Disability Benefits Questionnaires

[john999]

I had a C&P for an increase in DMII. I think my exam doctor just said that since I am on oral meds for control of glucose levels I should get 20%. If he filed out a disability questionnaire I did not see it and he signed the exam while I was there. He did not ask me about the two secondary conditions I have due to DMII. I guess I have to file for increase on them separately? Has anyone heard of Sleep Apnea secondary to DMII? Really, I wonder what kind of exam you get for DMII when the doctor does not ask about the obvious secondary conditions? I did not think he was personally hostile to me but just negligent. He only asked if I had been hospitalized due to the DMII. This is the guy who believes many vets get fat just to get higher DMII ratings.

John

[Veldrina]

John, sleep apnea (SA) is not a known complication of DMII. SA would have to be show either in service or have medical evidence linking it to another condition.

JewBacha, with the new relaxed criteria under "Changing the Game" & Waters vs Shinseki & Walker vs Shinseki, the DBQs should not have an expiration & as long as they answer the questions needed (have the rating criteria) it should be good.

Captdc, I dont know about Dr. Siy, but it sounds like you were turned down for pension, not compensation. Pension is income-based, compensation is not. Do you have any s/c disabilities currently or are u still waiting because u filed? If you want, PM me & I can try to look up how they're doing.

[etihwr]

I disagree with Veldrina. You can go to the web site docguide.com and set yourself up as an administrator and do a search between Sleep Apnea and Diabetes Below is one such study. You can then use this study to have a NEXUS letter written to show the link between the two. there are several studies out there that support the link.

Impact of Untreated Obstructive Sleep Apnea on

Glucose Control in Type 2 Diabetes

Renee S. Aronsohn

1, Harry Whitmore1, Eve Van Cauter1, and Esra Tasali1

1

Department of Medicine, University of Chicago, Chicago, Illinois

Rationale

: Obstructive sleep apnea (OSA), a treatable sleep disorder

that is associated with alterations in glucose metabolism in individuals

without diabetes, is a highly prevalent comorbidity of type 2

diabetes. However, it is not known whether the severity of OSA is a

predictor of glycemic control in patients with diabetes.

Objectives

: To determine the impact of OSA on hemoglobin A1c

(HbA1c), the major clinical indicator of glycemic control, in patients

with type 2 diabetes.

Methods

: We performed polysomnography studies and measured

HbA1c in 60 consecutive patients with diabetes recruited from

outpatient clinics between February 2007 and August 2009.

Measurements and Main Results

: A total of 77% of patients with diabetes

had OSA (apnea–hypopnea index [AHI]

>5). Increasing OSA

severity was associated with poorer glucose control, after controlling

for age, sex, race, body mass index, number of diabetes medications,

level of exercise, years of diabetes and total sleep time.

Compared with patients without OSA, the adjustedmeanHbA1cwas

increased by 1.49% (

P 5 0.0028) in patients with mild OSA, 1.93%

(

P50.0033) in patients with moderate OSA, and 3.69% (P,0.0001)

in patients with severeOSA(

P,0.0001 for linear trend). Measures of

OSA severity, including total AHI (

P 5 0.004), rapid eye movement

AHI (

P50.005), and the oxygen desaturation index during total and

rapid eye movement sleep (

P 5 0.005 and P 5 0.008, respectively)

were positively correlated with increasing HbA1c levels.

Conclusions

: In patients with type 2 diabetes, increasing severity of

OSA is associated with poorer glucose control, independent of

adiposity and other confounders, with effect sizes comparable to

those of widely used hypoglycemic drugs.

Keywords:

sleep disordered breathing; glycemic control; diabetes

Given the enormous public health burden of the type 2 diabetes

epidemic, and growing concerns about the safety profiles of current

pharmacologic treatments (1, 2), a better understanding of

the impact of comorbidities on glucose control is needed to

develop additional preventive and therapeutic strategies. Obstructive

sleep apnea (OSA) is a treatable sleep disorder characterized

by repetitive upper airway closures, leading to oxygen

desaturations and sleep fragmentation. OSA has been identified

as a highly prevalent comorbidity of type 2 diabetes (3–5). In

particular, among obese patients with type 2 diabetes, who

represent the vast majority of individuals with type 2 diabetes

in the United States, the prevalence has recently been estimated

at a staggering 86% (5).

OSA is a well documented risk factor for cardiovascular

disease and mortality (6–9). Multiple epidemiologic and clinical

studies have revealed that individuals without diabetes suffering

from OSA show alterations in glucose metabolism, including

insulin resistance and impaired glucose tolerance, independent

of adiposity (10–13).

Despite these independent associations between OSA and

abnormal glucose metabolism and the high prevalence of OSAin

patients with type 2 diabetes, data on whether the presence and

severity of OSA compromises glycemic control in patients with

type 2 diabetes is lacking. The majority of patients with type 2

diabetes need multiple drugs, in addition to lifestyle modifications,

to control glucose levels and avoid or delay the development

of serious complications (14). Currently, both physicians

and patients are challenged by rising concerns about the safety

of widely used pharmacologic treatment options. Therefore, determining

whether OSA has an adverse effect on glucose control

in patients with diabetes has major clinical implications, because

effective treatment of OSA could be a nonpharmacologic strategy

to improve glucose control in the management of millions of

patients with type 2 diabetes.

In the present study, we therefore evaluated the impact of

untreated OSA on hemoglobin A1c (HbA1c), the major clinical

indicator of glycemic control, in patients with type 2 diabetes.

Preliminary findings from this study have been previously reported

in abstract form (15, 16).

