Is the Berlin questionnaire a useful tool to diagnose obstructive sleep apnea in the elderly?

Sleep Medicine 12 (2011) 142–146

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Original Article

Is the Berlin questionnaire a useful tool to diagnose obstructive sleep apnea in the elderly? Emilia Sforza a,⇑, Florian Chouchou a, Vincent Pichot a, François Herrmann b, Jean Claude Barthélémy a, Frédéric Roche a a Service de Physiologie Clinique et de l’Exercice, CHU Nord, Saint-Etienne, Faculté de Médecine Jacques Lisfranc, PRES Université de Lyon 42023, Université Jean Monnet, Saint-Etienne, France b Geriatric Department, University Hospital of Geneva, Geneva, Switzerland

a r t i c l e

i n f o

Article history: Received 13 May 2010 Received in revised form 16 August 2010 Accepted 10 September 2010 Available online 11 January 2011 Keywords: Epidemiology Elderly Sleep apnea Berlin questionnaire Screening Aging

a b s t r a c t Objective: In the elderly, obstructive sleep apnea (OSA) is frequently under diagnosed. This study was undertaken to assess the accuracy of the Berlin questionnaire to diagnose OSA in a large healthy elderly population. Patients and methods: Six hundred forty-three participants aged 65.6 years were examined. All subjects completed the Berlin questionnaire and underwent at-home respiratory recording. Presence of OSA was defined by an AHI > 15. Results: Of the respondents, 202 subjects (31.4%) were in an OSA high-risk group according to the Berlin questionnaire. The high-risk subjects were significantly heavier, had greater waist and hip circumferences, higher AHI, and reported more frequently hypertension and diabetes. Habitual snoring was present in 54% of the sample, sleepiness in 12% of participants, and a BMI > 30 and a history of hypertension in 42.1%. Being in the high-risk group predicted an AHI > 15 with a sensitivity of 77%, a specificity of 39%, a positive predictive value of 63% and a negative predictive value of 55%. Among Berlin questionnaire categories, snoring correctly classified 61% of the sample and explained the 5% variance of AHI. Conclusions: The Berlin questionnaire did not provide a high level of diagnostic specificity to discriminate OSA in an elderly population. Although not sufficiently accurate, this questionnaire can be used to identify subjects for sleep study assessment. Ó 2010 Elsevier B.V. All rights reserved.

1. Introduction Obstructive sleep apnea (OSA) is a common sleep disorder characterized by repetitive nocturnal respiratory airflow cessation, hypoxemia and sleep fragmentation, affecting 2–4% of middle-aged population [1,2]. High prevalence rates of OSA were found in an elderly population (P65 years old) [3], 30.5% [4]–81% [5] having an apnea-hypopnea index (AHI) P 5, and 39% of women and 51% of men having an AHI > 20 [5,6]. Undiagnosed, and thus untreated, OSA is associated with severe morbidity and mortality essentially related to the OSA cardiovascular and cerebrovascular risk [6–11]. Polysomnography is the gold standard diagnostic tool for assessing OSA, but only a minority of patients at risk of OSA have access to polysomnography, owing to its technical requirements, labor-intensive procedures and cost. Portable respiratory monitoring was recently introduced as a valid tool for diagnosis of OSA [12] ⇑ Corresponding author. Address: Service de Physiologie Clinique, EFCR, CHU Nord – Niveau 6, F-42055, Saint-Etienne, Cedex 2, France. Tel.: +33 (0)4 77 82 83 00; fax: +33 (0)4 77 82 84 47. E-mail address: [email protected] (E. Sforza). 1389-9457/$ - see front matter Ó 2010 Elsevier B.V. All rights reserved. doi:10.1016/j.sleep.2010.09.004

in a clinical setting and in the elderly [13]. Despite being less complex than a full polysomnography, portable devices still entail a demanding examination and most sleep laboratories, already overburdened, are unable to diagnose all referred patients within a reasonable time. Moreover, from an epidemiological point of view, an efficient pre-selection procedure with an inexpensive and accurate method of screening, such as a questionnaire, can be conveniently incorporated for diagnostic purposes and follow-up studies to establish the still controversial question of hypertensive risk and vascular morbidity in elderly OSA patients. The Berlin questionnaire [14] is a widely used screening tool in the clinical evaluation of OSA, identifying in a primary care population 37.5% of patients as being at high risk to have an AHI > 5, with a sensitivity and specificity of, 86% and 77%, respectively. The predictive performance of the Berlin questionnaire for OSA, however, may vary in different patient populations, the sensitivity ranging from 54% to 86% and the specificity from 43% to 77% [15,16]. Although the Berlin questionnaire may be a useful tool in research and sleep medicine, it has never been validated in elderly subjects in whom the prevalence of OSA is significantly higher.

