Determinants of Hypercapnia in Obese Patients With Obstructive Sleep Apnea

CHEST

Original Research SLEEP MEDICINE

Determinants of Hypercapnia in Obese Patients With Obstructive Sleep Apnea A Systematic Review and Metaanalysis of Cohort Studies Roop Kaw, MD; Adrian V. Hernandez, MD, MSc, PhD; Esteban Walker, PhD; Loutfi Aboussouan, MD, FCCP; and Babak Mokhlesi, MD, FCCP

Background: Inconsistent information exists about factors associated with daytime hypercapnia in obese patients with obstructive sleep apnea (OSA). We systematically evaluated these factors in this population. Methods: We included studies evaluating the association between clinical and physiologic variables and daytime hypercapnia (PaCO2, > 45 mm Hg) in obese patients (body mass index [BMI], > 30 kg/m2) with OSA (apnea-hypopnea index [AHI], > 5) and with a < 15% prevalence of COPD. Two investigators conducted independent literature searches using Medline, Web of Science, and Scopus until July 31, 2008. The association between individual factors and hypercapnia was expressed as the mean difference (MD). Random effects models were used to account for heterogeneity. Results: Fifteen studies (n ⴝ 4,250) fulfilled the selection criteria. Daytime hypercapnia was present in 788 patients (19%). Age and gender were not associated with hypercapnia. Patients with hypercapnia had higher BMI (MD, 3.1 kg/m2; 95% confidence interval [CI], 1.9 to 4.4) and AHI (MD, 12.5; 95% CI, 6.6 to 18.4) than eucapnic patients. Patients with hypercapnia had lower percent predicted FEV1 (MD, ⴚ11.2; 95% CI, ⴚ15.7 to ⴚ6.8), lower percent predicted vital capacity (MD, ⴚ8.1; 95% CI, ⴚ11.3 to ⴚ4.9), and lower percent predicted total lung capacity (MD, ⴚ6.4; 95% CI, ⴚ10.0 to ⴚ2.7). FEV1/FVC percent predicted was not different between hypercapnic and eucapnic patients (MD, ⴚ1.7; 95% CI, ⴚ4.1 to 0.8), but mean overnight pulse oximetric saturation was significantly lower in hypercapnic patients (MD, ⴚ4.9; 95% CI, ⴚ7.0 to ⴚ2.7). Conclusions: In obese patients with OSA and mostly without COPD, daytime hypercapnia was associated with severity of OSA, higher BMI levels, and degree of restrictive chest wall mechanics. A high index of suspicion should be maintained in patients with these factors, as early recognition and appropriate treatment can improve outcomes. (CHEST 2009; 136:787–796) Abbreviations: AHI ⫽ apnea-hypopnea index; BMI ⫽ body mass index; CI ⫽ confidence interval; FEV1% ⫽ percent predicted FEV1; FEV1/FVC% ⫽ percent predicted FEV1/FVC; MD ⫽ mean difference; OHS ⫽ obesity hypoventilation syndrome; OR ⫽ odds ratio; OSA ⫽ obstructive sleep apnea; %TST Spo2 ⬍ 90% ⫽ percent of total sleep time with pulse oximetric saturation ⬍ 90%; RR ⫽ relative risk; RV% ⫽ percent predicted residual volume; Spo2 ⫽ pulse oximetric saturation; TLC% ⫽ percent predicted total lung capacity; VC ⫽ vital capacity; VC% ⫽ percent predicted vital capacity

hypoventilation syndrome (OHS) is charO besity acterized by obesity, chronic daytime hypercapnia, and sleep-disordered breathing in the absence of other known causes of hypercapnia.1,2 In approximately 90% of patients with OHS, the sleepdisordered breathing consists of obstructive sleep apnea (OSA).3–5 Because screening for hypercapnia www.chestjournal.org

in obese patients with OSA is not done routinely, the exact prevalence of OHS in patients with OSA remains unknown but has been reported to range between 10% and 38%.6 –9 Untreated OHS is associated with a significant increase in morbidity and mortality. Compared with eucapnic patients with OSA, patients with OHS have increased health-care CHEST / 136 / 3 / SEPTEMBER, 2009