METHODS

Participants and Study Design

Patients with type 2 diabetes were consecutively recruited by one of

the study investigators (R.S.A.), from the Primary Care and Endocrinology

Clinics at the University of Chicago between February 2007 and

August 2009. Sleep complaints or symptoms of OSA were not used as

selection criteria. All participants were on stable medications for diabetes

and other comorbidities for the preceding 3 months. Subjects were

excluded if they: failed to meet the criteria for type 2 diabetes, based on

physician diagnosis, in accordance with established guidelines (14); had

unstable cardiopulmonary, neurological, or psychiatric disease; upper

airway surgery; or used nocturnal oxygen, positive airway pressure

AT A GLANCE COMMENTARY

Scientific Knowledge on the Subject

Obstructive sleep apnea (OSA) is associated with alterations

in glucose metabolism in non-diabetic individuals

and is a highly prevalent co-morbidity of type 2 diabetes,

but its effect on glycemic control in patients with diabetes

was not known.

What This Study Adds to the Field

In patients with type 2 diabetes, there is a robust graded

relationship between the severity of OSA and glycemic

control.

(

Received in original form September 22, 2009; accepted in final form December 11, 2009)

Supported by the National Institute of Health grants P01 AG11412 (E.V.C.), R01

HL086459 (E.T.), UL1RR024999, and P60 DK20595, and grants from the

American Academy of Sleep Medicine/Pfizer Scholars Grant in Sleep Medicine,

and the ResMed Foundation.

Correspondence and requests for reprints should be addressed to Renee

Aronsohn, M.D., Department of Medicine, MC 1027, University of Chicago,

5841 South Maryland Avenue, Chicago, IL 60637. E-mail: raronsoh@medicine.

bsd.uchicago.edu

Am J Respir Crit Care Med Vol 181. pp 507–513, 2010

DOI: 10.1164/rccm.200909-1423OC

Internet address: www.atsjournals.org

therapy, or oral appliances. The study was approved by the University of

Chicago Institutional Review Board, and all participants gave written

informed consent.

During a 45-minutes interview, each patient completed surveys,

including the University of Chicago Diabetes/Quality of Life Survey

(17) (which includes self-report of medications, presence of diabetic

complications [retinopathy, nephropathy, neuropathy, coronary artery

disease, and peripheral vascular disease], and level of exercise [no

5

rarely, mild

5once or twice a week, moderate5three times a week, and

heavy

5 more than three times a week]), the Berlin Questionnaire (18)

(used to assess the presence of snoring), and the Center for Epidemiologic

Studies Depression Scale (19) (score

>16 indicates depression).

Height and weight were measured in all patients. Waist circumference

was measured in 58 patients. Subjects underwent 5 consecutive days of

ambulatory wrist actigraphy to determine habitual sleep habits. An

overnight laboratory polysomnogram (PSG) was then performed to

establish the presence and severity of OSA. Bedtimes in the laboratory

were individually designed based on the subject’s usual habits derived

from actigraphy. However, each subject was recorded for a minimum of

7 hours. HbA1c values (%, defined as the proportion of hemoglobin that

is glycosylated) were obtained from the patient’s chart if assessed during

the previous 3 months, or a single blood sample was drawn on the

morning after PSG. HbA1c was measured by Bio-Rad Variant Classic

boronate affinity-automatedHPLC(Bio-Rad, Hercules, CA). The intraassay

coefficient of variation was 0.5–1.0%, and the interassay coefficient

of variation ranges from 2.2–2.4%.

Polysomnography

PSG (Neurofax EEG 1100 system; Nihon Kohden, Foothill Ranch, CA)

included recordings of six electroencephalogram channels, bilateral

electro-oculograms, chin and tibialis electromyogram, electrocardiogram,

airflow by nasal pressure transducer and oronasal thermocouples,

chest and abdominal wall motion by piezo electrodes, and oxygen

saturation by pulse oximeter. Recordings were visually scored in 30

seconds in stages 1–4 of non–rapid eye movement (REM) sleep and in

REM sleep, according to standard criteria (20). Respiratory events and

microarousals were scored according to established criteria (21, 22).

Total cessation of airflow for at least 10 seconds was defined as apnea

(obstructive if respiratory efforts were present and central if respiratory

efforts were absent). Hypopneas were identified if there was a discernable

reduction in airflow lasting at least 10 seconds and associated with at

least3%desaturation. The apnea–hypopnea index (AHI) was defined as

the total number of obstructive apneas and obstructive hypopneas per

hour of sleep. OSA severity categories were defined according to

commonly used clinical cutoffs as follows: no OSA (AHI

,5); mild

OSA(AHI

>5 but,15); moderateOSA(AHI>15 but,30); and severe

OSA(AHI

>30). Total oxygen desaturation index (ODI) was defined as

the total number of desaturations of at least 3% per total sleep time in

hours. REM ODI was defined as number of desaturations of at least 3%

duringREMsleep perREMsleep time in hours. The microarousal index

was calculated as the total number of microarousals per hour of sleep.

Actigraphy

Habitual sleep duration was assessed at home by actigraphy using the

Actiwatch (Mini-Mitter, Bend, OR) in accordance with previously

described methods (23–25). Participants were asked to wear the Actiwatch

for 5 consecutive days—3 weekdays and 2 weekend days—and

to maintain their habitual bedtimes and fill out daily sleep logs. Of the

60 subjects who were included in the final analysis, 50 (83%) wore the

Actiwatch for all 5 days, 7 (12%) wore the Actiwatch for 4 days, and 2

(3%) wore the Actiwatch for 3 days. One subject’s data could not be

downloaded due to a technical failure, thus data on habitual sleep

duration are reported in 59 subjects.

