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Original Research: SLEEP MEDICINE |

Sleep Apnea in Early and Advanced Chronic Kidney Disease: Kaiser Permanente Southern California Cohort FREE TO VIEW

John J. Sim, MD; Scott A. Rasgon, MD; Dean A. Kujubu, MD; Victoria A. Kumar, MD; In Lu A. Liu, MS; Jiaxiao M. Shi, PhD; Tam T. Pham, MD; Stephen F. Derose, MD, MS
Author and Funding Information

*From the Division of Nephrology and Hypertension (Drs. Sim, Rasgon, Kujubu, Kumar, and Pham), Kaiser Permanente Los Angeles Medical Center, Los Angeles, CA; and the Department of Research and Evaluation (Ms. Liu, and Drs. Shi and Derose), Kaiser Permanente Southern California, Pasadena, CA.

Correspondence to: John J. Sim, MD, Division of Nephrology and Hypertension, Kaiser Permanente Los Angeles Medical Center, 4700 Sunset Blvd, Los Angeles, CA 90027; e-mail: John.j.sim@kp.org


Dr. Derose had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

This research was supported in part by grant No. 5R21DK064598 from the National Institute of Diabetes and Digestive and Kidney Diseases (to Dr. Derose).

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/misc/reprints.shtml).


Chest. 2009;135(3):710-716. doi:10.1378/chest.08-2248
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Background:  Sleep apnea (SA) has been reported to be highly prevalent in the dialysis population. The reported rates of SA in dialysis are severalfold greater than the 2 to 4% estimated in the general population. This study sought to determine whether an association exists between SA and early stages of chronic kidney disease (CKD) where SA may represent an important comorbidity and potential risk factor in kidney disease.

Methods:  Cross-sectional study of adults from an integrated health plan with documented serum creatinine levels in the period January 1, 2002, through December 31, 2004. SA diagnosis determined by International Classification of Diseases, ninth revision, coding for SA and Current Procedural Terminology coding for positive airway pressure devices. Kidney function was determined by the estimated glomerular filtration rate (eGFR). Logistic was regression used to estimate the relative risk for SA.

Results:  The overall prevalence of SA was 2.5% in the study population that included subjects with normal renal function and those with CKD. The odds ratios (ORs) for SA by eGFRs of 75 to 89, 60 to 74, 45 to 59, 30 to 44, and 15 to 29 mL/min per 1.73 m2, respectively, compared to normal kidney function, after adjustment for age, sex, and number of visits, were as follows: 1.22 (95% confidence interval [CI], 1.18 to 1.25); 1.32 (95% CI, 1.27 to 1.37); 1.42 (95% CI, 1.35 to 1.50); 1.37 (95% CI, 1.25 to 1.50); and 1.32 (95% CI, 1.13 to 1.55). The increased ORs for eGFRs > 45 mL/min per 1.73 m2 were sustained even after controlling for diabetes, heart failure, and hypertension.

Conclusion:  This study demonstrated an increased risk of SA in patients with early CKD. Further evidence of a causal relationship should be sought in the hope that the detection and management of SA may improve the course of CKD.

Figures in this Article

The association between end-stage renal disease (ESRD) and sleep apnea (SA) has been well described.17 The prevalence of SA in the earlier stages of chronic kidney disease (CKD) has not been well described, but the consequence of an association may be important. If SA is highly prevalent among patients with CKD stages 1 through 4, as defined by the National Kidney Foundation,8 it could be either a risk factor for or a consequence of CKD. An observed association between SA and CKD could provide the impetus for more definitive studies that determine whether SA contributes to the progression of CKD, just as it appears to contribute to hypertension and cardiovascular disease.9,10

The Institute of Medicine has estimated11 that 50 to 70 million persons are affected by some form of sleep disorder in the United States. SA causes derangements in several organ systems, including the endocrine, renal, and cerebrovascular systems, with clinical sequelae that extend into pregnancy and the psychosocial realm.4,1215

Because of the improved awareness of both the prevalence and clinical implications of SA, more providers are diagnosing SA.16 The prevalence of SA in the general population is estimated at 2 to 4%.17,18 In ESRD patients, the SA rate has been estimated at around 30%6 and observed at rates that are as high as 73%.2,4,6,7 This study sought to determine whether an association exists between SA and CKD before the occurrence of ESRD. We hypothesized that the risk of SA would increase at lower levels of estimated glomerular filtration rate (eGFR). Using the database of a large, ethnically diverse, vertically integrated prepaid health plan, this study sought to determine the risk of SA in a population with a range of kidney function from normal to late stage CKD, accounting for important comorbidities such as diabetes, hypertension, and congestive heart failure (CHF).