E. Sforza et al. / Sleep Medicine 12 (2011) 142–146

The objective of the current study was to evaluate the Berlin questionnaire as a screening tool for OSA in a large generally healthy population and to assess which symptoms better predict OSA occurrence. 2. Material and methods 2.1. Subjects Participants were from the PROOF study [17], a prospective cohort study of 1011 community-dwellers aged 65 years at the study entry, and randomly recruited from the electoral lists of the city of Saint-Etienne, France. An ancillary study addressing the association between OSA assessed by at-home polygraphic study and cardiovascular and cerebrovascular morbidity during a 7-year follow-up was proposed to participants (SYNAPSE study). The study methods have been reported previously [17,18]. Briefly, of the original sample of 1011, 851 subjects (58.5% women) participated in the SYNAPSE study. Inclusion criteria to participate in the SYNAPSE study were absence of prior diagnosis or treatment for OSA, myocardial infarction, heart failure, stroke, and neurological or psychiatric disorders. From the SYNAPSE sample, we included subjects having the following inclusion criteria: (1) acceptance to perform home sleep monitoring; (2) acceptable quality and duration of the sleep study; (3) ability to complete the French version of the Berlin questionnaire; and (4) complete clinical, anthropometric and questionnaire data. After exclusion, a sample of 643 participants (59.1% females) aged 65.6 ± 0.03 years was examined. When compared to excluded subjects, the final sample did not differ in any variables, including gender, daytime sleepiness, and incidence of prior disease. The study was approved by the local ethics committee (CCPPRB Rhône-Alpes, Loire, France) and written informed consent was obtained from all participants. 2.2. Clinical and instrumental data Detailed clinical assessment was focused on smoking and alcohol habits, the presence of cardiac, neurological or cerebrovascular diseases, hypertension, obstructive or restrictive lung disease, metabolic disorders and psychiatric diseases. Current medication with regard to antihypertensive therapy, hypnotic, anxiolytic or antidepressant therapy was also studied. Subjects were defined as normotensive if they did not report a history of hypertension and antihypertensive treatment and did not have, at the ambulatory blood pressure monitoring (ABPM) (Diasoft, Novavor, Rueil Malmaison, France), a mean systolic blood pressure > 135 mm Hg and a mean diastolic blood pressure > 85 mm Hg. During the clinical evaluation, body mass index (BMI) was calculated as weight (kg)/height squared (kg/m2). Neck circumference (NC) was measured in the midway of the neck between midcervical spine and mid-anterior neck to 0.5 cm just below the laryngeal prominence. Waist circumference (WC) was measured midway between the lower rib margin and the iliac crest and hip circumference (HC) measured at the level of the two bony prominences in the front of the hips. 2.3. Questionnaires Risk for sleep apnea was assessed with the Berlin Questionnaire at study entry. The Berlin Questionnaire (BQ) inquires about snoring behavior, sleepiness or fatigue and the presence of obesity and hypertension [14]. The questionnaire included 1 introductory and 4 follow-up questions including snoring history (5 questions), 3 questions about daytime somnolence (including 1 concerning

