Clinical Characteristics, Comorbidities, and Response to Treatment of Veterans With Obstructive Sleep Apnea, Cincinnati Veterans Affairs Medical Center, 2005-2007

ORIGINAL RESEARCH

Pamela Samson, MS; Kenneth R. Casey, MD, MPH; James Knepler, MD; Ralph
J. Panos, MD

Suggested citation for this article: Samson P,
Casey KR, Knepler J, Panos RJ. Clinical characteristics, comorbidities, and
response to treatment of veterans with obstructive sleep apnea, Cincinnati
Veterans Affairs Medical Center, 2005-2007. Prev Chronic Dis 2012;9:110117.
DOI:
http://dx.doi.org/10.5888/pcd9.110117.

PEER REVIEWED

Abstract

Introduction

Obstructive sleep apnea (OSA) is a common disorder that is associated with
significant morbidity. Veterans may be at an elevated risk for OSA because of
increased prevalence of factors associated with the development and progression
of OSA. The objective of this study was to determine the clinical
characteristics, comorbidities, polysomnographic findings, and response to
treatment of veterans with OSA.

Methods

We performed a retrospective chart review of 596 patients undergoing
polysomnography at the Cincinnati Veterans Affairs Medical Center from February
2005 through December 2007. We assessed potential correlations of clinical data
with polysomnography findings and response to treatment.

Results

Polysomnography demonstrated OSA in 76% of patients; 30% had mild OSA, 23%
moderate OSA, and 47% severe OSA. Increasing body mass index, neck
circumference, Epworth Sleepiness Scale score, hypertension, congestive heart
failure, and type 2 diabetes correlated with increasing OSA severity. Positive
airway pressure treatment was initiated in 81% of veterans with OSA, but only
59% reported good adherence to this treatment method. Of the patients reporting
good adherence, a greater proportion of those with severe OSA (27%) than with
mild or moderate disease (0%-12%) reported an excellent response to treatment.

Conclusion

The prevalence of metabolic and cardiovascular comorbidities increased with
increasing OSA severity. Only 59% of treated patients reported good adherence to
treatment with positive airway pressure, and response to treatment correlated
with OSA severity.

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Introduction

Obstructive sleep apnea (OSA), a condition characterized by repeatedly
interrupted breathing during sleep, occurs frequently in adults (1). The
prevalence of OSA increases with age and may affect 38% to 68% of people older
than 60 years (1). Clinical characteristics that predict risk of development and
progression of OSA include a large neck circumference and male sex. Body mass
index (BMI) and tonsil size are predictors of OSA severity (2,3). Comorbid
conditions associated with OSA include hypertension, atrial fibrillation,
congestive heart failure, stroke, metabolic syndrome, and type 2 diabetes
(2,4,5). Patients cared for by the Veterans Health Administration (VHA) are
predominantly older men with many of these conditions (6). A survey of veterans
in northeast Ohio using the Cleveland Sleep Habits questionnaire (7) showed that
46% of the respondents were at high risk for OSA (7). A similar study in San
Juan, Puerto Rico, showed that 34% of veterans attending ambulatory clinics were
at high risk for OSA (8).

OSA is diagnosed by polysomnography and measured by the apnea-hypopnea index
(AHI). An AHI of more than 5 events per hour (9) is diagnosed as OSA. OSA
severity is stratified according to AHI score. Fewer than 5 events per hour is
designated as normal, 5 to 14 events per hour as mild OSA, 15 to 30 events per
hour as moderate OSA, and more than 30 events per hour as severe OSA (9). Once OSA
is diagnosed, a continuous positive airway pressure (CPAP) study is often
performed to determine the optimal positive airway pressure required to reduce
the AHI and improve oxygenation. The most common treatment for OSA,
positive airway pressure (PAP) treatment, is frequently initiated to reduce sleep-related
symptoms. Patients with more sleep-related symptoms appear to receive greater
benefit from treatment than do patients with fewer sleep-related symptoms (10).
Despite the availability of numerous types of masks and interfaces, CPAP is
often poorly tolerated, and it is difficult to predict which patients will
adhere and respond to treatment (11). The objective of this study was to
determine the clinical characteristics, comorbidities, polysomnographic
findings, and response to therapy of veterans with OSA.

