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Clinical Investigations: SLEEP |

Determinants Affecting Health-Care Utilization in Obstructive Sleep Apnea Syndrome Patients* FREE TO VIEW

Ariel Tarasiuk, PhD; Sari Greenberg-Dotan, MA; Yaron S. Brin, MD; Tzahit Simon, MA; Asher Tal, MD; Haim Reuveni, MD
Author and Funding Information

*From the Sleep-Wake Disorders Unit, Soroka University Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Correspondence to: Ariel Tarasiuk, PhD, Sleep-Wake Disorders Unit, Soroka University Medical Center, PO Box 151, Beer-Sheva, 84105 Israel; e-mail: tarasiuk@bgu.ac.il



Chest. 2005;128(3):1310-1314. doi:10.1378/chest.128.3.1310
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Published online

Study objective: To investigate determinants of health-care utilization in patients with obstructive sleep apnea syndrome (OSAS).

Design: Case-control prospective study with OSAS patients and a control group. We compared 218 patients with OSAS to those of age-, gender-, geographically-, and family physician-matched control subjects from the general population, matched 1:1 (χ2 = 0.999).

Participants: All participants were members of Clalit Health Care Services, a health maintenance organization in the southern region of Israel. All OSAS patients underwent nocturnal polysomnography studies. Indexes of health-care utilization 2 years prior to the polysomnography were analyzed.

Measurements and results: Health-care utilization was 1.7-fold higher (p < 0.001) in the OSAS patients due to more hospitalization days (p < 0.001), consultations (p < 0.001), and cost for drugs (p < 0.05), particularly those for the cardiovascular system. In comparison to men, women consumed significantly more health-care resources (p < 0.001). OSAS patients ≤ 65 of age years consumed 2.2-fold more health-care resources than control subjects (p < 0.001). Polysomnography findings and OSAS severity and body mass index (BMI) did not predict health-care utilization, using multivariate logistic regression analysis. Age > 65 (odds ratio [OR], 2.2; p < 0.04) and female gender (OR, 2.0; p < 0.05) were the leading elements predicting the most costly OSAS patients. Arbitrarily dividing the OSAS group by cost of health-care utilization, the upper 25% (n = 55) of patients who were the “most costly” consumed sevenfold more health-care resources than the lower 75% of the patients. This was due to higher comorbidity, ie, 10 to 30% more hypertension, ischemic heart disease, diabetes mellitus, and pulmonary disease.

Conclusions: OSAS patients are heavy users of health-care resources. Age > 65 years and female gender were the leading elements predicting the most costly OSAS patients, and not necessarily patients with a high BMI and classic OSAS severity indexes.

Obstructive sleep apnea syndrome (OSAS) is a common sleep-related breathing disorder and is a risk factor for both chronic and acute conditions, such as cardiovascular events and even sudden death.12

OSAS patients are heavy consumers of health-care resources.34 Most information regarding adults comes from the Canadian health-care system48; only limited information is available from other parts of the world.910 These studies have shown that physician costs and hospital admissions are > 1.6-fold higher in patients with OSAS than in the general population. Five years prior to OSAS diagnosis, patients with OSAS have been shown to be heavy users of medications, particularly those used to treat cardiovascular diseases.5,8 Diagnosis of OSAS and adherence to treatment results in a significant reduction in resource utilization, eg, physician claims and hospital stays.,6

In Israel,11OSAS is underdiagnosed and undertreated. This may be due in part to the commonly held belief that OSAS may not pose a serious health risk,12and low awareness of the manifestations of OSAS13 by primary care physicians, as well as its relationship to health-care utilization and quality of life.

We present data on determinants affecting health-care utilization in OSAS patients, in the Israeli health-care arena, 2 years prior to diagnosis. In this system, which is similar to most industrialized countries, patients have obligatory National Health Insurance and physicians do not have any economic incentive to prevent or deter patients from medical services. We hypothesized that increased health-care utilization is related to comorbidity and OSAS patient characteristics. The current study explores the effect of age, gender, and apnea severity on utilization of health-care resources among patients with OSAS.