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sleepiness while driving), and 1 question about history of hypertension and/or body mass index (BMI) > 30. It also collects information about age, gender, height and weight. Obesity was quantified by BMI as calculated from self-reported weight and height expressed as kilograms per square meter. The determination of lower and higher probability was based on the chronic nature and severity of several reported symptoms. To have a high pretest probability, respondents were considered to be at high risk (HR) for OSA if they had (1) 2 of 4 questions positive in category 1 (snoring) that indicated presence of persistent snoring (more than 3–4 times a week) with snoring sufficiently loud to be heard in the next room, and/or persistent apneas (more than 3–4 times a week or everyday); (2) persistent daytime somnolence (>3 times per week), and/or having fallen asleep while driving (category 2); and (3) presence of hypertension or a BMI > 30 kg/m2. In other words, a questionnaire had to have 2 of the 3 categories positive to be considered as indicating a high pretest probability for OSA. Subjects who denied chronic symptoms or had chronic symptoms or signs in only 1 category were placed in the ‘‘lower pretest probability’’ (low risk: LR). During the clinical evaluation, all subjects answered the Epworth sleepiness scale (ESS) [19], and the presence of excessive daytime sleepiness was retained for a score >10. The St. Mary’s Hospital Questionnaire (a 9-item multiple choice self administered questionnaire) was used to assess perception of quality of sleep and the estimated sleep duration during the night of sleep monitoring [20]. The mini-mental-state examination (MMSE) [21] was administered to evaluate global cognitive functioning. This 30-item test measures different cognitive components, including orientation, attention, immediate and short-term recall, language, and the ability to follow commands, with possible scores ranging from 0 to 30. 2.4. Sleep study All subjects underwent full night at-home polygraphic recording with time in bed scheduled between 22:00–23:00 h and 06:00–07:00 h, which represented their average sleep periods. Nocturnal unattended home-sleep study was performed using a polygraphic system (HypnoPTT, Tyco Healthcare, Puritan Bennett, CO, USA), which included the following parameters: sound measurement, electrocardiogram, pulse transit time, R-R timing, airflow by nasal pressure, thoracoabdominal respiratory efforts by 1 inductance plethysmography, body position and oxygen saturation (SaO2) measured by pulse oximetry. This device is similar to other accepted methods to detect presence of OSA in middle-aged adults and the elderly [13,22]. A software package was used for downloading and visual analysis of tracings. To minimize potential overestimation of sleep duration, subjects completed the St. Mary’s Hospital questionnaire and wakefulness before lights-off was excluded by the analyses. A recording was considered acceptable if P5 h of recording without missing data on respiratory signals and SaO2 was obtained. A second night of monitoring was performed when subjective sleep latency exceeded 2 h on the first night, sleep duration was <5 h or when the respiratory recording was considered as unacceptable for more than 40% of the total recording. A single researcher who had no knowledge of the questionnaire results performed the scoring. Hypopnea was defined as a 50% or greater reduction in airflow from baseline value lasting at least 10 s and associated with at least 3% oxygen desaturation. Apneas were defined as the absence of airflow on the nasal cannula lasting >10 s. The absence of rib cage movements associated with an apnea defined the event as central, while progressive increase in pulse transit time and respiratory efforts allowed definition of the event as obstructive. The AHI was established as the ratio of the number of apneas and hypopneas

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per hour of recording. Indices of nocturnal hypoxemia were the following: mean SaO2; % of recording time below 90%; minimal SaO2 value recorded during sleep and the oxygen desaturation index (ODI), i.e., the number of episodes of oxygen desaturation per hour of recording time during which blood oxygen fell by 3% or more. Pulse transit time was continuously monitored and, according to previously defined criteria [23], an autonomic respiratory-related index (AArespI) and a total autonomic arousal index (AAI) were calculated. An AHI > 15 with at least 50% of events scored as obstructive was considered diagnostic of OSA [5,24]. Cases were stratified as mild (AHI > 15 < 30) and moderate to severe cases (AHI > 30).

3. Statistical analyses The subjects’ characteristics were summarized as means ± SEM for continuous variables, and counts and percentages for categorical variables. Comparisons between low-risk and high-risk groups were performed using the v2-test for categorical variables and the t-Student test for continuous variables. Sensitivity, specificity, positive and negative predictive values of the Berlin questionnaire were calculated for the whole sample, as well as for males and females, considering an AHI > 15 as the cutoff point for OSA. The predictive accuracy of risk grouping for each of the Berlin items was also measured. Pearson correlation coefficients were calculated to determine the relationship between AHI and clinical variables, and multivariate regression analysis was performed to define the contribution of anthropometric, diurnal and nocturnal variables in explaining the AHI variations. Table 1 Clinical, anthropometric and polygraphic data for the subjects at high and low risk for OSA.