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Methods

We reviewed the records of 596 patients who underwent polysomnography during
3 years at the Cincinnati Veteran Affairs Medical Center (VAMC). Patients were
evaluated on the basis of their AHI, OSA severity, clinical characteristics (eg,
neck circumference, BMI), comorbidities, and response to treatment. This
protocol was approved by the research and development committee of the
Cincinnati VAMC and reviewed by the University of Cincinnati institutional
review board, which waived the need for consent.

Participant selection

Health care providers throughout the Cincinnati VAMC referred veterans with
suspected sleep disorders to our sleep clinic, where a standardized sleep
evaluation was performed and polysomnography scheduled. We retrospectively
reviewed the medical records and polysomnography reports of 748 veterans who
completed evaluation and testing for sleep-disordered breathing in the
Cincinnati VAMC from February 2005 through December 2007. From this chart
review, we selected for our study group 596 patients who completed the
evaluation and polysomnography testing. We excluded 152 patients with previously
diagnosed OSA who returned for therapeutic (CPAP/bilevel titration) studies and
patients who did not complete testing, terminated the test prematurely, or
achieved insufficient or no sleep. All patients who were referred for
polysomnography completed a pretest assessment and questionnaire with assistance
from the sleep study technologist. Information abstracted from this
questionnaire included age, measured weight, self-reported height, smoking
history, Epworth Sleepiness Scale (ESS) score (a measure of sleep propensity)
(12), and self-reported snoring, apneas, and morning headaches.

We used a Sandman Elite sleep system for polysomnography studies (Sandman
Elite, version 8.0, Nellcor Puritan Bennett [Melville] Ltd, Kanata, Ontario,
Canada). Monitored channels included bilateral oculograms, 4
electroencephologram channels, electrocardiogram, bilateral anterior tibialis
electromyograms (EMG), chin EMG, body position, video channel, PAP level and flow, and snoring microphone. Nasal/oral and PAP
airflow were measured by thermocouple, thoracic and abdominal respiratory effort
by piezoelectric method, and oxygen saturation (SpO₂) by pulse
oximetry. We analyzed and scored data according to criteria of the American
Academy of Sleep Medicine (9). We defined apnea as cessation of airflow for at
least 10 seconds and hypopnea as a reduction in airflow of at least 30% lasting
at least 10 seconds, accompanied by at least a 4% decrease in oxygen saturation
(9). Rapid eye movement (REM) rebound was defined as 20% or more of sleep time
in REM. In many of our polysomnography studies we used a split-night protocol
consisting of an initial diagnostic study followed by titration of CPAP or
bilevel treatment on the same night. (CPAP maintains a constant minimal airway
pressure throughout the respiratory cycle whereas bilevel treatment oscillates
between a higher inspiratory pressure to maintain airway patency and a lower
expiratory pressure to facilitate exhalation. Both are forms of positive airway
pressure.) Patients with OSA who did not complete a split-night protocol because
of an insufficient number of events, too little sleep, or too little REM sleep
during the first half of the night returned for a titration study on another
night.