Statistical Analysis

Group data are expressed as means (

6SD). Variables were examined for

normality, and, if skewed, the log-transformed values were used. All

categorical data were compared by Pearson’s

x2 test. Pair-wise comparisons

of continuous variables in patients with and without OSA were

examined by

t test and confirmed by the nonparametric Mann-Whitney

test. Unadjusted group differences across OSA severity categories were

assessed by analysis of variance. A linear contrast was used to test for

trends.We performed multivariate regression analyses to characterize the

independent associations between measures of OSA severity and the

primary outcome variable, HbA1c. The primary independent predictor

was the OSA severity category, and we also examined total AHI, REM

AHI, totalODI, andREMODI.Potential confounding variables included

in all multivariable models as covariates were: age; sex; race; body mass

index (BMI);number of diabetesmedications; level of exercise; years since

diabetes diagnosis; and total sleep time by PSG.After log transformation,

the distribution of HbA1c values remained skewed due to one outlier

subject, thus a sensitivity analysis excluding this outlier value was

performed and confirmed the significance of the association between

severity ofOSA andHbA1c.We also performed sensitivity analyses using

waist circumference as covariate (instead of BMI) in all multivariate

models. Data are presented in non–log-transformed values for ease of

interpretation. All statistical analyses were performed using JMP version

6.0.3 statistical software (SAS Institute, Cary, NC). All reported

P values

are two sided.

RESULTS

Figure 1 shows the flow diagram of patient recruitment and selection.

Patients who obtained less than 4 hours of total sleep time

during the PSG, thus preventing accurate assessment of the

degree of severity of OSA, were not included in the analysis

(

n 5 6). One patient showed severe oxygen desaturations not

explained by apneas or hypopneas (thus consistent with significant

hypoventilation) and, in another patient, the PSG data could

not be interpreted due to multiple artifacts in the airflow signal.

Thus, 60 patients were included in the final analysis.

Table 1 summarizes the demographic characteristics of the

cohort, which comprised similar proportions of men and women

and of whites and African Americans. The age range was 41–77

years. The BMI range was 20–57 kg/m

2. The sample included

7 lean, 14 overweight, and 39 obese patients.

A total of 46 of the 60 patients (77%) had OSA (AHI

>5).

Only five patients had been previously evaluated for OSA, and

none were receiving treatment. Mild, moderate, and severe

OSA was found in 38.3% (

n 5 23), 25.0% (n 5 15), and 13.3%

(

n 5 8) of the sample, respectively.

Compared with patients without OSA, those with OSA were

heavier and 6 years older on average (Table 1). Increasing

severity of OSA was associated with increasing BMI (unadjusted

Figure 1.

Participant flow diagram

508 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 181 2010

P

5 0.00042 for linear trend) and greater waist circumference

(unadjusted

P 5 0.00038 for linear trend). Patients without OSA

had fewer diabetic complications than those with OSA. Out of

60 patients, 6 (10%) did not take any diabetes medications (i.e.,

insulin, oral agents, or incretin-based therapies), 18 (30%) were

on 1 medication, 24 (40%) were on 2 medications, 11 (18%) were

on 3 medications, and 1 (2%) patient was on 4 medications. Out of

60 patients, 20 (33.3%) reported no exercise, 11 (18.3%) reported

mild exercise, 14 (23.3%) reported moderate exercise, and 15

(25.0%) reported heavy exercise.

Sleep characteristics are summarized in Table 2. Habitual

sleep duration was not significantly different between patients

with and without OSA. In the laboratory, patients with OSA

had shorter total sleep duration, decreased sleep efficiency, increased

wake time after sleep onset, and less REM sleep than

those without OSA. Increasing severity of OSA was associated

with lower amounts of REM sleep (unadjusted

P 5 0.012 for

linear trend), more stage 1 sleep (unadjusted

P 5 0.007 for

linear trend), and more sleep fragmentation as assessed by the

microarousal index (unadjusted

P 5 0.0001 for linear trend).

The predominant respiratory disturbances were obstructive

apneas and hypopneas, rather than central apneas.

Increasing severity ofOSAwas associated with poorer glucose

control after controlling for age, sex, race, BMI, number of diabetes

medications, level of exercise, years of diabetes, and total

sleep time on PSG (

P , 0.0001 for linear trend). Figure 2 shows

the adjusted mean values of HbA1c in each OSA category.

Compared with patients without OSA, the adjusted mean HbA1c

was increased by 1.49% (

P 5 0.0028) in patients with mild OSA,

1.93% (

P 5 0.0033) in patients with moderate OSA, and 3.69%

(

P , 0.0001) in patients with severe OSA (P , 0.0001 for linear

trend). Associations between OSA severity and HbA1c levels

remained robust when ‘‘number of diabetes medications’’ was

replaced by ‘‘oral hypoglycemic medication use’’ (

P , 0.0001 for

linear trend) or ‘‘insulin use’’ (

P 5 0.0002 for linear trend) in the

regression model. Similar associations between the severity of

OSA and glycemic control were found when the presence of

diabetic complications was added to the regression model (

P ,

0.0001 for linear trend). A sensitivity analysis including waist

circumference (instead of BMI) in the regression model also

showed similar linear associations between increasing severity of

OSA and higher HbA1c levels (

P 5 0.0001 for linear trend).

Other measures of OSA severity, including total AHI (

P 5

0.004), REM AHI (

P 5 0.005), total ODI (P 5 0.005), and REM

ODI (

P 5 0.008), were positively correlated with increasing

HbA1c levels after adjusting for age, sex, race, BMI, number of

diabetes medications, level of exercise, years of diabetes, and

total sleep time on PSG.Wedid not detect significant associations

between HbA1c levels and the microarousal index (

P 5 0.75) or

the amount of slow wave sleep (

P 5 0.67) after adjusting for age,

sex, race, BMI, number of diabetes medications, level of exercise,

years of diabetes, and total sleep time.

DISCUSSION

The present study indicates that OSA is highly prevalent in

patients with type 2 diabetes, and demonstrates, for the first time,

a clear, graded, inverse relationship between OSA severity and

glucose control in patients with type 2 diabetes, after controlling

for the degree of adiposity and multiple other potential confounders.

A total of 46 of our 60 subjects (77%) had OSA. In

nearly 90% of these patients, the presence of OSA had not been

previously evaluated. Relative to patients without OSA, the

presence of mild, moderate, or severe OSA increased mean

adjusted HbA1c values by 1.49, 1.93, and 3.69%, respectively.