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expenses10 and are at higher risk of developing serious cardiovascular disease leading to early mortality.4,11 In a prospective study, the mortality rate at 18 months after hospital discharge was 23% among patients with untreated OHS as opposed to 9% among eucapnic patients with comparable degrees of obesity. More importantly, however, most of the deaths occurred in the first 3 months after hospital discharge.12 In contrast, a retrospective study3,13 of 126 patients with adequately treated OHS reported an 18-month mortality rate of 3%. Therefore, maintaining a high index of suspicion can lead to early recognition and treatment, reducing the high burden of morbidity and mortality associated with undiagnosed and untreated OHS. The mechanism by which obesity leads to chronic daytime hypercapnia is complex and not fully understood. Higher body surface area in obese individuals is associated with an increase in carbon dioxide production.14 However, in the majority of severely obese patients, the increase in carbon dioxide production is accompanied by a concomitant increase in minute ventilation, resulting in a normal Paco2. Therefore, obesity is not the only determinant of hypoventilation because chronic daytime hypercapnia develops in less than one-third of severely obese individuals.6,15 Other mechanisms proposed in the pathogenesis of hypoventilation in obese patients include abnormal respiratory system mechanics due to obesity, impaired central chemoresponsiveness to hypercapnia and hypoxia, sleep-disordered breathing, and neurohormonal abnormalities such as leptin resistance.16 Although obesity has been a well-recognized risk factor for hypercapnia, a limited number of studies6,8,17–19 have shown the effect of excess body weight on hypercapnia. The apnea-hypopnea index (AHI) has been reported by some studies15,20 –23 to be an independent risk factor for the development of hypercapnia. The purpose of our metaanalysis was to Manuscript received March 17, 2009; revision accepted May 22, 2009. Affiliations: From the Department of Hospital Medicine (Dr. Kaw), Medicine Institute, the Department of Outcomes Research (Dr. Kaw), Anesthesiology Institute, the Department of Quantitative Health Sciences (Drs. Hernandez and Walker), Lerner Research Institute, and the Department of Pulmonary, Critical Care, and Allergy (Dr. Aboussouan), Respiratory Institute, Cleveland Clinic, Cleveland, OH; and the Sleep Disorders Center (Dr. Mokhlesi), Section of Pulmonary and Critical Care Medicine, University of Chicago, Chicago, IL. © 2009 American College of Chest Physicians. Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/site/ misc/reprints.xhtml). Correspondence to: Roop Kaw, MD, Department of Hospital Medicine, Medicine Institute Desk A13, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195; e-mail: [email protected] DOI: 10.1378/chest.09-0615

identify the determinants of chronic daytime hypercapnia in obese patients with OSA.

Materials and Methods Study Selection We identified all published studies that evaluated the prevalence of chronic daytime hypercapnia (Paco2, ⱖ 45 mm Hg) in obese patients with OSA. OSA was defined as an AHI of ⱖ 5 events per hour, obesity was defined as a body mass index (BMI) of ⱖ 30 kg/m2. Two investigators (R.K. and A.V.H.) conducted independent comprehensive literature searches of Medline from 1966 to July 31, 2008, the Web of Science from 1980 to July 31, 2008, and Scopus from 1960 to July 31, 2008. A first search used text key words “hypercapnia,” “obstructive sleep apnea,” and “obesity,” and excluded patients ⬍ 15 years old. We also used MeSH and title and abstract terms for the Medline search. The results of the first search were combined with the results of a subsequent search. Terms used in the last search were “obesity hypoventilation syndrome,” “determinants,” “risk factors,” and “cohort studies” or “observational studies.” Review articles and editorials were acceptable if they provided appropriate information for our study. We included studies whose proportions of patients with OSA and/or obesity were high (⬎ 80%). The results of the combined search were limited to studies of humans published in English, Spanish, French, and German. In order to choose potentially relevant articles, the list of retrieved articles was reviewed independently by three investigators (R.K., A.V.H., and E.W.). When multiple articles for a single study had been published, we used the latest publication and supplemented it, if necessary, with data from earlier publications. We contacted authors for missing and additional unpublished data if necessary, and reviewed abstracts of the last 10 years of relevant conferences such as the American College of Chest Physicians, the Associated Professionals Sleep Societies, the European Respiratory Society, and the European Sleep Research Society. Only studies where factor summary values were clearly identified in the tables or text for both the hypercapnic and the eucapnic groups were included in the final data set. We excluded all studies in which the main purpose of the publication was to evaluate a treatment or intervention, unless baseline information for the factor was useful for the purpose of our study. We also excluded studies that only evaluated patients with COPD or overlap syndrome, and studies with ⬍ 10 patients in the hypercapnic and eucapnic groups. Only studies with a small proportion of patients with COPD (⬍ 15%) were included. Data Extraction Data extraction was performed by three investigators (R.K., A.V.H., and E.W.), and the results were compiled. Disagreement was resolved by consensus. Using a standardized data extraction form, we collected the following factors: lead author; publication year; study design; sample size; and proportion of patients with hypercapnia, OSA, obesity, and COPD. The following risk factors were collected from the studies, for both the hypercapnic and eucapnic groups: gender; age; BMI; AHI; percent predicted FEV1 (FEV1%); percent predicted vital capacity (VC%); percent predicted FEV1/FVC (FEV1/FVC%); percent predicted total lung capacity (TLC%); percent predicted residual volume (RV%); mean overnight pulse oximetric saturation (Spo2); and percentage of total sleep time with Spo2 ⬍ 90% (%TST Spo2 ⬍ 90%).