Subjects are enrollees of Clalit Health Care Services (CHS), the largest health maintenance organization in Israel; all had been permanent residents of the southern region for at least 3 years prior to study initiation. Recruited subjects are “typical” OSAS patients (with or without chronic diseases and prescribed medication respectively) and control subjects, entitled to a polysomnographic study and all diagnostic and treatment information free of charge. Control subjects (n = 218) randomly selected from the general population were matched (1:1 with OSAS patients) by family physician, age, gender, and area of residency.5 In cases where we matched more than one control subject, we arbitrarily selected the first subject. We excluded three enrollees with OSAS who exhibited extreme consumption (> 10 times the mean values) of health-care services and none from the control group. Patients were not matched to control subjects for body mass index (BMI) because that information is not included in the CHS database. By law, we were not permitted to contact the control subjects. We confirmed that the control group was healthy and none of these subjects had a chronic disease by verifying that they did not receive any regular prescribed medications. However, it is possible that 2 to 4% (at most) of the control subjects might have undiagnosed OSAS. The Institutional Ethics Committee approved the protocol, and informed consent was obtained from all OSAS subjects.

Diagnosis of OSAS was based on history and polysomnographic findings. Data on patient history were acquired by self-administered questionnaires. Overnight polysomnography was performed according to previously described methods in our laboratory.14

Data were obtained from the CHS billing system, with a reliability > 98%.1516 All costs were collected in the 24-month period prior to the polysomnography. Direct costs of OSAS include the following: (1) number of hospitalization days, number of “day hospital” visits (< 24-h admission), and number of emergency department visits; (2) number of (new and repeated) visits to the primary care physician and specialist (ie, consultations for continuous positive airway pressure titration, pulmonary/otolaryngologists); and (3) drugs prescribed (type and cost), categorized according to World Health Organization recommendations.17 We did not include indirect costs such as cost of polysomnography, titration study, or out-of-pocket expenses for CPAP purchase in our analysis. We defined total annual cost as the sum of the costs for all indicators. Costs are expressed as the mean per patient per year in US dollars according to the price list published by the Israeli Ministry of Health. The exchange rate was 4.2 New Israeli sheqal per US $1. Values were adjusted for inflation.

Data Analysis

Cost data were analyzed18 using statistical software (SPSS version 11.5; SPSS; Chicago, IL). Statistical power (α = 0.05) was calculated for the women (n = 44, control vs OSAS) and was found to be 0.98. One-way analysis of variance was used to compare between mean values. A Mann-Whitney U test was used to determine statistical significance of cost elements between groups; χ2 was used to confirm “population match” and univariate analysis. Multivariate logistic regression analysis was used to calculate the high costly subgroup of OSAS patients and control subjects. Data were presented as mean ± SEM for costs and median and range. Statistical significance was accepted at p ≤ 0.05.

Two hundred eighteen adult OSAS patients were included (mean age, 54.8 ± 10.3 years; 18% >65 years old; 79.8% male gender). The control subjects were perfectly matched (χ2 = 0.999) by family physician, age, gender, and address. All symptoms were typical for the OSAS group except for “observed choking” by the spouse, which was reported in 47% of the men vs 25% of women (p < 0.01). The comorbidity of the OSAS group (hypertension, 40.5%; diabetes mellitus, 14.5%; pulmonary diseases, 12.4%) was similar between genders and ages (≤ 65 years and > 65 years), except for ischemic heart disease, which was 54% and 19% (p < 0.001) in patients > 65 years vs ≤ 65 years old, respectively. The OSAS group had a mean respiratory disturbance index (RDI) of 34.9 ± 22.3 events/h, BMI of 32.8 ± 6.8, Epworth sleepiness scale (ESS) 7.6 ± 4.4, arousal index 28.9 ± 16.1 events/h. In comparison to men, women with OSAS were 3 years older (p < 0.05), heavier (> 3 BMI units), and had milder OSA (< 8 RDI units) than men (p < 0.05).

Health-care utilization was 1.7-fold higher (p < 0.001) in the OSAS patients compared with the control group (Table 1 ) due to more hospitalization days (p < 0.001), consultations (p < 0.001), and cost of prescribed drugs (p < 0.05), particularly those for the cardiovascular system and alimentary tract and metabolism (Table 2 ). “Other medications,” which represents the remaining 13 pharmacological groups, were significantly reduced among OSAS patients due to significant elevation of “cardiovascular system” and “alimentary tract and metabolism” drugs (Table 2).