These effect sizes are comparable to, if not exceeding, those of

TABLE 1. SAMPLE CHARACTERISTICS: PATIENTS WITH DIABETES ACCORDING TO OBSTRUCTIVE

SLEEP APNEA STATUS

All Patients Patients without OSA Patients with OSA

Characteristic (

n 5 60) (n 5 14) (n 5 46) P Value*

Age, yr 57.0

6 9.2 52.4 6 7.6 58.4 6 9.2 0.03

Male sex, % 45 43 46 0.85

Race, %

African American 58 64 57

White 42 36 43 0.61

BMI, kg/m

2 33.8 6 7.7 28.9 6 5.8 35.3 6 7.6 0.005

Waist circumference, inches

† 43.0 6 6.6 39.8 6 5.6 43.9 6 6.6 0.05

HbA1c, % 7.7

6 1.8 7.2 6 1.4 7.8 6 1.9 0.28

Diabetes diagnosis, yr 9.6

6 8.0 9.9 6 9.0 9.6 6 7.8 0.91

Diabetic complications, %

† 55 21 65 0.004

Diabetic medications, %

†

Insulin 35 50 30 0.18

Oral hypoglycemic 76 71 78 0.60

Incretin based 20 14 22 0.54

Exercise, %

† 67 79 63 0.28

Hypertension, %

† 70 64 72 0.59

Depression, %

† 35 21 39 0.22

Snoring* 33 32 21 0.42

Definition of abbreviations:

BMI 5 body mass index (calculated as weight in kilograms divided by height in meters

squared); HbA1c

5 hemoglobin A1c; OSA 5 obstructive sleep apnea defined by five or more obstructive apneas and

hypopneas per hour of sleep.

Data are given as mean

6 SD or percentage.

*

P values for unadjusted comparisons between patients with and without OSA are determined by t test for continuous

variables or Pearson’s

x2 test for categorical variables.

†

Data forwaist circumference are reported in n558 subjects; presence of diabetic complications is based on self-report of

one or more of the following: retinopathy, nephropathy, neuropathy, coronary artery or peripheral vascular disease; use of all

diabetic medications are dichotomous variables (yes or no) by self-report; use of oral hypoglycemic agents is defined as use of

at least one of the following medications: metformin, sulfonylurea, thiazolidinedione; exercise is a dichotomous variable

(yes or no) based on self-report of exercising at least one to two times per week; the presence of hypertension is based on

either self-report and/or use of medications; presence of snoring is by self-report using the Berlin Questionnaire.

Aronsohn, Whitmore, Van Cauter,

et al.: Sleep Apnea and Type 2 Diabetes 509

widely used hypoglycemic medications (26–28). Our findings

have important clinical implications, as they support the hypothesis

that reducing the severity of OSA may improve glycemic

control. Thus, effective treatment of OSA may represent a novel

nonpharmacologic intervention in the management of millions of

patients with type 2 diabetes.

Obstructive apneas and hypopneas were more frequent during

REM sleep than during other sleep stages, indicating that the

prevalence and the degree of severity of OSA in patients with

type 2 diabetes may be underestimated when recording times

are too short to allow for sufficient amounts of REM sleep to

occur. Our findings contrast with the negative results of the only

previous study that examined associations between the severity of

OSAand HbA1c in patients with type 2 diabetes (4). It is possible

that the lack of association in the previous study was due to the

short duration ofPSGrecording (reported to be as low as 4 h), and

thus perhaps insufficient to detect an association between OSA

severity and HbA1c. In contrast, our study design specified

a minimum duration of PSG recording of 7 hours, and our

subjects achieved 6.6 hours of sleep on average. Of note, in an

exploratory reanalysis of our own data set using only the first 4

hours of recording, the robust relationship between severity of

OSA and HbA1c found with a PSG recording time of at least

7 hours was much weaker. Compared with patients without OSA

(mean adjustedHbA1c

5 7.05%), when only 4 hours of recording

were analyzed, the adjusted meanHbA1c levelswere not different

in patients with mild OSA (mean adjusted HbA1c

5 6.83%; P 5

0.67), moderate OSA(mean adjusted HbA1c

57.79%; P5 0.28),

and severe OSA (mean adjusted HbA1c

5 8.53%; P 5 0.10),

indicating that the shorter duration of PSG recording, which precludes

observing normal amounts of REM sleep, fails to detect

the robust relationship observed with the longer recording time.

These findings highlight the importance of obtaining PSG recordings

longer than the commonly used minimum of 4 hours

to examine associations between OSA severity and metabolic

variables.

Figure 2.

Adjusted mean hemoglobin A1c (HbA1c) values for

patients with no, mild, moderate and severe obstructive sleep

apnea (OSA). Data were adjusted for age, sex, race, body mass

index, number of diabetes medications, level of exercise, years of

diabetes, and total sleep time on polysomnogram.

Bars represent

SEM;

P , 0.0001 for linear trend.