Study subjects were all members of Kaiser Permanente Southern California, which is an integrated health-care system that provides comprehensive care to > 3 million members at 11 medical centers and hundreds of satellite clinics and service sites throughout Southern California. All members have very similar coverage benefits for health-care services, including office visits, tests, and medications. These data were collected as part of normal health-care operations. Potentially eligible subjects were limited to adults > 17 years of age with > 1 month of membership in the health plan, who had one or more or serum creatinine level measurements indicating an eGFR of > 15 mL/min per 1.73 m2 from January 1, 2002, to December 31, 2004.

Diagnosed SA was identified from administrative databases using inpatient and outpatient International Classification of Diseases, ninth revision, (ICD-9) diagnosis codes for SA (327.20, 327.21, 327.23, 780.51, 780.53, and 780.57) and by dispensation of continuous positive airway pressure (CPAP) or bilevel pressure ventilation (BPV) devices based on data from a health plan database that records device dispensations. To validate the accuracy of ICD-9 coding for SA, a physician chart review of 50 random subjects with a diagnosis of SA was performed. Forty-four of 50 subjects (88%) had either polysomnography findings demonstrating SA or written documentation by a clinician that the patient was being treated for SA with CPAP/BPV.

Kidney function was assessed by the abbreviated Modification of Diet in Renal Disease Study equation, which calculates eGFR based on serum creatinine level, age, sex, and black vs non-black race.8,19 Data on black vs non-black race were not available in 43% of potentially eligible subjects to calculate the eGFR. When race data were not available, black vs non-black race was imputed using geocoding based on US Census block group data. Assignment of race was made when > 75% of health plan members were either black or non-black based on the census block of residence.20 Race data were 91% complete after geocoding.

We identified serum creatinine test results during the observation period that were unlikely to be obtained during acute kidney injury (AKI), a condition in which kidney function is temporarily reduced. If a subject had undergone only one serum creatinine test and the eGFR was ≥ 90 mL/min per 1.73 m2, then normal kidney function was presumed. In subjects with any eGFR < 90 mL/min per 1.73 m2, two or more serum creatinine tests were required. To avoid an eGFR that had been obtained during AKI, we used an algorithm that examined serial serum creatinine test results > 90 days apart in a pair-wise manner.8 The second eGFR was used as the chronic-state measure of kidney function with the following one exception: if the second eGFR was less than two thirds of the first eGFR, AKI may have occurred, and a third eGFR determined > 90 days later was used.21

Exclusion criteria included patients with eGFR < 15 mL/min per 1.73 m2 and ESRD patients. Cases of ESRD were identified by an ESRD registry for dialysis and renal transplant maintained by the health plan and based on Medicare ESRD reporting and ESRD case managers. Subjects with a preexisting diagnosis of diabetes, CHF, or hypertension were identified by using existing health plan case-identification databases used for clinical care. Cases were identified based on inpatient and outpatient ICD-9 diagnosis codes, specific medications, as well as abnormal glycosylated hemoglobin levels (> 7.0%) for diabetes, using data from 1997 onward. Height and weight for the calculation of body mass index (BMI) were not available from electronic health plan databases during the observation period.

Logistic regression was performed in which the dependent variable was the presence or absence of SA. Covariates that were also evaluated and controlled for in the logistic regression analyses were age, sex, diabetes, hypertension, and CHF. The main explanatory variable was the eGFR, using strata in units of 15 mL/min from 15 to 89 mL/min per 1.73 m2 compared with an eGFR ≥ 90 mL/min per 1.73 m.2 Our primary analyses used the earliest “chronic-state” eGFR as described above during the observation period. The number of outpatient visits that included provider contact of any type (ie, physician, nurse practitioner) during the observation period was included as a control variable since more visits due to illnesses such as CKD may increase the likelihood of a diagnosis of SA. Models were tested with and without control for comorbid conditions. Model 1 controlled for age, gender, race, and outpatient visits. Model 2 added diabetes and heart failure to model 1. Model 3 added hypertension to model 2. In an attempt to further validate the SA diagnosis, a subgroup analysis was conducted by restricting regression analyses to subjects in whom SA had been diagnosed by positive airway pressure device prescription and excluded subjects in whom SA had been diagnosed solely by ICD-9 coding. These subjects were determined to be more likely to have SA confirmed by polysomnography before a clinician prescribed therapy with a positive airway device.