In comparison to men (Table 1), women in both groups consumed significantly more health-care resources. OSAS patients ≤ 65 years old consumed 2.2-fold more health-care resources (Table 1) than control subjects (p < 0.001), but similar consumption was found among those > 65 years of age in both groups. The leading elements in which the cost ratio (> 65 years/≤ 65 years of age) was significantly different in both groups were drugs and consultations. The ratio of hospitalization days was significant only in the control group (Table 1).

When arbitrarily dividing the OSAS group by cost, the upper 25% (n = 55) of patients who were the “most costly” had a mean consumption per person per year of $2,641, and consumed approximately 70% of all OSAS group costs. This group consumed sevenfold more health-care resources than the lower 75% of patients, who had a mean consumption per person per year of $377. The characteristics of the most-costly subgroup include higher comorbidity (10 to 30% more hypertension, ischemic heart disease, diabetes mellitus and pulmonary disease) and 1.8 and 2.1 times more women and subjects > 65 years old, respectively. Comparing polysomnographic findings of the “low costly” to the most-costly subgroup, no significant differences were found (p = 0.8) in any of the indexes. For example, RDI was 34.6 ± 22.4 events/h vs 35.5 ± 22.3 events/h, respectively, and arousal and awakening index was 28.5 ± 16.3 events/h vs 30.4 ± 15.9 events/h, respectively.

Age (≤ 65 years, > 65 years), gender, BMI, RDI, ESS score, and smoking were weighed as independent variables by using multivariate logistic regression analysis. The best model for predicting health-care consumption among the “most-costly” subgroup were age > 65 (odds ratio [OR], 2.2; confidence interval [CI], 1.1 to 4.1; p < 0.04) and female gender (OR, 2.0; CI, 1.05 to 4.6; p < 0.05). Using the same analysis for the control group, using age and gender as independent variables, only age (OR, 3.3; CI, 1.6 to 6.9; p < 0.001) was a predictor for health-care consumption among the high-costly subgroup.

OSAS patients consumed 1.7-fold more health-care resources than control subjects. The present study describes cost elements previously described in children1516 for “typical” adults with OSAS in a health-care system in which all citizens are entitled by law to free access to medical care. Our data on health-care utilization may be difficult to compare with those from other health-care systems that have more than one payer. These data can be compared to similar health-care systems as in Canada, from which published reports48 from Manitoba demonstrated higher health-care service utilization in adults with OSAS. Several lines of evidence support our premise that the information presented in this study reflects the “true” consumption of health-care resources of adults with OSAS. First, all polysomnography and the relevant medical information regarding OSAS patients are stored in the only Sleep-Wake Disorder Center in the study region. Second, CHS uses one billing system located in the regional Department of Health Economics. Third, equal access to medical services is provided to all enrollees according to the national health care law implemented in January 1995. Finally, physicians are paid a capitation fee once every 3 months per patient and therefore do not have any economic incentive to increase their patients’ consumption of services.1516 Although we matched case patients and control subjects by family physician, age, gender, and area of residency, we were not permitted to contact the control subjects to obtain their BMI because of legislation protecting patient confidentiality.

Our findings of 1.7-fold more utilization of health-care resources than control subjects are comparable to information from Canada5 demonstrating a 23 to 50% increase in health-care costs in OSAS patients. Both studies used a similar algorithm to select control patients in order to minimize confounding effects. Earlier reports4,7 demonstrated a 2- to 3.5-fold increase in use of health-care services by OSAS patients, years before polysomnographic diagnoses. Differences could be the result of differences in matching the control subjects. Interestingly, the upper 25% of most costly OSAS patients accounts for 70% of total health-care expenditures. This is probably due to greater morbidity in the latter subgroup.

We found that increased age is a predictor for higher health-care cost (Table 1) and cardiovascular diagnoses in OSAS patients.5,8 A similar trend was found in the control group. It is of interest that > 65 years of age, the health-care costs of OSAS patients and control subjects were similar. In contrast, greater than twofold more health-care resources were consumed by subjects ≤ 65 years old with OSAS compared with control subjects. A possible explanation for this cost gap (ie, age > 65 years/≤ 65 years) between OSAS patients and control subjects may be related to higher morbidity in those ≤ 65 years old with OSAS, mainly cardiovascular,5,8 and mental comorbidities.19It is possible that with age (> 65 years), the effect of OSAS-related morbidity is minimized between the groups. Indirect support for this possibility lies in the fact that drug use (indicator for morbidity) increases with age.20 These findings need further investigation.