TABLE 2. SLEEP CHARACTERISTICS: PATIENTS WITH DIABETES ACCORDING TO OBSTRUCTIVE

SLEEP APNEA STATUS

All patients Patients without OSA Patients with OSA

Characteristic (

n 5 60) (n 5 14) (n 5 46) P Value*

Actigraphy

Sleep duration, h

† 6.1 6 1.2 5.7 6 1.0 6.2 6 1.3 0.18

Polysomnography

Total sleep time, h 6.6

6 1.1 7.2 6 1.1 6.5 6 1.0 0.02

Sleep efficiency, % 83.1

6 11.6 89.7 6 7.7 81.1 6 11.9 0.01

Sleep latency, min 14.9

6 18.6 9.3 6 7.8 16.7 6 20.5 0.19

Wake after sleep onset, min 66.1

6 50.0 42.0 6 34.0 73.5 6 52.0 0.04

REM, % 22.3

6 7.8 27.0 6 7.2 20.9 6 7.5 0.01

Stage 1 sleep, % 8.5

6 5.3 6.1 6 2.4 9.2 6 5.7 0.06

Stage 2 sleep, % 62.9

6 8.7 59.0 6 9.0 64.1 6 8.3 0.06

Slow wave sleep, % 6.4

6 7.8 7.9 6 8.6 5.9 6 7.5 0.40

Microarousal index per hour of sleep 25.6

6 13.4 20.1 6 10.7 27.3 6 13.8 0.07

Total AHI per hour of sleep 15.2

6 14.8 2.0 6 1.2 19.2 6 14.8 ,0.0001

REM AHI per hour of sleep 27.3

6 21.0 3.4 6 3.4 34.6 6 18.5 0.003

Total obstructive events 96.5

6 89.1 14.8 6 9.1 121.3 6 87.7 ,0.0001

Number of obstructive events in REM sleep 36.5

6 33.9 5.9 6 4.6 45.8 6 33.5 ,0.0001

Total central events 1.7

6 3.8 0.8 6 1.4 2.0 6 4.2 0.30

Total ODI per hour of sleep 11.0

6 12.0 1.1 6 0.6 14.0 6 12.2 0.0002

REM ODI per hour of sleep 22.1

6 18.2 2.3 6 2.2 28.2 6 16.6 , 0.0001

Total no. of desaturations:

>3% 69.7 6 71.5 8.0 6 4.8 88.5 6 71.8 0.0001

No. of desaturations in REM sleep:

>3% 29.1 6 28.3 3.9 6 2.6 36.7 6 28.1 ,0.0001

Definition of abbreviations:

AHI 5 apnea–hypopnea index; ODI 5 oxygen desaturation index; OSA 5 obstructive sleep

apnea defined by five or more obstructive apneas and hypopneas per hour of sleep; REM

5 rapid eye movement.

Data are given as mean

6 SD.

*

P values for unadjusted comparisons between patients with and without OSA are determined by t test for continuous

variables.

†

Data for sleep duration measured by wrist actigraphy are reported in n 5 59 subjects.

510 AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE VOL 181 2010

In our sample,OSAwas characterized by a clear predominance

of obstructive, rather than central, disease. This is in contrast with

findings from the Sleep Heart Health Study (SHHS) (3), in which

self-reported diabetes was associated with a significant increase in

periodic breathing, an abnormality reflecting disruption of central

control of breathing, and a nonstatistically significant increase in

the occurrence of central apneas. By contrast, we did not observe

periodic breathing pattern in any participant in our study. Consistent

with our findings, two previous studies in patients with

diabetes with autonomic neuropathy have reported a high frequency

of obstructive, rather than central, respiratory events (29,

30). The finding of predominantly obstructive disease in patients

with diabetes has important clinical implications, as it would

indicate that the available therapies to improve obstructive

disease, such as positive airway pressure therapy, oral appliances,

and surgical options (31), could have a significant effect on glucose

control in patients with type 2 diabetes and OSA. To date, six

studies, including a total of 120 patients, have examined the impact

of continuous positive airway pressure (CPAP) treatment ofOSA

on measures of glucose tolerance in type 2 diabetes (32–37). The

study by Babu and colleagues (32) involving 25 obese patientswith

diabetes showed beneficial effects of 3 months of CPAP use on

HbA1c and postprandial glucose levels, and two other studies (33,

36) reported improvements in nocturnal glucose levels after

CPAP. Two earlier studies, including only a total of 10 subjects

(34, 35), showed no change in HbA1c levels, but reported improvements

in insulin sensitivity (by hyperinsulinemic eugylcemic

clamps) after 3–4 months of CPAP. The only randomized controlled

study, by West and colleagues (37), which included 20

obese patients with diabetes randomized to the active CPAP arm,

found no effect of active CPAP on HbA1c levels or insulin

sensitivity, but reported significant improvements in sleepiness

measures. Of note, in this study, the average nightly CPAP use

over a 3-month period was only about 3.3 hours. By contrast, the

positive study by Babu and colleagues found that, in patients who

usedCPAP formore than 4 hours per night (average nightly use of

z

6.6 h/night), the reduction in HbA1c levels was strongly correlated

with CPAP use, suggesting that the negative findings on

HbA1c in the study byWest and colleagues could be explained, at

least in part, by low CPAP adherence. It is also possible that the

efficacy of CPAP varies according to the outcome (i.e., sleepiness

versus glucose control), such that the duration and nightly use of

CPAP needed to observe significant benefits may not be the same

for cognitive versus metabolic outcomes.

Our findings regarding the prevalence of OSAin patients with

type 2 diabetes are consistent with those of the most recent and

largest study, the SleepAHEAD(Action for Health in Diabetes)

study, which included 306 obese patients with diabetes, and

reported a prevalence of 86% (5). Two earlier studies had

estimated the prevalence of OSA in patients with type 2 diabetes

using full overnight PSG. First, the SHHS involving older individuals

(about 50%

.65 yr of age), in whom the diagnosis of

diabetes was based on self-report only, found an OSAprevalence

of 58% (3). Furthermore, in the SHHS, the definition of hypopneas

was based on at least 4% desaturation, whereas, in our

study, we used a cutoff of 3% desaturation, which could explain

the difference in prevalence estimations (38). The second study

(4), which did not specify respiratory event definitions, reported

a prevalence of 71%, similar to our findings. Of note, in an

exploratory reanalysis of our data using a definition of hypopneas

based on a minimum of 4% desaturation, the prevalence of OSA

was58%(versus77%with a cutoff of3%desaturation), similar to

that reported in the SHHS. Importantly, the associations between

OSA severity and HbA1c levels that we observed with a cutoff of

3% desaturation remained significant, albeit somewhat weaker,

when the 4% desaturation criterion was used (

P 5 0.007 and P 5

0.013 for total AHI and REM AHI, respectively). These findings

suggest that the reliance on strict criteria in definingOSAmay fail

to detect patients with milder disease who could nonetheless

potentially benefit from treatment.