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Study Quality Assessment We developed a priori criteria to assess study quality. Prospective cohort studies were considered to be of higher quality than retrospective cohort studies. If available, case-control studies that were specifically designed to assess the influence of risk factors on the occurrence of hypercapnia were considered to be of higher quality than studies that used a nested case-control design either by identifying cases with hypercapnia by hospital discharge registers or by using existing patient registries. Statistical Analysis We used statistical software (Review Manager, version 5.0 for Windows; The Cochrane Collaboration; Oxford, UK) to pool data for each individual risk factor. For each factor, the mean difference (MD) or the odds ratios (ORs) between hypercapnic and eucapnic patients and 95% confidence intervals (CIs) were calculated. The overall effect of each factor was calculated with the inverse variance method, by using the DerSimonian and Laird random-effects models. Statistical heterogeneity was evaluated with the ␹2 test and the I2 statistic. The overall effect was calculated with the Z test. A p value of ⬍ 0.05 was considered significant. We did not have access to individual patient-level data; therefore, no adjustment was possible for potential confounders of the association between each factor and hypercapnia. Sensitivity Analyses We performed exploratory subgroup analyses to evaluate the consistency of the associations in the following predefined risk factors: age; BMI; AHI; FEV1%; VC%; FEV1/FVC%; TLC%; and mean overnight Spo2. Studies were grouped by race (Asian vs non-Asian) as determinants of OSA may be different in Asian patients due to cephalometric differences in contrast to nonAsian patients. We also controlled for obesity by grouping studies in those of patients with BMIs ⱖ 30 kg/m2 only and those studies with patients with a broader BMI range (ie, both overweight and obese patients) or unclear BMI inclusion criterion. We evaluated studies with ⬎ 100 patients vs ⱕ 100 patients, because associations between risk factors and hypercapnia may be more reliable in larger studies. Finally, we evaluated prospective vs retrospective studies, because prospective studies are of higher quality than retrospective studies. The existence of effect modification in the subgroups was evaluated with the interaction test.

Results Study Characteristics Figure 1 provides details on how an initial search that yielded 314 potential abstracts was reduced to the 15 studies that were included in the metaanalysis (n ⫽ 4,250). The number of patients in each study ranged between 30 and 1,227 (Table 1).21,24 All the studies were published in the last 15 years, with one exception.8 Eleven studies were performed in white populations, and 4 studies7,21,24,25 (n ⫽ 1,572; 38% of total sample) were performed in Japanese patients. Most of the studies were prospective cohorts, with the exception of three studies (n ⫽ 510; 12% of total sample) that were retrospective cohorts.9,15,25 One study25 did not provide information about the gender of patients. The majority of patients were men (n ⫽ 3,305; 81%). www.chestjournal.org

Figure 1. Search strategy profile of the metaanalysis.