Smith et al5 found that women with OSAS consumed approximately 1.6-fold more health-care resources and drugs than men. In our study, utilization of health-care services was about twofold greater in women with OSAS compared with control subjects. Women with OSAS8 were more likely to be receiving medications than men, but not cardiovascular drugs or antihypertensives. The reasons for these sex differences are not fully known. Some explanation includes differences in obesity, distribution of adipose tissue, upper airway anatomy, upper airway muscle function, control of ventilation, the effect of sex hormones, and leptin.21 Due to the small sample of women, we were unable to define whether a cost gap exists ≤ 65 years/> 65 years of age.

Interestingly, our OSAS patients with high OSAS severity (RDI, arousal index) and high BMI did not consume more health-care resources. The best predictors of health-care consumption were age (> 65 years) and female gender. As previously discussed,5 there is no one measure that by itself adequately defines the severity of OSAS (ie, apnea-hypopnea index, ESS score, and percentage of time with arterial oxygen saturation < 90%), and would therefore predict health-care utilization. The lack of correlation with the apnea-hypopnea index is probably related to the fact that this index is an imperfect linear measure of severity. Finally, people who are markedly overweight are not necessarily heavy users of health-care resources.,22 The best suggested model5 predicting health-care utilization measures was comprised of age, gender, and BMI, and explained 9%, 14%, and 8% of the variability in physician fees, number of physician claims, and number of physician visits, respectively.

OSAS is underdiagnosed and undertreated. OSAS patients are heavy users of health-care resources. Health-care utilization is a reliable index for morbidity. Further studies are needed to define the specific characteristics of patients in whom intervention will provide the most beneficial effects in terms of cost and quality.

Abbreviations: BMI = body mass index; CHS = Clalit Health Care Services; CI = confidence interval; ESS = Epworth sleepiness scale; OR = odds ratio; OSAS = obstructive sleep apnea syndrome; RDI = respiratory disturbance index

Table Graphic Jump Location
Table 1. The Effect of Age and Gender on Annual Costs of Health-Care Services*
* 

Data are presented as mean US$ ± SEM (median; range).

 

p < 0.001 comparing the control group to OSAS group.

 

p < 0.05 comparing > 65 years to ≤ 65 years of age, Mann-Whitney U test.

§ 

p < 0.001 comparing > 65 years to ≤ 65 years of age, Mann-Whitney U test.

 

Calculated as cost for > 65 years/≤ 65 years of age; the effect of gender on health-care consumption within and between groups was also significant (p < 0.001).

Table Graphic Jump Location
Table 2. The Effect of OSAS on Annual Health-Care Utilization Prior to Diagnosis*
* 

Data are presented as mean ± SEM or %.

 

Data are presented as the percentage of drugs consumed according to World Health Organization classification.

 

The remaining 13 pharmacologic groups.

Shahar, E, Whitney, CW, Redline, S, et al (2001) Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study.Am J Respir Crit Care Med163,19-25. [PubMed]
 
Newman, AB, Nieto, FJ, Guidry, U, et al Sleep Heart Health Study Research Group. Relation of sleep-disordered breathing to cardiovascular disease risk factors: the Sleep Heart Health Study.Am J Epidemiol2001;154,50-59. [CrossRef] [PubMed]
 
Wittmann, V, Rodenstein, DO Health care costs and the sleep apnea syndrome.Sleep Med Rev2004;8,269-279. [CrossRef] [PubMed]
 
Kryger, MH, Roos, L, Delaive, K, et al Utilization of health care services in patients with severe obstructive sleep apnea.Sleep1996;19,S111-S116. [PubMed]
 
Smith, R, Ronald, J, Delaive, K, et al What are obstructive sleep apnea patients being treated for prior to this diagnosis?Chest2002;121,164-172. [CrossRef] [PubMed]
 
Bahammam, A, Delaive, K, Ronald, J, et al Health care utilization in males with obstructive sleep apnea syndrome two years after diagnosis and treatment.Sleep1999;22,740-747. [PubMed]
 