Abstracted polysomnography data included total sleep time; sleep latency; REM
latency; percentage of sleep achieved in stages 1, 2, 3-4, and REM; number of
central, obstructive, and mixed apneas; number of hypopneas; REM-related AHI;
and minimal SpO₂. If treatment was initiated, we reviewed these same
values as well as AHI at optimal treatment pressure. We obtained patient medical
history and information on comorbid conditions (ie, hypertension, coronary
artery disease, congestive heart failure, atrial fibrillation, pulmonary
hypertension, type 2 diabetes, cardiovascular accidents, and transient ischemic
attacks) from the Cincinnati VAMC electronic medical record. We reviewed all
clinical reports from postpolysomnography encounters to assess the patient’s
adherence to treatment and response to therapy. We graded adherence according to
the following criteria: “good,” patient reported use of positive pressure
equipment for 3 or more nights weekly; “partial,” patient reported use of
equipment for fewer than 3 nights weekly; “not adherent,” no use of equipment;
and “not specified/no data,” patient had not returned to the sleep clinic for
follow-up or there were no comments regarding adherence in other clinical notes.
For veterans with good adherence, we graded the response to treatment according
to the following criteria: “excellent,” complete or near complete relief of
pretreatment sleep-related symptoms, greatly improved energy and alertness, and
more restful sleep; “moderate,” relief of most sleep-related symptoms but
persistent daytime somnolence or fatigue and inconsistently restorative sleep;
“no change,” persistence of nearly all sleep-related symptoms; and “not
specified/no data,” patients had not returned to the sleep clinic for follow-up
or there were no comments regarding sleep-disordered breathing in records of
other clinical encounters.

Because of the high prevalence of severe OSA, we performed further
comparisons to determine whether patients with ultrasevere OSA (AHI >60
events/h, 1 respiratory event/min) could be distinguished from those with less
severe OSA (AHI 31-60 events/h).

Statistical analysis

We calculated mean, standard deviation (SD), standard error of the mean, and
confidence intervals for continuous variables. Differences between the
categorical OSA groups and continuous variables were analyzed by using 1-way
ANOVA with the Bonferroni test for multiple comparisons. We calculated
categorical variables as frequencies or proportions and analyzed them using χ
² testing with the Marascuilo procedure for multiple comparisons. We
defined significant differences as
P < .05. We performed all statistical analyses with GraphPad Prism 5.0
statistical software (GraphPad, La Jolla, California).

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Results

Patients were predominantly male (559 of 596 [94%]), with a mean (SD) age of
56.0 (11.6) years. Polysomnography demonstrated OSA in 76% of patients; 30% had
mild OSA, 23% moderate OSA, and 47% severe OSA. Increasing BMI, neck
circumference, ESS scores, hypertension, congestive heart failure, and type 2
diabetes correlated with increasing OSA severity (Table
1).

Among the OSA patients, the REM-related AHI rose and the SpO₂
declined as OSA severity increased (Table
2).

Treatment was initiated for 81% of the patients with OSA; 73% of patients
received CPAP and 27% received bilevel therapy. With CPAP, the proportion of
patients with REM rebound increased with increasing OSA severity; one-third of
patients with severe OSA experienced REM rebound (Table 2). More than 10% of
patients did not tolerate CPAP (pulled off the mask during the study or
requested removal of the mask), and treatment adherence did not vary with OSA
severity. The AHI declined dramatically with successful CPAP for all patients
with OSA, and the posttreatment AHI was lower in the mild group compared with
the severe group. The optimal levels of CPAP and inspiratory and expiratory
bilevel pressures rose with increasing OSA severity.

Adherence and outcomes

Follow-up information about adherence to treatment was available for 291 of
the 368 treated patients (79%). Of the 291, 172 patients (59%) reported using
their CPAP or bilevel equipment at least 3 nights weekly, and 27 of 100 (27%)
patients with severe OSA reported an excellent response compared with 0 of 40
patients with mild OSA (Table 3).

Ultrasevere and less severe OSA

Patients with more than 30 AHI events per hour (n = 211) were divided into
less severe (n = 99) and ultrasevere (n = 112) categories. More patients with
ultrasevere OSA reported a history of observed apnea events, a higher BMI, and
concurrent coronary artery disease and pulmonary hypertension than did patients
with less severe OSA. Although the minimal SpO₂ was less in the
ultrasevere group, other polysomnographic findings, treatments, adherence, and
outcomes were similar in the 2 groups.