To assess the potential impact of death and ESRD on a diagnosis of SA at any given level of eGFR, we compared rates (No. of cases per 100 subjects) of diagnosis of SA, death, and ESRD by eGFR strata from 15 to 89 mL/min per 1.73 m2. ESRD was determined to be present in any patient whose condition progressed to replacement therapy (ie, dialysis or renal transplantation) during the observation period.

Analyses were conducted by the research team using a statistical software package (SAS, version 9.1; SAS Institute; Cary, NC; and Stata, version 9.2; StataCorp; College Station, TX). The study protocol was approved by the Kaiser Permanente Southern California Institutional Review Board.

There were 1,377,427 adult health plan members who had undergone one or more serum creatinine tests during the 3-year observation period (59% of all adult members). Of these, 1,102,089 members did not have ESRD and had one or more chronic-state eGFRs identified that were > 15 mL/min per 1.73 m2. Table 1 describes these subjects' demographic composition and comorbidities. Sixty-one percent of subjects were women, and 9.7% were black. The overall percentage of subjects with evidence of a diagnosis of SA at any time during the 3-year observation period was 2.54% (Table 2). Among subjects with SA, 62.6% were men, and the mean age was 55.0 years. Fifty-three and one half percent of SA cases were identified by ICD-9 diagnoses alone; the remaining 47.5% had a positive airway pressure device. The proportion of subjects with SA was lower for an eGFR ≥ 90 mL/min per 1.73 m2 compared to any eGFR in the range of 15 to 89 mL/min per 1.73 m2 (p < 0.01), but there was little variation in that range.

Table Graphic Jump Location
Table 1 Subjects' Age, Sex, Black and Non-Black Race, and Comorbidities

*White, 47%; Hispanic, 38%; Asian and Pacific Islander, 11%; Native American and Alaskan, 0.5%; other, 3%.

Table Graphic Jump Location
Table 2 Subjects' Kidney Status by eGFR Strata (mL/min per 1.73 m2) and Subjects With Evidence of Diagnosed SA By eGFR Strata

The results of logistic regression models appear in Table 3, which demonstrates the relationship between SA and eGFR. In model 1, adjustment was made individually for age, sex, race (specified as black vs non-black race), and the number of outpatient visits. The model 1 odds ratios (ORs) for SA at eGFR strata of 75 to 89, 60 to 74, 45 to 59, 30 to 44, and 15 to 29 mL/min per 1.73 m2 compared to an eGFR ≥ 90 mL/min per 1.73 m2 were as follows: 1.22 (95% confidence interval [CI], 1.18 to 1.25); 1.32 (95% CI, 1.27 to 1.37); 1.42 (95% CI, 1.35 to 1.50); 1.37 (95% CI, 1.25 to 1.50); and 1.32 (95% CI, 1.13 to 1.55), respectively. Model 2 includes the additional covariates of diabetes and CHF, and model 3 adds hypertension as a covariate. Diabetes (OR, 1.36; 95% CI, 1.32 to 1.40), CHF (OR, 2.40; 95% CI, 2.30 to 2.51), and hypertension (OR, 1.63; 95% CI, 1.59 to 1.68) are all strongly and positively associated with SA despite simultaneous adjustment.

Table Graphic Jump Location
Table 3 ORs for SA by Subject Characteristics*

*N = 1,102,089 in all models. OP = outpatient. The first available chronic-state eGFR was use to categorize eGFR strata. Model 1 adjusts for the covariates of age, gender, race, and OP visits. Model 2 adds the covariates of diabetes and CHF, which are associated with both SA and CKD. Model 3 adds to Model 2 the covariate of hypertension. Hypertension is a likely intermediary between SA and CKD.

†Reference eGFR: >90 mL/min/1.73 m2.

‡Reference age group: 18–39 years.

§Compared to all other races combined.

‖Five additional outpatient contacts with providers.

The relation between SA and the lower eGFR levels attenuates with the addition of comorbidities in models 2 and 3 (Table 3). In model 3, the OR was significantly < 1 at an eGFR of 15 to 29 mL/min per 1.73 m2 (OR, 0.81; 95% CI, 0.69 to 0.95). To explore this finding, we examined the occurrence of death and ESRD, because either event makes the diagnosis of SA less likely during late-stage CKD before progression to ESRD. Figure 1 compares the rates of a diagnosis of SA, death, and ESRD subsequent to the first chronic-state eGFR finding. The rates of death and ESRD become very high compared to the rate of SA below an eGFR of 30 mL/min per 1.73 m2.