As shown in Table 1, six studies clearly identified all the patients as having BMI ⱖ 30 kg/m2, and the remaining nine studies4,6 –9,21,24,26,27 either reported patients with a broader range of BMI or the BMI range was unclear. At least 2,437 patients (69%) were obese (BMI, ⱖ 30 kg/m2). All patients had OSA, defined as an AHI ⱖ 5 events per hour. Nine studies provided information on the presence of COPD. Six studies4,6,15,19,28 specifically excluded patients with COPD as defined by FEV1/FVC ⬍ 70%. Another study29 reported patients with OSA and COPD separately, and patients with COPD were excluded from the analysis. Of the two other studies, Akashiba et al7 reported a very low likelihood of obstructive airways disease (hypercapnic patients, FEV1 76 ⫾ 9% predicted; eucapnic patients, FEV1 80 ⫾ 8% predicted), and Golpe et al9 reported a COPD prevalence of 13% among their patients. Hypercapnia was present in 788 patients (19%). Weighted means and percentages of patients with and without hypercapnia per risk factor are shown in Table 2. Statistical heterogeneity of the effects among studies was present for most factors (p ⬍ 0.05), with the exception of RV% and %TST Spo2 ⬍ 90% (p ⬎ 0.2). Age Thirteen studies6 – 8,11,15,19,21,24 –26,28,29 evaluated the association between age and hypercapnia. Seven hundred thirty-two patients with hypercapnia and 3,231 patients without hypercapnia were included in the study. There was no difference between patients with hypercapnia and eucapnic patients (MD, 0.09 years; 95% CI, ⫺1.76 to 1.93; p ⫽ 0.9). Gender Eight studies6,8,11,15,19,21,29 evaluated the association with gender. These studies included 563 paCHEST / 136 / 3 / SEPTEMBER, 2009

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Table 1—Characteristics of Studies Included in the Metaanalysis BMI ⬎ 30

Men Study Akashiba et al7 Akashiba et al25 Banarjee et al28 Chin et al24 Golpe et al9 Javaheri et al26 Kawata et al21 Kessler et al11 Laaban et al6 Leech et al8 Mokhlesi et al15 Mokhlesi et al15 Resta et al19 Resta et al29 Weitzenblum et al27 Total

Year

Country

2002 2006 2007 1997 2002 1994 2007 2001 2005 1987 2007A 2007B 2000 2000 1999

Japan Japan Australia Japan Spain United States Japan France France United States United States United States Italy Italy France

Patients, No. 143 172 46 30 175 55 1,227 254 1,141 111 163 359 65 197 112 4,250

No.

%

No.

143 ? 25 29 156 55 1091 223 943 75 75 218 32 132 108 3,305

100 ? 54 97 89 100 89 88 83 68 46 61 49 67 96 81

57 172 46 ? ? ? 614 ? 764 ? 163 359 65 197 ? 2,437

AHI ⬎ 5

% 40 100 100 Approximately Approximately Approximately 50 Approximately 67 ? 100 100 100 100 Approximately 69

36 60 90 70

50

COPD

Hypercapnia

No.

%

No.

%

No.

%

143* 172‡ 46§ 30* 175* 55† 1,227§ 254‡ 1,141* 111* 163§ 359§ 65* 197* 112† 4,250

100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100

0 ? 0 ? 22 ? ? 0 0 ? 0 0 0 0 ? 22

0 ? 0 ? 13 ? ? 0 0 ? 0 0 0 0 ? 1

55 55 23 13 24 32 178 34 126 41 52 89 24 29 13 788

38 32 50 43 14 58 15 13 11 37 32 25 37 15 12 19

? ⫽ not reported. *OSA defined as AHI ⬎ 10. †OSA defined with an unreported AHI threshold. ‡OSA defined as AHI ⬎ 20. §OSA defined as AHI ⬎ 5.

tients with hypercapnia and 2,368 patients without hypercapnia. Gender was not associated with hypercapnia (OR, 0.96; 95% CI, 0.62 to 1.50; p ⫽ 0.9). BMI

710 hypercapnic patients and 3,289 eucapnic patients. The AHI was significantly higher in patients with hypercapnia (MD, 12.51; 95% CI, 6.59 to 18.44; p ⬍ 0.0001) [Fig 3]. FEV1%

Fourteen studies evaluated the association with BMI. Seven hundred twenty-eight hypercapnic patients and 3,511 eucapnic patients were included in the study. BMI was significantly higher in hypercapnic patients (MD, 3.13 kg/m2; 95% CI, 1.85 to 4.42; p ⬍ 0.00001) [Fig 2].

Eleven studies evaluated the association with FEV1%. These studies included 665 patients with hypercapnia and 3,245 patients without hypercapnia. The FEV1% was significantly lower in patients with hypercapnia (MD, ⫺11.22; 95% CI, ⫺15.67 to ⫺6.78; p ⬍ 0.00001) [Fig 4].

