studies comparing CPAP to suboptimal CPAP pressures may be informative in this regard. Directions for future research are suggested.
To examine the association of sleep apnea with heart disease.
Prospective study.
Medical wards at the Veterans Affairs San Diego Healthcare System.
Three hundred fifty-three randomly selected ...inpatient men.
Sleep was recorded for 2 nights in the hospital. Medical conditions were obtained from hospital medical records. Cox proportional hazards analyses indicated that patients with congestive heart failure (CHF) plus central sleep apnea (CSA) had shorter survival than those with just CHF, just sleep apnea (obstructive or central), or neither. Survival for those with obstructive sleep apnea (OSA) or CSA and no CHF was no different than for those with neither disorder. Follow-up analysis showed that for those with no CHF, neither CSA nor OSA shortened survival (p > 0.80). For those with CHF, having CSA shortened the life span with a hazard ratio of 1.66 (p = 0.012), but having OSA had no effect. Patients with CHF had more severe sleep apnea than those with no heart disease.
This study does not clarify the issues of cause and effect, but does reinforce the strong associations between sleep apnea and heart disease in elderly men. These data suggest that people with coronary disease should be regarded as a risk group for sleep apnea.
To examine the nightly variability of sleep-disordered breathing (SDB) as measured by the apnea-hypopnea index (AHI).
Retrospective comparison of 3 sequential nights of testing performed in the home ...in 1091 patients who were referred for diagnostic testing of SDB.
The Pearson and Intraclass correlation coefficients ranged between 0.88 and 0.90 for each pair of nights. Based on night 1, approximately 90% of patients were classified consistently with "AHI-high" (the highest AHI measured across the 3 nights) using an AHI threshold of 5. However, 10% were misclassified on night 1 relative to the highest AHI level.
These findings suggest that (1) 1 night of diagnostic testing for SDB is not sufficient to diagnosis SDB in approximately 1 of every 10 cases, and (2) there is little, if any, significant nightly change in SDB in the home environment.
D.
Abstract
Introduction
The CPAP recall of 2021 has highlighted an inherent problem that occurs when a field of medicine is overly dependent on a single class of medical devices to treat a condition. ...The global shortage of CPAP devices has led to numerous individuals with OSA being unable to obtain a CPAP machine to treat their condition, including those with severe OSA. CPAP is well known to be efficacious in treating OSA, but has limited effectiveness, particularly for mild-to-moderate cases. It has been reported that there are nearly 200 different medical devices approved by the FDA to treat OSA. The goal of this project was to search the FDA databases to investigate the number of devices currently on file with the FDA. A secondary goal was to examine the range of FDA product categories for the treatment of OSA.
Methods
An FDA database (AccessGUDID; https://accessgudid.nlm.nih.gov) with a release date of December 1, 2021 was searched for devices that are approved for the treatment of sleep apnea. The text string “sleep apnea” was used for the search. Diagnostic devices, duplicate versions of the same treatment devices, and device accessories were excluded from the total counts. The FDA classifies medical devices into three categories (I, II, III), with a higher classification level indicating greater risk to patients.
Results
The FDA AccessGUDID database search returned 166 results, which resulted in 72 unique devices across 10 product code categories. 9 of the 10 product codes in the FDA database were class II (medium risk) and 1/10 was classified as III (high risk). 65 of the devices were reported to be in commercial distribution at the time of the search and 7 were not.
Conclusion
This analysis found that a relatively large number of FDA-approved devices exist for the treatment of OSA across a range of product categories. The field is encouraged to develop a better understanding of which subgroups of OSA patients could benefit from alternative forms of treatment in an effort to diversify treatment options and reduce the field’s reliance on a single type of device, particularly for patients with mild-to-moderate OSA.
Support (If Any)
VA IIR 16-277
The Hepatitis C Self-Management Program Groessl, Erik J.; Ho, Samuel B.; Asch, Steven M. ...