Age (years) BMI (kg/m2) Neck circumference (cm) Waist circumference (cm) Hip circumference (cm) Hypertension (%) Diabetes (%) Dyslipidemie (%) Smoking (%) Total subjective sleep time (h) AHI (n/h) ODI (n/h) Minimal SaO2 (%) SaO2 < 90% (%) Snoring index (n/h) AArespI (n/h) AAI (n/h) MMSE score ESS score

Low risk n = 441

High risk n = 202

p

65.6(0.04) 24.5(0.2) 36.2(0.2) 83.8(0.5) 96.8(0.4) 17.1 2.5 22.1 15.6 6.8(0.7) 18.9(0.7) 7.3(0.4) 90.4(0.2) 1.2(0.2) 38.2(3.2) 13.7(0.4) 39.0(0.9) 28.7(0.1) 5.4(0.2)

65.6(0.06) 27.1(0.3) 38.2(0.3) 91.3(0.8) 101.1(0.6) 25.4 3.3 12.8 10.0 6.8(0.1) 27.5(1.2) 12.7(0.8) 88.8(0.3) 3.1(0.5) 82.9(6.8) 18.4(0.8) 42.0(1.5) 28.4(0.1) 5.9(0.3)

ns 0.004 ns 0.05 0.05 <0.001 0.001 0.03 0.01 ns 0.001 <0.001 0.02 <0.001 <0.001 0.001 <0.001 ns ns

BMI: body mass index; AHI: apnea + hypopnea index; AArespI: autonomic arousal related to respiratory events; AAI: total autonomic arousal index; ESS: Epworth sleepiness scale; MMSE: mini-mental-state examination; ODI: oxygen desaturation index. p = v2 or unpaired t-Student.

All statistical analyses were conducted using the SPSS statistical software package (SPSS for Windows, version 12.0, SPSS, Chicago, IL). After Bonferroni’s correction a two-tailed value of p 6 0.05 was considered significant. 4. Results 4.1. Characteristics of the sample A total of 643 subjects, 380 women and 263 men aged 65.6 ± 0.03 years were analysed. Their mean BMI was 25.3 ± 0.2 kg/m2 and their mean waist and hip circumference, respectively, 86.1 ± 10.4 cm and 98.1±.0.3 cm. The mean ESS score was 5.59 ± 0.2, 9% of subjects reporting daytime sleepiness. An AHI > 15 was identified in 369 (57.8%) subjects, 193 women and 176 men, males having a higher AHI (36.1 ± 1.9) compared to women (27.1 ± 1.9) (p < 0.001). The mean MMSE score was 28.7 ± 0.1, 10 having a value below 24 and 42 between 24 and 27. Berlin category 1 (habitual snoring) criteria were observed in 347 subjects (54.0%). Excessive daytime sleepiness (category 2) was reported by 77 subjects (12%), and a BMI > 30 and history of hypertension (category 3) were present in 271 subjects (42.1%). Overall the Berlin questionnaire categorized 202 subjects (31.4%) into a high-risk group. The characteristics of the subjects in the HR and LR groups for OSA are outlined in Table 1. The prevalence of obesity and hypertension was significantly higher in the HR group than in the LR group, the subjects in the HR group having higher BMI and greater neck (p = 0.06), waist and hip circumferences (p = 0.05). The ESS score was similar in HR and LR subjects. As expected, statistically significant differences were found between groups for polygraphic data, subjects with HR having increased snoring time, more severe hypoxemia, greater AHI and higher indices of sleep fragmentation. The predictive value of the overall score of the Berlin questionnaire to identify OSA is shown in Table 2. At a cut-off of AHI > 15, the Berlin questionnaire had a sensitivity of 76.7%, a specificity of 39.3%, a positive prediction value of 63.2% and a negative predictive value of 55.4%. Overall it correctly classified 61.6% of the total population and explained the 4.3% of variance in the AHI. When we considered the three different categories of the Berlin questionnaire (Table 3) we found that category 1 of the Berlin questionnaire had better sensitivity (63.4%) and specificity (58.8%) compared to categories 2 and 3, stressing the predictive role of frequency of snoring in diagnosis. The same analysis was conducted putting the AHI threshold to >30 indicating severe OSA. At this cutoff value the total Berlin questionnaire score demonstrated greater specificity (76.6%) but lower sensitivity (23.4%), the snoring category score being again more accurate than scores of categories 2 and 3 (Table 3). In order to estimate whether altered cognitive function might affect the Berlin accuracy, the same analysis was done excluding subjects having an MMSE < 27. In the 590 subjects having an MMSE > 27, the accuracy of the Berlin questionnaire remained unchanged, the sensitivity being 76.3%, specificity 38.9%, positive predictive value 62.6% and negative predictive value 55.1%.