Figure Jump LinkFigure 1 Rates (No. of cases per 100 subjects) of SA, death, and progression to ESRD by eGFR strata for the study period January 1, 2002, through December 31, 2004. The rates in each eGFR stratum are directly standardized using weights taken from all subjects with an eGFR of 15 to 89 mL/min per 1.73 m2.Grahic Jump Location

Demographic characteristics and outpatient utilization are associated with SA in a predictable manner (Table 3). Men were at increased risk of SA. Black race was associated with an increased OR for SA in all models. An increasing number of outpatient visits is strongly associated with SA (p < 0.001) [Table 3]. Subgroup analysis using logistic regression restricted to subjects using a positive airway pressure device (N = 13,308) demonstrated the same significance and direction of effect in all variables (Table 4). The ORs for each eGFR range between Table 3 and Table 4 were < 5% different, except for an eGFR of 15 to 29 mL/min per 1.73 m2, where the difference was 14%.

Table Graphic Jump Location
Table 4 ORs for SA in the Subgroup of Subjects (N = 13,308) With Positive Airway Pressure Devices and Excludes SA Diagnosis by ICD-9 Coding (N = 1,087,401)

*As in Table 2, Model 1 control for age, gender, race, and outpatient visits; Model 2 adds in control for diabetes and CHF; and Model 3 add in control for hypertension.

†Reference eGFR: >90 mL/min/1.73 m2.

A 30% increase in CKD has been observed in the past decade, and this has been mostly attributed to the rising rates of diabetes and hypertension.22 If an association exists between SA and earlier stages of CKD, a prospective study to determine the clinical usefulness of SA screening and treatment early in the course of CKD may be valuable and lead to a new approach to prevent a portion of cases of CKD. This study found a higher risk of SA in patients with an eGFR of 45 to 89 mL/min per 1.73 m2 The association between eGFR and SA was attenuated but not eliminated by controlling for diabetes, CHF, and the potential intermediary of hypertension.

The overall prevalence of SA in our study population was 2.5%. After adjustment for diabetes, CHF, and hypertension, the risk of SA was lower in those patients with late-stage CKD (eGFR, 15 to 29 mL/min per 1.73 m2) than in those with normal kidney function. The risk of SA in late-stage CKD before ESRD was actually lower than we expected, given the reported rates23 in patients with ESRD that are often four times the rate in the general population. A possible explanation is that the risk of SA declines because of attrition from mortality in patients with both CKD and SA before they have ESRD. Because mortality rates are high in patients with CKD, there are competing risks present (Fig 1), which can alter the associations observed. This possibility is underscored by the relationship of age to SA, in which a similar peak occurs not in the oldest age group but in the 50- to 59-year-old group, which matches population prevalence peaks.2426 SA patients have shortened life spans, much like CKD patients.12,27,28 Longitudinal studies of SA patients have demonstrated that they have far greater risk of mortality compared to control subjects.12,29 In addition, the majority of CKD patients die from cardiovascular or other diseases and never reach ESRD.30,31

SA in ESRD patients has been well described and occurs at rates as high as 73%.27,3236 SA in dialysis patients is often theorized to be a manifestation of uremia and thus occurs in the latest stage of CKD.3739 Aggressive treatment of the uremic milieu with renal transplantation and/or nocturnal hemodialysis4042 has even been shown to improve or cure SA in some patients.

Although this study demonstrates an association between CKD and SA, the direction of the relationship of the two disease processes cannot be determined. Nevertheless, known pathogenic mechanisms make it conceivable that SA may contribute to the progression of CKD. SA onset and severity have been linked to CVD risk factors and pathophysiology, and many of these same CVD-related factors are considered to be important in the development of CKD. For example, reactive oxygen species and oxidative stress indicators have been shown to be elevated in patients with SA,43 suggesting the possibility that recurrent hypoxia with ischemia and reperfusion can cause renal injury. Vascular endothelial growth factor has also been demonstrated to be increased in SA patients where vascular endothelial growth factor may potentially have a pathogenic role within the kidney.44,45

An important shortcoming of this study is the lack of data regarding BMI. The association between obesity and SA has been well described.18,46 Patients with CKD and higher BMIs have been shown to progress to ESRD at a faster rate.47 Reliable BMI indicators were unattainable for the entire study population.