Health education & behavior,
12/2013, Letnik:
40, Številka:
6
Journal Article
Recenzirano
Objective. Chronic hepatitis C infection afflicts millions of people worldwide. Although antiviral treatments are increasingly effective, many hepatitis C virus (HCV) patients avoid treatment, do not ...complete or respond to treatment, or have contraindications. Self-management interventions are one option for promoting behavioral changes leading to liver wellness and improved quality of life. Our objective was to evaluate whether the effects of the HCV self-management program were sustained at the 12-month follow-up assessment. Methods. Veteran Affairs patients with hepatitis C (N = 134; mean age = 54.6 years, 95% male, 41% ethnic minority, 48% homeless in last 5 years) were randomized to either a 6-week self-management workshop or an information-only intervention. The weekly 2-hour self-management sessions were based on a cognitive–behavioral program with hepatitis C–specific modules. Outcomes including hepatitis C knowledge, depression, energy, and health-related quality of life were measured at baseline, 6 weeks, 6 months, and 12 months later. Data were analyzed using repeated measures ANOVA. Results. Compared with the information-only group, participants attending the self-management workshop improved more on HCV knowledge (p < .005), SF-36 energy/vitality (p = .016), and the Quality of Well-Being Scale (p = .036). Similar trends were found for SF-36 physical functioning and Center for Epidemiologic Studies Short Depression Scale. Conclusion. Better outcomes were sustained among self-management participants at the 12-month assessment despite the intervention only lasting 6 weeks. HCV health care providers should consider adding self-management interventions for patients with chronic HCV.
Abstract Introduction Obstructive sleep apnea (OSA) is highly prevalent in the Veteran population. The prevailing treatment for OSA is positive airway pressure (CPAP), but benefits depend on regular ...use. CPAP adherence is operationally defined as the number of hours of CPAP use per 24-hour period at the prescribed pressure. There are a variety of alternate metrics help to describe CPAP use, with most focused on duration and some type of categorization. Given the limited utility of these kinds of CPAP metrics, we wondered if a different type of CPAP adherence metric might be warranted. Putting on the CPAP mask is a behavioral action, so we explored the value of a metric focused on putting the mask on at least once per day. Methods Participants in an CPAP trial were provided standard education about their diagnosis and treatment at baseline. Follow-up visits were held two and four months from start of treatment. Treatment adherence metrics were derived from CPAP usage data. The “anyuse” metric was defined as the percentage of nights the mask was put on at least once in a 24-hour period. Results Twenty participants had a mean age of 50.2±13.9, mean AHI of 23.3±16.0, and mean BMI of 31.3.8±4.9 (kg/m2). Nightly CPAP adherence measured over the two-month period was 2.6±1.6 hours per night (mean±SD). The average anyuse at two-month was 78% ± 0.24 (12%-100%). Anyuse was moderately correlated with CPAP adherence (r=0.682, r-squared=0.465, p< 0.001), which means that while 46% of the variance in adherence was accounted for by anyuse, 54% of the variance was not. Conclusion The anyuse metric is a relatively simple metric that might have value as a supplemental metric to CPAP adherence. Importantly, it does not overlap substantially with CPAP adherence and provides a measure of initial behavioral action. A possible related metric is a count of the number of mask on events per day. Further exploration of these metrics appears to be warranted. Support (if any) This project was supported in part by the VA HSR&D IIR 16-277 and the VA San Diego Healthcare System Pulmonary Sleep Medicine Section and Research Service.
Abstract
Introduction
Research study recruitment has been profoundly affected by the COVID-19 pandemic, demonstrated by significant delays or pauses. Various guidelines pertaining to in-person visits ...have applied to research. Some call for exclusion of participants that the CDC has labeled “at increased risk”.1 For obstructive sleep apnea (OSA) studies, these guidelines have caused a sharp decrease in the number of new participants. This decrease is due to high rates of OSA comorbidities including obesity and diabetes. New evidence-based risk scores have been developed using individual- and community-level factors. The use of more refined COVID-19 risk scores can help protect patient safety while allowing research to continue.