Table 2 Predictive parameters for the Berlin questionnaire to identify an AHI > 15 in the total sample and in males and females.

Total population Women Men

Sens (%)

Spe (%)

PPV (%)

NPV (%)

Odds ratio

ROC curve

TP (%)

FP (%)

TN (%)

FN (%)

76.69 67.36 86.93

39.34 44.62 27.91

63.17 55.79 71.16

55.44 56.85 51.06

1.62 1.53 1.61

0.60 0.61 0.62

60.7 55.4 72.1

23.3 32.6 13.1

36.8 44.2 28.8

44.6 43.2 48.9

Sensitivity (Sens), specificity (Spe), positive (PPV), negative (NPV) predictive value, area under the ROC curve, true positive (TP), false positive (FP), true negative (TN) and false negative (FN).

E. Sforza et al. / Sleep Medicine 12 (2011) 142–146 Table 3 Receiver–operator characteristic of potential Berlin questionnaire prediction of OSA according to severity.

AHI > 15 Berlin first category Berlin second category Berlin third category AHI > 30 Berlin first category Berlin second category Berlin third category

ROC area

Odds ratio

SD

95% CI

p

0.6112 0.5053

2.4761 1.1071

0.4058 0.2739

1.79–3.41 0.68–1.79

0.000 0.681

0.5639

1.6990

0.2793

1.23–2.34

0.001

0.6220 0.5088

2.7234 0.7420

0.5616 0.2276

1.82–4.08 0.41–1.35

0.000 0.331

0.5635

1.5130

0.2931

1.03–2.21

0.03

When the gender effect was considered (Table 2), the Berlin questionnaire’s ability to detect OSA was better for men than for women. To assess the relative significance of the clinical and anthropometric variables associated with sleep-disordered breathing, we used correlation and multiple regression analyses. At correlation analysis the AHI was found to be correlated with BMI (r = 0.23, p = 0001), neck (r = 0.37, p = 0.0001) and waist (r = 0.16, p = 0.001) circumferences and ESS (0.11, p = 0.001). The logistic regression analysis showed that a model including neck circumference (r = 0.276, p = 0.004), ESS (r = 0.086, p = 0.03) and hypertension (r = 0.09, p = 0.02) explained the 3% in AHI variance. 5. Discussion Previous studies have underlined that OSA is a highly prevalent disorder in the elderly, carrying a high risk of cardiovascular morbidity and mortality. This study was the first attempt to assess the prevalence of individuals at high risk of having OSA in a community of elderly people using a validated questionnaire which has already been shown to have a very high sensitivity and specificity. The first finding of our study was that, in line with recent data [25,26], the Berlin questionnaire demonstrated only a moderate level of accuracy, its sensitivity being 76.7% but its specificity 39.3%. Among categories defining a high OSA risk, sleepiness was less likely to be the determining factor for the high risk classification, snoring criteria alone showing a better sensitivity (63.4%) and specificity (58.8%). Due to low specificity and high positive and negative values, the Berlin questionnaire alone is not an accurate instrument for identifying elderly subjects with OSA in a general healthy population. The Berlin questionnaire, however, appears to be more powerful than clinical examination to identify high OSA risk (4.3% of the AHI variance vs. 3% variance), suggesting that it could be used as a pre-screening tool for sleep study in a high risk older population. The Berlin questionnaire is a standardized, self administered enquiry developed for assessing subjects at high risk for OSA. It is inexpensive, easy to administer and has acceptable test–retest reliability [14–16]. The predictive performances of the Berlin questionnaire vary according to the population in which it is used. In primary care patients the sensitivity and specificity were 86% and 77% at a cutoff point of AHI > 5, and 54% and 97% at a cutoff of AHI > 15 [14]. In patients referred to a sleep laboratory, the Berlin questionnaire showed a very low predictive value. The sensitivity and specificity were 68% and 49% at an AHI > 5, 62% and 43% at an AHI > 10, and 57% and 43% at a respiratory index >15 [16]. In spite of its widespread use, there are no studies on the validity of the Berlin questionnaire in the elderly. Our study found that the overall prevalence of individuals at high risk for OSA as assessed by the Berlin questionnaire was 31%, a prevalence similar to those reported by previous epidemiological studies [1,2,5].