Ronald, J, Delaive, K, Roos, L, et al Health care utilization in the 10 years prior to diagnosis in obstructive sleep apnea syndrome patients.Sleep1999;22,225-229. [PubMed]
 
Otake, K, Delaive, K, Walld, R, et al Cardiovascular medication use in patients with undiagnosed obstructive sleep apnoea.Thorax2002;57,417-422. [CrossRef] [PubMed]
 
Peker, Y, Hedner, J, Johansson, A, et al Reduced hospitalization with cardiovascular and pulmonary disease in obstructive sleep apnea patients on nasal CPAP treatment.Sleep1997;20,645-654. [PubMed]
 
Kapur, V, Blough, DK, Sandblom, RE, et al The medical cost of undiagnosed sleep apnea.Sleep1999;22,749-755. [PubMed]
 
Tarasiuk, A, Reuveni, H Obstructive sleep apnea syndrome: the dilemma of diagnostic strategy.Isr Med Assoc J2004;6,686-690. [PubMed]
 
Wright, J, Johns, R, Watt, I, et al Health effects of obstructive sleep apnoea and the effectiveness of continuous positive airway pressure: a systematic review of the research evidence.BMJ1997;314,851-860. [CrossRef] [PubMed]
 
Reuveni, H, Tarasiuk, A, Wainstock, T, et al Awareness level of obstructive sleep apnea syndrome during routine unstructured interviews of a standardized patient by primary care physicians.Sleep2004;27,1518-1525. [PubMed]
 
Rotem, AY, Sperber, AD, Krugliak, P, et al Polysomnography and actigraphy evidence of sleep fragmentation in irritable bowel syndrome.Sleep2003;26,746-752
 
Reuveni, H, Simon, T, Tal, A, et al Health care services utilization in children with obstructive sleep apnea syndrome.Pediatrics2002;110,68-72. [CrossRef] [PubMed]
 
Tarasiuk, A, Simon, T, Tal, A, et al Adenotonsillectomy in children with obstructive sleep apnea syndrome reduces health care utilization.Pediatrics2004;113,351-356. [CrossRef] [PubMed]
 
World Health Organization... Collaborating center for drug statistic methodology guidelines for ATC classification and DDD assignment. 2000; World Health Organization. Oslo, Norway:.
 
Thompson, SG, Barber, J How should cost data in pragmatic randomized trials be analyzed?BMJ2000;320,1197-1200. [CrossRef] [PubMed]
 
Pillar, G, Lavie, P Psychiatric symptoms in sleep apnea syndrome: effects of gender and respiratory disturbance index.Chest1998;114,697-703. [CrossRef] [PubMed]
 
Metge, C, Black, C, Peterson, S, et al The population‘s use of pharmaceuticals.Med Care1999;37,JS42-JS59. [CrossRef] [PubMed]
 
Kapsimalis, F, Kryger, MH Gender and obstructive sleep apnea syndrome, part 2: mechanisms.Sleep2002;25,499-506. [PubMed]
 
Berg, G, Delaive, K, Manfreda, J, et al The use of health-care resources in obesity-hypoventilation syndrome.Chest2001;120,377-383. [CrossRef] [PubMed]
 

Figures

Tables

Table Graphic Jump Location
Table 1. The Effect of Age and Gender on Annual Costs of Health-Care Services*
* 

Data are presented as mean US$ ± SEM (median; range).

 

p < 0.001 comparing the control group to OSAS group.

 

p < 0.05 comparing > 65 years to ≤ 65 years of age, Mann-Whitney U test.

§ 

p < 0.001 comparing > 65 years to ≤ 65 years of age, Mann-Whitney U test.

 

Calculated as cost for > 65 years/≤ 65 years of age; the effect of gender on health-care consumption within and between groups was also significant (p < 0.001).

Table Graphic Jump Location
Table 2. The Effect of OSAS on Annual Health-Care Utilization Prior to Diagnosis*
* 

Data are presented as mean ± SEM or %.

 

Data are presented as the percentage of drugs consumed according to World Health Organization classification.

 

The remaining 13 pharmacologic groups.