Methods
The risk score assessment used for this study (COVID-19 Mortality Risk Calculator; Johns Hopkins University, Baltimore, MD)2 is evidence-based and uses a set of risk factors and community-level pandemic dynamics in the state of residence.3,4 It was compared to the list of CDC medical conditions that are considered to put an individual “at increased risk.” Both measures were calculated retrospectively on current participants to determine how many could safely attend in-person visits based on each risk assessment method.
Results
Sample characteristics of the 110 participants were: mean age: 49.5±13.7(24–76); mean BMI: 32.3±5.3(20.9–46.1); mean AHI: 24.3±21.4(5.1–110). Mortality Risk Calculator scores were: 91(82.7%) close to/lower than average Level 1; 12(10.9%) moderately elevated; 6(5.5%) substantially elevated; 1(0.9%) high; and 0(0%) very high Level 5. Using CDC guidance, 63 (57.3%) had at least one at-risk condition and 47 (42.7%) had 0. Using only Level 1 of the Risk Calculator would allow an additional 28 (25%) participants to attend in-person visits; using Levels 1 and 2 would allow an additional 40 (37%) participants.
Conclusion
Policies based on CDC at-risk conditions resulted in higher levels of participant exclusion in research during the COVID-19 pandemic than use of an evidence-based Mortality Risk Calculator. This analysis shows that researchers can use risk-adjusted scores to make informed decisions about study participation that balances both participant safety and research study progress.
Support (if any)
This project was supported in part by Department of Veteran Affairs VA HSRD IIR 16–277, VA RRD D2651-R, and VA San Diego Healthcare System Research Service.
The goal of this study was to examine whether there were ethnic differences in polysomnographically recorded sleep, either in the controlled laboratory environment or in the home setting.
Prospective ...study of ethnic differences in stress physiology and sleep.
Two sleep recordings were performed on consecutive nights in a hospital-based sleep laboratory, followed 1 to 4 weeks later by a third sleep recording in the subject's home.
51 employed healthy adult subjects, aged 15 to 50 years. 24 self-identified as black, and 27 as white.
None.
Blacks had less slow wave sleep than did whites in both the sleep laboratory and in the home. Blacks had significantly more slow wave sleep at home compared to the hospital setting, while the reverse was true for whites. This location-by-ethnicity interaction could not be accounted for by depression ratings or social class.
The home setting is generally considered to be more ecologically valid than the controlled hospital-based laboratory setting for the monitoring of sleep. These data suggest that ethnicities may respond differentially to the sleeping environment. This observation may need to be taken into account in future epidemiologic studies of sleep.
We previously postulated how evolutionary changes in man's upper respiratory tract to facilitate speech, a phenomenon Jared Diamond calls The Great Leap Forward, have predisposed man to obstructive ...sleep apnea (OSA) Diamond J. The Third Chimpanzee: the evolution and future of the human animal. New York: HarperCollins Publishers; 1992. p. 21, 23, 32–54, 54–6; Davidson TM. The Great Leap Forward: the anatomic evolution of obstructive sleep apnea. Sleep Medicine 2003;4:185–94. We grouped these anatomic changes into four categories: klinorynchy, laryngeal descent, craniobase angulation and supralaryngeal vocal tract (SVT) ratio of SVT
H:SVT
V. This study was designed to investigate the relationship between cephalometric measures corresponding to these anatomic changes and OSA.
One hundred and twenty-three male subjects presenting with symptoms of OSA underwent unattended multi-channel home sleep studies. We obtained cephalometric measurements from standard lateral cephalograms. Pearson correlation coefficients were calculated between cephalometrics and apnea–hypopnea index (AHI), age, and body mass index (BMI).
Our results showed significant correlation between AHI and klinorynchy, laryngeal descent, and craniobase angulation.
Overall, our data supports the theory that evolutionary anatomic changes to facilitate speech correlate with OSA severity. The cumulative changes in each cephalometric category trended in the directions hypothesized and support the Great Leap theory of OSA evolution.
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