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Discussion

In our study group of 596 patients who underwent complete diagnostic
polysomnography testing, 76% had OSA. Of these, 30% had mild, 23% moderate, and
47% severe OSA. BMI, neck circumference, and ESS score increased with worsening
OSA severity, as did cardiovascular and metabolic comorbidities. Most patients
were treated for OSA, but only 59% reported good adherence with positive
pressure therapy. More adherent patients with severe OSA than with mild or
moderate disease reported an excellent response to treatment. Finally, despite a
higher proportion of patients with severe OSA, we were unable to determine
clinical or polysomnographic features that distinguished less severe OSA from
ultrasevere OSA.

Previous studies within the VHA have shown that 34% to 47% of veterans
attending outpatient clinics are at increased risk for OSA (7,8). In 1983, a
preliminary study of 27 randomly selected inpatients at the San Diego VAMC who
underwent portable polysomnography monitoring of 4 channels (thoracic and
abdominal respiratory effort, lower-extremity electromyogram, and wrist
actigraphy) in their hospital beds demonstrated that 7 (27%) had sleep apnea,
defined as 30 or more apneas per hour (13). Subsequent studies at the same
institution using the same study protocol found that 84% of 436 randomly
selected inpatients had an AHI greater than 5 in 1991, and 53% of 186 inpatients
had an AHI greater than 15 in 2003 (14,15). In contrast, a review of the first
117 patients undergoing polysomnography by the same group in the San Diego Sleep
Disorders Clinic showed that 44% had sleep apnea (16). Approximately one-fourth
(46 of 192) of Persian Gulf War veterans self-referred to the Comprehensive
Clinical Evaluation Program at Fort Sam Houston had histories suggesting a sleep
disorder; polysomnography demonstrated OSA (defined as a respiratory disturbance
index of ≥15 events/h) in 33% of these veterans (17). Differences in technology,
study protocols including the tested population, and definition of OSA make it
difficult to compare these reports with our study, which demonstrated OSA (AHI ≥5 events/h) in 76% of veterans undergoing polysomnography, 47% of whom had
severe OSA (AHI >30 events/h).

Based on previous estimates of the proportion of the veteran population that
is at increased risk of OSA (34%-47%) (7,8) and our polysomnography results (76%
with demonstrated OSA, 47% of whom had severe OSA), approximately 26% to 36% of
veterans served by the VHA would be diagnosed with OSA, and 12% to 17% would
have severe OSA if all veterans at increased risk for sleep disordered breathing
completed diagnostic polysomnography testing. In a review of VHA administrative
databases from 1998 to 2001, Sharafkhaneh and colleagues (18) found that the
prevalence of coded and documented diagnosed OSA was 2.9%. Thus, sleep apnea may
be underrecognized and underdiagnosed in veterans receiving care in the VHA
system, and possibly only 1 of every 5 to 10 veterans with OSA is diagnosed.
Prospective, multicenter epidemiologic studies are needed to determine the
precise prevalence and severity of OSA among veterans served by the VHA.

Previous population-based studies suggest that 15% to 32% of men in the
general American population have OSA and that the prevalence of severe OSA is
approximately 5% (1). These prevalence calculations are very similar to our
estimated prevalence of OSA and severe OSA in the national veteran population,
26% to 36% and 12% to 17%, respectively. These national studies include people
aged 20 to 99 and, since the prevalence of OSA appears to begin to increase with
age in midlife, may not be comparable to the national veteran population (1).
Furthermore, the veteran population may have a higher prevalence of factors
associated with the development and progression of OSA, such as excess body
weight, smoking, alcohol consumption, and nasal congestion (1). Thus, comparison
of the veteran population with an age-, sex-, and risk-factor–matched cohort
from the general American population is required to determine whether the
prevalence and severity of OSA are the same in both groups.