AHI

VC%

Thirteen studies evaluated the association between AHI and hypercapnia. The studies included

Nine studies evaluated the association between VC% and hypercapnia. The studies included 605

Table 2—Weighted Averages for Hypercapnic and Eucapnic Patients, and Associations Between Individual Determinants and Hypercapnia Weighted Mean (95% CI) Determinant

Studies, No.

Hypercapnic

Eucapnic

MD (95% CI)

p Value

Age % Male gender BMI AHI FEV1% VC% FEV1/FVC% TLC% RV% Mean Spo2 %TST Spo2 ⬎ 90%

13 8 14 13 11 9 9 6 3 7 3

50.00 (46.74 to 53.26) 69.1* (57.4 to 80.8) 38.94 (34.2 to 43.9) 63.7 (51.9–75.5) 70.87 (62.77 to 78.97) 84.97 (71.92 to 98.03.7) 78.50 (73.94 to 83.05) 77.43 (69.81 to 85.05) 91.59 (69.93 to 113.24) 85.48 (83.81 to 87.14) 56.16 (42.47 to 69.87)

49.91 (47.61 to 52.23) 69.2* (53.6 to 84.8) 35.81 (31.1 to 41.2) 51.19 (42.3–60.1) 82.09 (75.17 to 89.0) 93.10 (81.86 to 104.34) 80.16 (76.62 to 83.69) 83.81 (78.64 to 88.98) 89.76 (62.31 to 117.19) 90.34 (87.87 to 92.81) 18.80 (⫺9.86 to 47.47)

0.09 (⫺1.76 to 1.93) OR 0.96 (0.62 to 1.50) 3.13 (1.85 to 4.42) 12.51 (6.59 to 18.44) ⫺11.22 (⫺15.67 to ⫺6.78) ⫺8.13 (⫺11.33 to ⫺4.93) ⫺1.66 (⫺4.06 to 0.75) ⫺6.38 (⫺10.04 to ⫺2.72) 1.83 (⫺6.00 to 9.66) ⫺4.86 (⫺6.99 to ⫺2.74) 37.36 (29.76 to 44.97)

0.9 0.9 ⬍ 0.00001 ⬍ 0.0001 ⬍ 0.00001 ⬍ 0.00001 0.2 0.0006 0.7 ⬍ 0.00001 ⬍ 0.00001

*Weighted mean percentage. 790

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Figure 2. Forest plots of the association between BMI and hypercapnia.

patients with hypercapnia and 2,996 patients without hypercapnia. The VC% was significantly lower in patients with hypercapnia (MD, ⫺8.13; 95% CI, ⫺11.33 to ⫺4.93; p ⬍ 0.00001) [Fig 5].

with hypercapnia and 325 patients without hypercapnia. The RV% was not different between hypercapnic patients and eucapnic patients (MD, 1.83; 95% CI, ⫺6.00 to 9.66; p ⫽ 0.2).

FEV1/FVC%

Mean Overnight SpO2

Nine studies evaluated the association with FEV1/FVC%. These studies included 360 hypercapnic patients and 1,008 eucapnic patients. The FEV1/FVC% was nonsignificantly lower in patients with hypercapnia (MD, ⫺1.66; 95% CI, ⫺4.06 to 0.75; p ⫽ 0.2).

Seven studies evaluated the association between mean overnight Spo2 and hypercapnia. The studies included 378 patients with hypercapnia and 1,792 patients without hypercapnia. The mean overnight Spo2 was significantly lower in patients with hypercapnia (MD, ⫺4.86; 95% CI, ⫺6.99 to ⫺2.74; p ⬍ 0.00001) [Fig 7].

TLC%

%TST SpO2 ⬍ 90%

Six studies evaluated the association with TLC%. The studies included 241 patients with hypercapnia and 827 patients without hypercapnia. The TLC% was significantly lower in patients with hypercapnia (MD, ⫺6.38; 95% CI, ⫺10.04 to ⫺2.72; p ⫽ 0.0006) [Fig 6].

Three studies evaluated the association with %TST Spo2 ⬍ 90%. These studies included 87 patients with hypercapnia and 429 patients without hypercapnia. The %TST Spo2 ⬍ 90% was significantly higher in patients with hypercapnia (MD, 37.36; 95% CI, 29.76 to 44.97; p ⬍ 0.00001) [Fig 8].