Our study was not designed to examine the mechanisms

linking OSA and glucose control in type 2 diabetes. Although it

remains possible that hyperglycemia may promote sleep disturbances,

the current evidence supports the hypothesis that OSA,

and its inherent characteristics, such as intermittent hypoxia,

elevated sympathetic nervous activity (39, 40), sleep fragmentation

and low amounts of slow wave sleep (41), and cumulative

sleep loss (42, 43), has adverse effects on glucose tolerance.

Multiple prospective epidemiologic studies have indicated that

short sleep and/or poor sleep quality, as is typical of OSA, is

associated with an increased incidence of diabetes over time (44–

49). In a recent prospective population study, the presence of

moderate to severe OSA was found to be a significant risk factor

for incident diabetes during a 4-year follow-up period (50).

The present study reveals that the majority of patients with

type 2 diabetes have undiagnosed OSA, and that untreated OSA

is associated with poorer glucose control, which may instigate the

need for more intensive pharmacotherapy. Conversely, treating

OSA may have clinically significant beneficial effects on glucose

control and reduce the number of drugs needed and/or their dose

regimen. Pharmacotherapy of type 2 diabetes with drugs that

promote weight gain may have the undesirable consequence of

promoting the development of OSA or exacerbating the severity

of existing OSA, thereby compromising glycemic control and

elevating cardiovascular risk. The high prevalence of OSA and

its cardiovascular consequences in type 2 diabetes may help in

understanding possible adverse effects of antidiabetic pharmacotherapy.

Noteworthy examples are the recent findings of the

Action to Control Cardiovascular Risk in Diabetes and Action in

Diabetes and Vascular Disease trials that examined the impact of

intensive glucose lowering on cardiovascular risk (51, 52). Based

on the data from our study, it is likely that OSA was present in

most participants in both trials, and that this unrecognized comorbidity

may explain the failure of near-normal glucose control

to decrease the incidence of major macrovascular events. Consistent

with a putative role of OSA in these findings, the

ACCORD trial, which had to be terminated early due to unexpected

mortality (particularly from cardiovascular causes), enrolled

participants who were on average 15 kg heavier at baseline

(thus, more likely to have OSA as well as more severe OSA) than

those participating in theADVANCEtrial, which did not observe

increased mortality or higher incidence of cardiovascular disease.

Furthermore, those in the intensive treatment arm of ACCORD

gained substantially more weight (

.10 kg in about one-third of

the patients) than those in the standard therapy arm, whereas the

difference in weight gain between the two treatment arms of

ADVANCEwas less than 1 kg. It is well documented that weight

gain increases the severity of OSA (53, 54) and thus obese participants

in the intensive treatment arm of ACCORD may have

been at increased risk for more severe OSA, and thus at increased

risk for major cardiovascular events and death. Our findings are

also noteworthy in the context of recent reports discussing a

possible link between the use and dose of insulin glargine and

cancer risk (2). Although the evidence is inconclusive, the

questions raised by these reports clearly highlight the importance

of developing additional, nonpharmacologic alternatives to offer

patients with type 2 diabetes.

There is a relentless increase in type 2 diabetes worldwide.

Diligent control of glucose levels is needed to prevent or delay the

development of life-threatening complications. Most patients are

treated with multiple drugs, and a substantial proportion requires

insulin injections. This pharmacotherapy is not without risk, and

Aronsohn, Whitmore, Van Cauter,

et al.: Sleep Apnea and Type 2 Diabetes 511

may promote further weight gain. Our findings indicate that the

role of OSA in the management of type 2 diabetes is in urgent

need of further rigorous assessment. Current practice approaches

should be updated to include systematic evaluation and treatment

of OSA in patients with type 2 diabetes.

Conflict of Interest Statement

: R.S.A. received $50,001–$100,000 as an investigator-

initiated research grant from the ResMed Foundation, more than

$100,001 as an investigator-initiated research grant from Respironics/Philips, and

more than $100,001 (pending) as an investigator-initiated research grant from

Amylin, Inc.; H.W. does not have a financial relationship with a commercial entity

that has an interest in the subject of this manuscript; E.V.C. received more than

$100,001 as an investigator-initiated research grant from Respironics/Philips,

$50,001–$100,000 as an investigator-initiated research grant from the ResMed

Foundation, more than $100,001 (pending) as an investigator-initiated research

grant from Amylin, Inc.; E.T. does not have a financial relationship with

a commercial entity that has an interest in the subject of this manuscript.

Acknowledgment

: The authors would like to acknowledge Kristen Knutson,

Ph.D., for her expertise and assistance in the statistical analysis of this study.

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t least one in three people with Type 2 diabetes mellitus referred to a diabetes centre has symptomatic obstructive sleep apnoea; Storgaard H, Mortensen B, Almdal T, Laub M, Tarnow L; Diabetic Medicine (Apr 2014)

Tags:

• Diabetes
• Sleep Apnoea

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AIMS To investigate the prevalence of symptomatic obstructive sleep apnoea in unselected patients with Type 2 diabetes referred to a tertiary diabetes clinic.

METHODS In a cross-sectional design, all newly referred patients were offered a stepwise screening for obstructive sleep apnoea with: (1) The Berlin questionnaire; then, if indicative: (2) overnight home monitoring with the ApneaLink(®) device. Patients with an apnoea-hypopnoea index ≥ 5/h were offered referral for diagnostic polygraphy and treatment initiation.