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Nevertheless, in our elderly group the Berlin questionnaire had a sensitivity of 76.7%, a specificity of 39.3%, a positive prediction of 63.2%, and a negative prediction of 55.4%, stressing the reduced accuracy to discriminate elderly with and without OSA. The lack of accuracy was not related to a cognitive impairment since the majority of our population had an MMSE > 27. Interestingly, among the three categories we found that the presence of snoring alone identifies about 60% of OSA cases, BMI, history of hypertension and especially sleepiness as being less accurate. One possible explanation is that older subjects may have a different symptom presentation resulting in inaccurate reporting of OSA by a symptom-based questionnaire. Sleepiness and quality of life are not dependent on the severity of OSA [27], and the typical symptoms, i.e., snoring, apnea, sleepiness and hypertension, if they are sensitive enough (92–94%) to exclude the disease in one-third of middle-aged patients, have lower specificity (28–51%) [28,29]. When we consider the role of hypertension 87% of our sample reported hypertension at the third item of the Berlin questionnaire, explaining the lower accuracy of this symptom to discriminate OSA. These results suggest that either current measures to define OSA are not specific enough to detect the consequences of sleep disorders in the elderly or that the clinical profile is different from that reported in a middle-aged population [25,30]. When we examined the relative contribution of clinical and anthropometric variables on AHI, neck circumference was the most important factor explaining, with the ESS and hypertension, only 3% of the variance in the AHI. This finding confirms that, from a clinical standpoint, in the elderly any of the typical features characterizing OSA explain the occurrence of an AHI > 15. Alternatively, since a high number of healthy elderly have an AHI > 15 [31], it might be suggested that an AHI > 15 tends to increase with age but the clinical significance, the vascular consequences and mortality decrease with aging. In an earlier study examining the association of hypertension and OSA [32], the authors found a strong correlation in young subjects, whereas the association was not significant in the elderly. Similar data were obtained when the association between aging and mortality was considered, the correlation being not significant or even directly opposed [33–35]. Thus, we can speculate that aging in itself acts as a protective mechanism [36]. Some limitations of our study have to be considered. First, we used polygraphic recording without EEG monitoring, the latter providing more detailed estimates of sleep structure and respiratory pattern. Although it is possible that the use of at-home polygraphy led to a higher AHI as compared to polysomnography and does not allow correct estimation of sleep fragmentation, several studies have demonstrated the validity of ambulatory polygraphy in children, [37] middle-aged [38,39] and elderly patients [13], with sensitivity ranging from 70% to 98% and specificity from 68% to 97%. Second, participants were recruited from a crosssectional community-based population aged 65 years at the study entry without previous medical, heart, neurological and cardiovascular diseases. Therefore, the age at the study entry, the lack of very old subjects and the strict inclusion criteria may limit our evaluation to ‘‘very healthy’’ and ‘‘very young’’ elderly, and results cannot be generalized to the overall older population. In conclusion, in our study sample of a generally healthy elderly population, we were not able to demonstrate a satisfactory accuracy of the Berlin questionnaire as a screening tool to discriminate subjects with and without OSA. The weighing of hypertension in the Berlin questionnaire probably leads to lower symptom discrimination in a senior population. The questionnaire could be more accurate in this age group when the third item consists of obesity alone or in association with another clinical sign. Despite the low accuracy, its administration appears to be more reliable than clinical examination to provide a convenient and cost-effective

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