In our study, BMI, neck circumference, and ESS score correlated positively
with AHI. Participants in the Sleep Heart Health Study (SHHS) who had an AHI of
15 or more were significantly more likely to have an increased BMI, neck
circumference, and breathing-pause frequency (2). The SHHS did find a
correlation between habitual snoring and loud snoring and AHI of 15 or more,
which we did not see in our study (2). Of all the patient attributes evaluated
in the SHHS, self-reported, frequent apneas (>3 nights/wk) occurred most
frequently among those with an AHI of 15 or more (49%), but this finding alone
was only minimally predictive of OSA (2). BMI and neck circumference are strong
predictors of OSA, whereas self-reported apneas, ESS values, and frequent, loud
snoring predict OSA severity (2,19).

In 118,105 veterans diagnosed with OSA, metabolic and cardiovascular
comorbidities occurred frequently: diabetes in 32.9%, obesity in 30.5%,
hypertension in 60.1%, cardiovascular disease in 27.6%, congestive heart failure
in 13.5%, and cerebrovascular accident in 5.7% (17). In our study, the
prevalence of hypertension, congestive heart failure, and type 2 diabetes
correlated with OSA severity. Large studies have shown a positive association
between hypertension and OSA severity (1,20). In a study of nearly 2,300 people
in China undergoing polysomnography, AHI was linearly related to systolic and
diastolic blood pressure up to an AHI of 60 (19). Others have also shown that
the prevalence of diabetes increases with the severity of OSA (21).

The minimal measured SpO₂ declined with increasing OSA severity.
Various indices of nocturnal oxygen saturation have been shown to correlate with
and predict AHI (22,23). Lin and colleagues (23) showed that the oxyhemoglobin
desaturation index was the most sensitive and specific measure of oxygenation
for all levels of OSA.

For many patients, apneas and hypopneas can be more prominent during REM
sleep (24). A Japanese study found that patients with an AHI of 60 or more were
significantly more likely to have a higher AHI in non-REM sleep than in REM
sleep, whereas among patients with less severe disease, the relationship was
reversed (25). Another investigation showed that half of patients with OSA have
a higher non-REM AHI than REM AHI (26). The REM-related AHI correlated with AHI
and increased most dramatically when AHI was greater than 60 events per hour.

Our study showed that patients with severe OSA were slightly more likely to
adhere to CPAP treatment, a finding similar to that of other investigations
(27,28). In our study, 53% of patients with severe OSA had good adherence to
treatment, whereas only 39% of those with mild OSA reported using their
equipment more than 3 nights weekly. Adherence to CPAP use is better in people
with more daytime sleepiness regardless of OSA severity (10,29). The ESS score,
a measure of excessive daytime sleepiness, was significantly higher in patients
with more severe OSA, suggesting that these patients were more symptomatic and
may have experienced more symptom improvement with treatment. The higher
proportion of excellent response to treatment among Cincinnati VMAC patients
with severe OSA corresponds to results of previous studies that found
significant associations between the resolution of symptoms with CPAP treatment
and improved treatment adherence (30,31).

This study was a retrospective review of polysomnography studies at a single
center, the Cincinnati VAMC sleep center. Patients with more severe
sleep-related symptoms may have been preferentially referred for sleep
evaluation, resulting in higher prevalence and severity of OSA. Only completed
diagnostic polysomnography studies were analyzed; including patients who did not
complete testing and may not have had OSA would reduce the OSA diagnosis rate.
In most of the patients we studied, we used a split-night polysomnography
protocol that may have underestimated the presence and severity of OSA. Another
limitation was the use of self-reporting for adherence assessment. Although
patients’ CPAP and bilevel units were examined for the numbers of hours used per
night, this evaluation was not performed consistently, and there were
insufficient data for analysis. Finally, the severity of hypertension and
treatment for hypertension at the time of the polysomnography study were not
documented. Only the presence or absence of a hypertension diagnosis was noted.

On the basis of our data and on previous surveys of the prevalence of
patients at high risk for OSA within the VHA, we estimate the prevalence of OSA
to be 26% to 36% of veterans cared for by the VHA, and the prevalence of severe
OSA to be 12% to 17%. Metabolic and cardiovascular comorbidities occurred
frequently in veterans with OSA, and the prevalence of these disorders increased
with OSA severity. Only 59% of treated patients at the Cincinnati VAMC reported
good adherence with CPAP treatment, and within this group, response to therapy
increased as OSA severity worsened.