RV%

Subgroup Analyses

Three studies7,11,24 evaluated the association with RV%. These studies included 102 patients

In general, the associations between risk factors and hypercapnia did not change when subgrouping

Figure 3. Forest plots of the association between AHI and hypercapnia. www.chestjournal.org

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Figure 4. Forest plots of the association between FEV1 percent predicted and hypercapnia.

by race, BMI criterion, sample size, or type of study. Effect modification by race and BMI was found for a few risk factors. However, these findings should be taken with caution given the small number of studies within subgroups and the low power of the interaction tests to detect significant subgroup effects. In two studies21,25 with Asian patients, hypercapnic patients had a nonsignificantly lower FEV1% (MD, ⫺1.37; 95% CI, ⫺3.83 to 1.10; p ⫽ 0.3). In contrast, this difference was significant in nine studies6,8,9,11,15,19,28,29 with non-Asian patients (MD, ⫺14.02; 95% CI, ⫺19.94 to ⫺8.10; p ⬍ 0.00001; p ⬍ 0.00001 [for interaction]). In three studies15,25 with BMI ⱖ 30 kg/m2, hypercapnic patients had significantly lower VC% than eucapnic patients (MD, ⫺8.90; 95% CI, ⫺16.08 to ⫺1.71). This significant association was also found in six studies6,7,11,21,24,27 with unclear/broad BMI (⫺6.92; 95% CI, ⫺9.75 to ⫺4.10), although the effects between subgroups were different (p ⫽ 0.0005 [for interaction]). Discussion Main Findings Our metaanalysis confirms that in obese patients without evidence of obstructive airways disease,

chronic daytime hypercapnia is associated with the following three factors: the severity of OSA (as measured by AHI or the degree of nocturnal hypoxemia); BMI; and the degree of restrictive chest wall mechanics. More importantly, the severity of OSA and the impairment of respiratory system mechanics are closely associated with the degree of obesity. Specifically, lower FEV1, vital capacity (VC), TLC, minimum overnight Spo2, and higher AHI are associated with hypercapnia. Clinical Relevance In obese patients, the development of chronic daytime hypercapnia may be an end product of complex factors including impaired chest wall mechanics, severity of obesity, severity of OSA, altered central chemosensitivity, or abnormal respiratory muscle strength. The presence of COPD (or airways obstruction) is a major confounder in the study of daytime hypercapnia in obese patients with OSA. In studies17,30,31 that did not exclude patients with COPD, both FEV1 and FEV1/FVC ratio were lower in hypercapnic patients with OSA compared with those patients with eucapnic OSA. The few studies17,31,32 that have reported the presence of airways obstruction as the main risk factor for the development of chronic daytime hypercapnia in obese pa-

Figure 5. Forest plots of the association between VC% and hypercapnia. 792

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Figure 6. Forest plots of the association between TLC% and hypercapnia.

tients with OSA had a high proportion of patients with COPD and overall lower degrees of obesity. Indeed, Resta et al31 confirmed this finding by demonstrating that in obese patients with OSA and COPD, also known as overlap syndrome, hypercapnia was related to the degree of airways obstruction. In contrast, in obese patients with OSA but no evidence of obstructive airways disease, hypercapnia was related to the degree of restrictive ventilatory defect and the severity of OSA as measured by the degree of nocturnal oxyhemoglobin desaturation.29 In our analysis, six studies4,6,15,19,28 excluded patients with COPD or evidence of airways obstruction (FEV1/FVC, ⬍ 70%), and the overall pool had a very small number of patients with COPD (mean FEV1/FVC, 79%). These findings suggest that chronic daytime hypercapnia can occur in obese patients with OSA independent of obstructive airways disease or COPD. Several studies have reported an association between BMI and hypercapnia in patients with OSA4,8,17,18 even after excluding those patients with COPD or FEV1/FVC ⬍ 70%.6,19 The association between hypercapnia and obesity can be explained on the basis that increasing severity of obesity can lead to restrictive chest wall mechanics and/or increase the severity of OSA. Studies7,19 of severely obese patients with OSA but without COPD have consistently shown that chronic daytime hypercapnia is significantly associated with measures of respiratory system mechanics, mean nocturnal Spo2 saturation, and %TST Spo2 ⬍ 90%. Akashiba et al7