Inclusion in this study required a documented serum creatinine level that made health plan members who utilized the health-care system intensively, including those with CKD, more likely to be included as study subjects. This selection factor, including multiple interactions with health-care providers, may have introduced a bias favoring the diagnosis of SA. We did examine this by adjusting for the number of outpatient visits (Table 3). This confirmed that the relative risk for SA with each five additional outpatient visits increased the OR for diagnosed SA. However, a statistically significant association of SA with CKD remained after this adjustment.

In terms of the actual distribution of the patients by CKD stage, our data (Table 2) indicate that the proportion of subjects in each CKD stage is similar and not highly skewed by comparison to that found in the US population.48 The overall prevalence of SA in our study population was 2.5%, which is consistent with the 2 to 4% prevalence estimated in the general population but is closer to the 2% estimated in women vs the 4% estimated in men.18

Validation of the diagnosis of SA was also a shortcoming of this study. Polysomnography results were not available on the entire group of > 20,000 patients in this study who were coded for SA. A random chart review of those coded for SA revealed that 88% of patients who had been coded for SA had a documented polysomnogram or were being treated for SA with CPAP/BPV. When analyses were restricted to subjects using a positive airway pressure device, who are more likely to have undergone polysomnography, the association between SA and eGFR was unchanged. Finally, kidney function was by necessity determined based on estimated GFR; but, we acknowledge that there is imprecision in the Modification of Diet in Renal Disease Study formula, particularly when used in healthy individuals.49

In summary, this study demonstrates a greater risk of SA in patients with decreased kidney function, including those with clear CKD as defined by an eGFR < 60 mL/min per 1.73 m2, when compared to patients with normal kidney function. Given the high morbidity and mortality associated with CKD, and the high prevalence of sleep disorders in the United States, further research is necessary to examine the relationship between SA and CKD and to elucidate the pathophysiologic mechanisms involved. If a causal relationship does indeed exist between SA and CKD, the identification and treatment of SA could potentially modify the course of kidney disease.

AKI

acute kidney injury

BMI

body mass index

BPV

bilevel pressure ventilation

CHF

congestive heart failure

CI

confidence interval

CKD

chronic kidney disease

CPAP

continuous positive airway pressure

eGFR

estimated glomerular filtration rate

ESRD

end-stage renal disease

ICD-9

International Classification of Diseases ninth revision

OR

odds ratio

SA

sleep apnea

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Rule AD, Rodeheffer RJ, Larson TS, et al. Limitations of estimating glomerular filtration rate from serum creatinine in the general population. Mayo Clin Proc. 2006;81:1427-1434. [PubMed]
 

Figures

Figure Jump LinkFigure 1 Rates (No. of cases per 100 subjects) of SA, death, and progression to ESRD by eGFR strata for the study period January 1, 2002, through December 31, 2004. The rates in each eGFR stratum are directly standardized using weights taken from all subjects with an eGFR of 15 to 89 mL/min per 1.73 m2.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 Subjects' Age, Sex, Black and Non-Black Race, and Comorbidities

*White, 47%; Hispanic, 38%; Asian and Pacific Islander, 11%; Native American and Alaskan, 0.5%; other, 3%.

Table Graphic Jump Location
Table 2 Subjects' Kidney Status by eGFR Strata (mL/min per 1.73 m2) and Subjects With Evidence of Diagnosed SA By eGFR Strata
Table Graphic Jump Location
Table 3 ORs for SA by Subject Characteristics*

*N = 1,102,089 in all models. OP = outpatient. The first available chronic-state eGFR was use to categorize eGFR strata. Model 1 adjusts for the covariates of age, gender, race, and OP visits. Model 2 adds the covariates of diabetes and CHF, which are associated with both SA and CKD. Model 3 adds to Model 2 the covariate of hypertension. Hypertension is a likely intermediary between SA and CKD.

†Reference eGFR: >90 mL/min/1.73 m2.

‡Reference age group: 18–39 years.

§Compared to all other races combined.

‖Five additional outpatient contacts with providers.

Table Graphic Jump Location
Table 4 ORs for SA in the Subgroup of Subjects (N = 13,308) With Positive Airway Pressure Devices and Excludes SA Diagnosis by ICD-9 Coding (N = 1,087,401)

*As in Table 2, Model 1 control for age, gender, race, and outpatient visits; Model 2 adds in control for diabetes and CHF; and Model 3 add in control for hypertension.

†Reference eGFR: >90 mL/min/1.73 m2.

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