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Acknowledgments

Ms Samson was supported by a research grant from the National Review
Committee for the Medical Student Training in Aging Research (MSTAR) Program of
the American Federation for Aging Research.

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Author Information

Corresponding Author: Ralph J. Panos, MD, Pulmonary, Critical Care, and Sleep
Division, Cincinnati Veterans Affairs Medical Center, Cincinnati, OH 45220.
Telephone: 513-861-3100. E-mail:
Ralph.Panos@va.gov.

Author Affiliations: Pamela Samson, Washington University in St. Louis School
of Medicine, St. Louis, Missouri; Kenneth R. Casey, Cincinnati Veterans Affairs
Medical Center, Cincinnati, Ohio; James Knepler, University of Arizona, Tucson,
Arizona. At the time of this study, Ms Samson and Dr Knepler were affiliated
with the Cincinnati Veterans Affairs Medical Center, Cincinnati, Ohio.

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Table
1. Clinical Characteristics of Veterans (N = 596) With Obstructive Sleep
Apnea, Cincinnati Veterans Affairs Medical Center, 2005-2007

Abbreviation: SD, standard deviation; BMI, body mass index.

^a None, apnea-hypopnea index (AHI) <5; mild, AHI 5-14; moderate, AHI
15-30; severe, AHI >30.

^b ANOVA with Bonferonni correction was used to compare continuous
values and χ² test with Marasculio procedure was used to compare
proportional variables.

^c None vs severe.

^d Johns (12).

^e None vs severe, mild vs severe, moderate vs severe.

^f Data were not available for all patients; n = number of patients
with this information.

^g None vs mild, moderate, and severe.

Table
2. Polysomnographic Findings and Treatment of Patients With Obstructive
Sleep Apnea (N = 596), Cincinnati Veterans Affairs Medical Center, 2005-2007

Abbreviations: AHI, apnea-hypopnea index; SD, standard
deviation; NA, not applicable; REM, rapid eye movement; SpO₂, pulse oximetry oxygen
saturation; CPAP, continuous positive airway pressure.

^a None, AHI <5; mild, AHI 5-14; moderate, AHI 15-30; severe, AHI >30.

^b ANOVA with Bonferonni correction was used to compare continuous
values, and χ² test with Marasculio procedure was used to compare
proportional variables.

^c Mild vs moderate and severe.

^d Mild vs severe, moderate vs severe.

^e Treatment data are only for patients with OSA.

^f Mild vs severe.

^g REM rebound was defined as 20% of sleep time in REM; no. is the
number of patients with data concerning REM rebound. Data were not available for
all patients; n = number of patients with this information.

Table
3. Adherence of Patients With Obstructive Sleep Apnea (n = 368) Treated With
Positive Airway Pressure and Response in Patients with Good Adherence to
Treatment (n = 172), Cincinnati Veterans Affairs Medical Center, 2005-2007

^a None, AHI <5; mild, AHI 5-14; moderate, AHI
15-30; severe, AHI >30.

^b  χ² test with Marasculio procedure was used to compare
proportional variables.

^c Good, self-reported use of positive pressure equipment for ≥3
nights weekly; partial, self-reported use of equipment <3 nights weekly; not
adherent, no use of equipment; not specified/no data, patient did not return to
the sleep clinic for follow-up or there were no comments regarding adherence in
other clinical notes.

^d Excellent, complete or near complete relief of pretreatment
sleep-related symptoms, greatly improved energy and alertness, and more restful
sleep; moderate, relief of most sleep-related symptoms but persistent
daytime somnolence or fatigue and inconsistently restorative sleep; no change,
persistence of nearly all sleep-related symptoms; not specified/no data,
patients did not return to the sleep clinic for follow-up or there were no
comments regarding sleep disordered breathing in other clinical notes.

^e Mild vs severe.