reported the mean overnight Spo2 during sleep and the severity of restrictive impairment as measured by VC% as the major factors explaining approximately one-half of the variance in the Paco2 (R2 ⫽ 0.43; p ⬍ 0.0001). In that study, AHI and BMI were not independent risk factors possibly because BMI correlated with VC (r ⫽ ⫺0.300; p ⬍ 0.01). To correct for any effects of obesity, the same group of investigators compared hypercapnic patients with OSA (n ⫽ 55) to markedly obese patients with eucapnic OSA (n ⫽ 117).25 The only significant differences were observed in Paco2 (p ⫽ 0.001), pH (p ⫽ 0.001), VC% (p ⫽ 0.046), and FEV1% (p ⫽ 0.049). Of all these variables, VC% most closely correlated with Paco2 (r ⫽ ⫺0.455; p ⬍ 0.0009). Laaban and Chailleux,6 in their study of 1,141 patients with OSA who did not have any evidence of obstructive airways disease or COPD (mean FEV1/ FVC, ⱖ 80%; FEV1, ⱖ 70% predicted), reported the presence of daytime hypercapnia in 126 patients (11%) with OSA. Chronic daytime hypercapnia was related to the severity of obesity (7.2% in patients with BMI ⬍ 30 kg/m2 vs 23.6% in patients with BMI ⬎ 40 kg/m2; relative risk [RR], 1.68) and to obesity-related impairment in respiratory system mechanics (FEV1, ⬍ 90% predicted [RR, 2.23; p ⬍ 0.001]; VC, ⬍ 91% predicted [RR, 2.20; p ⬍ 0.001]). However, BMI, FEV1, VC, and Pao2 explained only 9% of the variance in Paco2 levels. Other investigators15,20 have likewise found that the prevalence of hypercapnia in patients with OSA is higher in those patients with severe obesity (BMI,

Figure 7. Forest plots of the association between mean overnight Spo2 and hypercapnia. www.chestjournal.org

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Figure 8. Forest plots of the association between %TST Spo2 ⬍ 90% and hypercapnia.

⬎ 40 kg/m2) vs patients with OSA and moderate obesity (BMI, ⱖ 30 but ⬍ 40 kg/m2). A variety of measures of severity of OSA (eg, AHI, mean overnight Spo2, minimum Spo2 during sleep, or %TST Spo2 ⬍ 90%) have been reported to be independent predictors of hypercapnia by several studies.15,19 –21 Indeed, Resta et al20 reported that %TST Spo2 ⬍ 90% and AHI accounted for 24% and 20%, respectively, of the total variance of daytime Paco2. More recently, a large study21 of Japanese patients with OSA showed only AHI to be a predictor of hypercapnia, although this index was not independent of BMI. Serum bicarbonate levels can increase due to metabolic compensation for chronic respiratory acidosis in patients with OHS. In fact, serum bicarbonate can be used as a clinical predictor (but not a mechanistic predictor) of hypercapnia. In a prospective study, Mokhlesi et al15 demonstrated that serum bicarbonate levels can be used as a highly sensitive screening tool to rule out hypercapnia in obese patients with OSA given that a normal serum bicarbonate level effectively excluded hypercapnia. However, our metaanalysis could not establish clinically useful cutoffs for the significant determinants of hypercapnia, because we did not have access to individual patient data on determinants from every cohort. The AHI could be considered as a collinear variable for BMI (given the increasing prevalence and severity of OSA with increasing BMI) and mean overnight Spo2, especially in cases of extreme obesity. Mokhlesi et al15 reported that although BMI was associated with hypercapnia in a univariate analysis, it did not remain a significant independent predictor of hypercapnia after adjustment, possibly because of its strong correlation with AHI and lowest oxygen saturation during sleep. Moreover, Labaan and Chailleux6 reported a prevalence of hypercapnia in 7.2% of patients with OSA who were not obese (BMI, ⬍ 30 kg/m2) and did not have evidence of obstructive airways disease or COPD. This finding suggests a relationship between OSA and daytime hypercapnia independent of obesity and respiratory system mechanics. The role of OSA in the pathogenesis of hypoventilation has been well established by