RESULTS A total of 200 patients participated (61% men; age 59.6 ± 10.5 years, diabetes duration 8.3 ± 6.3 years and BMI 31.7 ± 6.7 kg/m(2) ). According to the questionnaire, 106 patients showed 'high risk' of obstructive sleep apnoea, and 72 of these were referred to polygraphy based on ApneaLink screening corresponding to a prevalence of symptomatic obstructive sleep apnoea of 39%. Patients with symptomatic obstructive sleep apnoea had significantly higher BMI, poorer glycaemic control and lower plasma HDL cholesterol levels as compared with patients unlikely to have obstructive sleep apnoea. The groups were not different with respect to sex, age, diabetes duration, blood pressure, diabetic complications or medication use. In multiple regression analyses, age, BMI and HDL cholesterol levels were all significant, independent predictors of obstructive sleep apnoea.

CONCLUSIONS At least one third of people with Type 2 diabetes referred to a diabetes clinic in Denmark has symptomatic obstructive sleep apnoea. Our data suggest higher age, a compromised plasma lipid profile and a more obese phenotype in patients with Type 2 diabetes who have obstructive sleep apnoea, highlighting the need to focus on screening and treatment of obstructive sleep apnoea in these patients. This article is protected by copyright. All rights reserved.

Nonalcoholic fatty pancreatic disease and cardio-metabolic risk: is there is a place for obstructive sleep apnea?; Mirrakhimov A; Cardiovascular Diabetology 13 (1), 29 (2014)

Tags:

• Diabetes
• Sleep Apnoea

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BACKGROUND Obstructive sleep apnea is a common disorder acting as a risk factor for the development and progression of cardiometabolic derangements including non-alcoholic fatty liver disease. Recent research data suggest that non-alcoholic fatty pancreatic disease may be a more sensitive marker than non-alcoholic fatty liver disease for early subclinical metabolic risk and may contribute to the progression of subclinical disease to overt type 2 diabetes mellitus.

PRESENTATION OF THE HYPOTHESIS We postulate that obstructive sleep apnea may be a risk factor for non-alcoholic fatty pancreatic disease. It is well known that intermittent hypoxia related to obstructive sleep apnea leads to hormonal derangements. Excessive lipolysis, enhanced lipid synthesis and systemic and local inflammation may favor ectopic fat deposition similarly to non-alcoholic fatty liver disease. Furthermore, it is possible that obstructive sleep apnea can lead to pancreatic beta cell damage via intermittent hypoxia.

TESTING OF THE HYPOTHESIS Future research should focus on the following: first, whether non-alcoholic fatty pancreatic disease is an independent risk factor for the development of metabolic disease including diabetes mellitus or is a simple consequence of obesity; second, the prevalence of non-alcoholic fatty pancreatic disease among people with obstructive sleep apnea and vice versa, which should be compared to the prevalence of these diseases in general population; third, whether coexistence of these conditions is related to greater cardiometabolic risk than either disease alone; and fourth, whether the treatment of obstructive sleep apnea will translate into the resolution of non-alcoholic fatty pancreatic disease.

IMPLICATIONS OF THE HYPOTHESIS If proven, this hypothesis will provide new knowledge on the complex interplay between various metabolic insults. Second, screening for NAFPD may identify individuals at risk for developing type 2 diabetes mellitus for targeted prevention. Third, screening for the presence of non-alcoholic fatty pancreatic disease in patients with obstructive sleep apnea may help to decrease the incidence of diabetes mellitus through a targeted prevention.

Gestational Diabetes Mellitus and Sleep-Disordered Breathing; Bisson M, Sériès F, Giguère Y, Pamidi S, Kimoff J, Weisnagel S, Marc I; Obstetrics & Gynecology (Feb 2014)

Tags:

• Depression
• Diabetes
• Pregnancy
• Sleep Apnoea
• Sleep Disorders - Apnoea

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OBJECTIVE: To examine the link between gestational diabetes mellitus (GDM) and sleep-disordered breathing using complete polysomnography and questionnaires in a case-control study of pregnant women.

METHODS: Pregnant women (body mass index [bMI] less than 35, no prior diabetes or hypertension) were eligible as cases (n=26) if diagnosed with GDM by routine 75-g oral glucose tolerance test. Women in the control group without GDM (n=26) were matched for gestational age at polysomnography, BMI, and age. Polysomnography were conducted at home at 24-32 weeks of gestation. Sleepiness score (Epworth Sleepiness Scale), subjective sleep quality (Pittsburgh Sleep Quality Index), risk for depression (Edinburgh Postnatal Depression Scale), and restless legs syndrome were assessed by questionnaire.

RESULTS: Primary outcome apnea-hypopnea index (4.2±3.9 events per hour in women in the case group compared with 3.8±2.3 events per hour in women in the control group) as well as other objective and subjective sleep measures, including oxygen desaturation index, snoring, and flow limitation, were not significantly different between groups. Sleepiness was greater in women in the case group than in women in the control group (9.8±3.6 compared with 7.2±3.6, P=.05). Additionally, 23% of women in the case group compared with 0% of women in the control group (P<.01) reported an Edinburgh Scale score of at least 10 (suggesting significant depression) and 46% of women with GDM reported restless legs syndrome compared to 19% of women in the control group (P=.07).

CONCLUSION: There was no association between GDM and sleep-disordered breathing in pregnant women with prepregnancy BMIs under 35 and no medical comorbidities. LEVEL OF EVIDENCE:: II.