References

Shahar, E, Whitney, CW, Redline, S, et al (2001) Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the Sleep Heart Health Study.Am J Respir Crit Care Med163,19-25. [PubMed]
 
Newman, AB, Nieto, FJ, Guidry, U, et al Sleep Heart Health Study Research Group. Relation of sleep-disordered breathing to cardiovascular disease risk factors: the Sleep Heart Health Study.Am J Epidemiol2001;154,50-59. [CrossRef] [PubMed]
 
Wittmann, V, Rodenstein, DO Health care costs and the sleep apnea syndrome.Sleep Med Rev2004;8,269-279. [CrossRef] [PubMed]
 
Kryger, MH, Roos, L, Delaive, K, et al Utilization of health care services in patients with severe obstructive sleep apnea.Sleep1996;19,S111-S116. [PubMed]
 
Smith, R, Ronald, J, Delaive, K, et al What are obstructive sleep apnea patients being treated for prior to this diagnosis?Chest2002;121,164-172. [CrossRef] [PubMed]
 
Bahammam, A, Delaive, K, Ronald, J, et al Health care utilization in males with obstructive sleep apnea syndrome two years after diagnosis and treatment.Sleep1999;22,740-747. [PubMed]
 
Ronald, J, Delaive, K, Roos, L, et al Health care utilization in the 10 years prior to diagnosis in obstructive sleep apnea syndrome patients.Sleep1999;22,225-229. [PubMed]
 
Otake, K, Delaive, K, Walld, R, et al Cardiovascular medication use in patients with undiagnosed obstructive sleep apnoea.Thorax2002;57,417-422. [CrossRef] [PubMed]
 
Peker, Y, Hedner, J, Johansson, A, et al Reduced hospitalization with cardiovascular and pulmonary disease in obstructive sleep apnea patients on nasal CPAP treatment.Sleep1997;20,645-654. [PubMed]
 
Kapur, V, Blough, DK, Sandblom, RE, et al The medical cost of undiagnosed sleep apnea.Sleep1999;22,749-755. [PubMed]
 
Tarasiuk, A, Reuveni, H Obstructive sleep apnea syndrome: the dilemma of diagnostic strategy.Isr Med Assoc J2004;6,686-690. [PubMed]
 
Wright, J, Johns, R, Watt, I, et al Health effects of obstructive sleep apnoea and the effectiveness of continuous positive airway pressure: a systematic review of the research evidence.BMJ1997;314,851-860. [CrossRef] [PubMed]
 
Reuveni, H, Tarasiuk, A, Wainstock, T, et al Awareness level of obstructive sleep apnea syndrome during routine unstructured interviews of a standardized patient by primary care physicians.Sleep2004;27,1518-1525. [PubMed]
 
Rotem, AY, Sperber, AD, Krugliak, P, et al Polysomnography and actigraphy evidence of sleep fragmentation in irritable bowel syndrome.Sleep2003;26,746-752
 
Reuveni, H, Simon, T, Tal, A, et al Health care services utilization in children with obstructive sleep apnea syndrome.Pediatrics2002;110,68-72. [CrossRef] [PubMed]
 
Tarasiuk, A, Simon, T, Tal, A, et al Adenotonsillectomy in children with obstructive sleep apnea syndrome reduces health care utilization.Pediatrics2004;113,351-356. [CrossRef] [PubMed]
 
World Health Organization... Collaborating center for drug statistic methodology guidelines for ATC classification and DDD assignment. 2000; World Health Organization. Oslo, Norway:.
 
Thompson, SG, Barber, J How should cost data in pragmatic randomized trials be analyzed?BMJ2000;320,1197-1200. [CrossRef] [PubMed]
 
Pillar, G, Lavie, P Psychiatric symptoms in sleep apnea syndrome: effects of gender and respiratory disturbance index.Chest1998;114,697-703. [CrossRef] [PubMed]
 
Metge, C, Black, C, Peterson, S, et al The population‘s use of pharmaceuticals.Med Care1999;37,JS42-JS59. [CrossRef] [PubMed]
 
Kapsimalis, F, Kryger, MH Gender and obstructive sleep apnea syndrome, part 2: mechanisms.Sleep2002;25,499-506. [PubMed]
 
Berg, G, Delaive, K, Manfreda, J, et al The use of health-care resources in obesity-hypoventilation syndrome.Chest2001;120,377-383. [CrossRef] [PubMed]
 
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