the resolution of hypercapnia in the majority of patients with hypercapnic OSA or OHS with shortterm treatment with either positive airway pressure therapy or tracheostomy. This improvement occurs without any significant changes in body weight or respiratory system mechanics.33–36 It has been demonstrated37,38 that the resolution of OSA by continuous positive airway pressure can lead to the improvement or resolution of chronic daytime hypercapnia by increasing central chemoresponsiveness and improvement in the hypercapnic ventilatory response. Limitations Although our metaanalysis did establish a convincing association between chronic daytime hypercapnia, measures of chest wall restriction, and underlying severity of OSA, we were limited in our analysis by the degree of heterogeneity between studies. Several small studies9,11,24,26,27 included in the metaanalysis (the largest of which had 254 patients) [Table 1] did not report the mean BMI but only that 70% of those patients included were obese (BMI, ⱖ 30 kg/m2). Six of the studies4,6,15,19,28 purposefully excluded patients with COPD. In the overall group of patients included in our metaanalysis, ⬍ 10% of patients with hypercapnia had COPD. However, the exact percentage of COPD in these studies remains unclear as various cutoffs of FEV1/FVC were used to define COPD. Various cutoffs of AHI were used in the studies to define OSA. Four studies15,21,28 defined OSA by using an AHI ⱖ 5 (19% with hypercapnia; 342 of 1,795 patients); seven studies6 –9,19,24,29 used an AHI ⱖ 10 (17% with hypercapnia; 312 of 1,862 patients); and two studies11,25 used an AHI ⱖ 20 to define OSA (21% with hypercapnia; 89 of 426 patients). There was no statistically significant difference among these proportions (p ⫽ 0.6). Two studies26,27 did not report an AHI cutoff for defining OSA. Additionally, even though impairments in the respiratory system mechanics and AHI have been implicated as being contributory to the development of chronic daytime hypercapnia, other factors may be involved in its development in obese patients with

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OSA who do not have obstructive airways disease. These factors could include anthropometric characteristics and patterns of fat distribution, neurohormonal abnormalities such as leptin resistance, or genetic differences.19 Several studies24,26,33,39 – 41 have reported a reduced ventilatory response to both hypercapnia and hypoxia in patients with OHS or hypercapnic OSA compared with eucapnic patients with OSA. Our metaanalysis did not include respiratory drive as one of the exploratory variables for the development of chronic daytime hypercapnia in obese patients with OSA given the small number of studies that have assessed ventilatory responsiveness in these patients. In summary, a growing number of studies originating from various geographic regions have reported a high prevalence of hypercapnia among obese patients with OSA. The prevalence of hypercapnia is likely to increase due to the global obesity epidemic. Compared with patients with similar degrees of obesity and similar severity of OSA, hypercapnic patients have increased health-care expenses and are at higher risk for the development of serious cardiovascular disease, leading to early mortality. Despite the significant morbidity and mortality associated with hypercapnic OSA, it is often unrecognized, and treatment is frequently delayed. Our study provides further evidence that clinicians can use several physiologic parameters that are routinely available (eg, severity of BMI, pulmonary function test variables, and the severity of OSA) to maintain a high index of suspicion, because the early recognition and treatment of these patients can improve outcomes. Further research is needed to establish and validate particular thresholds for BMI, measures of severity of OSA (eg, AHI and minimum oxygen saturation during sleep), and pulmonary function test variables in order to assist clinicians in screening obese patients with OSA who are at increased risk for hypercapnia. Ultimately, these individuals should undergo a measurement of arterial blood gases in order to confirm the presence of hypercapnia and to establish the diagnosis of OHS.

Acknowledgments Author contributions: Drs. Kaw, Hernandez, and Walker contributed to the conception and design of this article. Drs. Hernandez, Kaw, and Walker were responsible for the acquisition of data. Drs. Hernandez, Kaw, Walker, Aboussouan, and Mokhlesi were responsible for the analysis and interpretation of the data. Drs. Kaw, Hernandez, Walker, and Mokhlesi contributed to the drafting of the article. Drs. Hernandez, Kaw, Walker, Aboussouan, and Mokhlesi contributed to the critical revision of the article for important intellectual content. Drs. Kaw, Hernandez, Walker, Aboussouan, and Mokhlesi contributed to the final approval of the article. Drs. Hernandez and Walker provided statistical expertise. Drs. Kaw, Hernandez, Walker, and Mokhlesi provided study supervision. www.chestjournal.org

Financial/nonfinancial disclosures: 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.

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