Obstructive sleep apnea syndrome causes a pseudo-Cushing's state in Japanese obese patients with type 2 diabetes mellitus; Tamada D, Otsuki M, Kashine S, Hirata A, Onodera T, Kitamura T, Shimomura I; Endocrine Journal (Sep 2013)

Tags:

• dexamethasone
• Diabetes
• Obesity
• Sleep Apnoea

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Activation of the hypothalamic-pituitary-adrenal axis has been reported in some patients with the obstructive sleep apnea syndrome (OSAS). In current study, we investigated whether OSAS affect the screening test for subclinical Cushing's disease using 0.5 mg overnight dexamethasone suppression test (DST) in Japanese obese diabetic patients with OSAS. Among Japanese obese patients with type 2 diabetes mellitus who had been hospitalized in our department, we selected 20 patients with moderate to severe untreated OSAS (apnea-hypoxia index, AHI, of ≥15 events/hour). All patients underwent 0.5 mg DST. The same test was repeated in patients with positive response of it within a few days after continuous positive airway pressure (CPAP) therapy. We found that five patients showed positive response of DST (25%). Three of these patients continued to use CPAP, and they showed normal response of DST after CPAP therapy. Serum cortisol after 0.5 mg DST measured before CPAP therapy correlated significantly with fasting serum cortisol level (r=0.764, p<0.0001), but not with various clinical parameters, including AHI (P=0.784), body mass index (P=0.984), waist circumference (p=0.957), HbA1c (p=0.261), fasting plasma glucose (p=0.420) and HOMA-IR (p=0.500). Our study show that OSAS causes a pseudo-Cushing's syndrome in obese patients with type 2 diabetes mellitus, which phenomena can be reversed by CPAP therapy.

Obstructive Sleep Apnea and Diabetic Nephropathy: A cohort study; Tahrani A, Ali A, Raymond N, Begum S, Dubb K, Altaf Q, Piya M, Barnett A, Stevens M; Diabetes Care 36 (11), 3718-25 (Nov 2013)

Tags:

• Diabetes
• Sleep Apnoea

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OBJECTIVE Diabetic nephropathy (DN) is a leading cause of end-stage renal disease (ESRD). Obstructive sleep apnea (OSA) is common in type 2 diabetes and increases oxidative stress. Hence, OSA could promote the development and progression of DN. RESEARCH DESIGN AND METHODS This was a cohort study in adults with type 2 diabetes. Patients with known OSA or ESRD were excluded. DN was defined as the presence of albuminuria or an estimated glomerular filtration rate (eGFR)<60 mL/min/1.73 m(2). DN progression was based on eGFR measurements. OSA was defined as apnea hypopnea index (AHI) ≥5 events/h. Serum nitrotyrosine abundance (a marker of nitrosative stress) was measured by ELISA. RESULTS A total of 224 patients were included. OSA and DN prevalence was 64.3 and 40.2, respectively. DN prevalence was higher in patients with OSA (OSA(+)) compared with those without OSA (OSA(-)) (49.3% vs. 23.8%, P<0.001). After adjustment, OSA (odds ratio 2.64 [95% CI 1.13-6.16], P = 0.02) remained independently associated with DN. After an average follow-up of 2.5 (0.7) years, eGFR decline was greater in OSA(+) compared with OSA(-) patients (median -6.8% [interquartile range -16.1 to 2.2]vs. -1.6% [-7.7 to 5.3%], P = 0.002). After adjusting, both baseline OSA (B = -3.8, P = 0.044) and AHI (B = -4.6, P = 0.02) remained independent predictors of study-end eGFR. Baseline serum nitrotyrosine abundance (B = -0.24, P = 0.015) was an independent predictor of study-end eGFR after adjustment. CONCLUSIONS OSA is independently associated with DN in type 2 diabetes. eGFR declined faster in patients with OSA. Nitrosative stress may provide a pathogenetic link between OSA and DN. Interventional studies assessing the impact of OSA treatment on DN are needed.

Association of obstructive sleep apnea in REM sleep with reduced glycemic control in type 2 diabetes: Therapeutic implications; Grimaldi D, Beccuti G, Touma C, Van Cauter E, Mokhlesi B; Diabetes Care (Oct 2013)

Tags:

• Diabetes
• Sleep Apnoea

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ObjectiveSeverity of obstructive sleep apnea (OSA) has been associated with poorer glycemic control in type 2 diabetes. It is not known whether obstructive events during rapid eye movement (REM) sleep have a different metabolic impact compared to those during non-REM (NREM) sleep. Treatment of OSA is often limited to the first half of the night, when NREM rather than REM sleep predominates. We aimed to quantify the impact of OSA in REM versus NREM sleep on hemoglobin A1c (HbA1c) in subjects with type 2 diabetes.Research Design and MethodsAll participants underwent polysomnography and glycemic control was assessed by HbA1c.ResultsOur analytic cohort included 115 subjects (65 women, age 55.2 ± 9.8 years; BMI 34.5 ± 7.5 kg/m(2)). In a multivariate linear regression model, REM AHI was independently associated with increasing levels of HbA1c (p=0.008). In contrast, NREM AHI was not associated with HbA1c (p=0.762). The mean adjusted HbA1c increased from 6.3% in subjects in the lowest quartile of REM AHI to 7.3% in subjects in the highest quartile of REM AHI (p=0.044 for linear trend). Our model predicts that 4 hours of CPAP use would leave 60% of REM sleep untreated and would be associated with a decrease in HbA1c by about 0.25%. In contrast, 7 hours of CPAP use would cover more than 85% of REM sleep and would be associated with a decrease in HbA1c by as much as 1%.ConclusionsIn type 2 diabetes, OSA during REM sleep may influence long-term glycemic control. The metabolic benefits of CPAP therapy may not be achieved with the typical adherence of 4 hours per night.

[Veldrina]

etihwr,

Wow, that was a mouthful! :) I haven't seen any claims in my 7+ yrs of rating that had SA as a known complication of DM. We are never taught that, & if it's not one of the presumptive conditions in CFR 3.309 we don't look at it. That doesn't mean that a doctor can't turn around & say in this case it is, provided there is medical rationale. I do hope John & anyone claiming it tries & wins. They discover new complications of diabetes mellitus all the time, so who is to say it might not be in the future? I just know that as of right know, unless you have a good doc who is willing to help you out by citing those studies, it's a slim chance. This isn't to say that you can't get them back with the homework above if you appeal. Try it....the worst they can say is no. Good luck!

[Notorious Kelly]

Veldrina,

Sure appreciate your presence and patient contributions in spite of our battering.

Pass on our thanks to your coworkers and have some fun this summer!