Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder and is associated with significant morbidity. We sought to present an updated systematic review of the literature on the accuracy of screening questionnaires for OSA against polysomnography (PSG) as the reference test. Using the main databases (including Medline, Cochrane Database of Systematic Reviews and Scopus) we used a combination of relevant keywords to filter studies published between January 2010 and April 2017. Population-based studies evaluating the accuracy of screening questionnaires for OSA against PSG were included in the review. Thirty-nine studies comprising 18 068 subjects were included. Four screening questionnaires for OSA had been validated in selected studies including the Berlin questionnaire (BQ), STOP-Bang Questionnaire (SBQ), STOP Questionnaire (SQ), and Epworth Sleepiness Scale (ESS). The sensitivity of SBQ in detecting mild (apnea-hypopnea index (AHI) ≥ 5 events/hour) and severe (AHI ≥ 30 events/hour) OSA was higher compared to other screening questionnaires (range from 81.08% to 97.55% and 69.2% to 98.7%, respectively). However, SQ had the highest sensitivity in predicting moderate OSA (AHI ≥ 15 events/hour; range = 41.3% to 100%). SQ and SBQ are reliable tools for screening OSA among sleep clinic patients. Although further validation studies on the screening abilities of these questionnaires on general populations are required.
Keywords: Obstructive Sleep Apnea, Surveys and Questionnaires, Validation, SensitivityObstructive sleep apnea (OSA) is the most common sleep breathing disorder and manifests as repeated apneas and hypopneas during sleep. 1-3 OSA increases the risk of hypertension, glucose intolerance, cardiovascular, and cerebrovascular disorders. 4-7 Untreated OSA is also associated with daytime sleepiness, cognitive dysfunction, and increased risk of automobile accidents. 8-10 Polysomnography (PSG) is the gold standard for the diagnosis of OSA, but it is an expensive and time-consuming and requires trained personnel. PSG is a noninvasive technique that involves overnight monitoring of several physiological variables including electroencephalography, eye movements, and muscle tone as well as respiratory effort, airflow, and oxygen saturation. 11 Therefore, different clinical models have been developed to evaluate patients at high risk for OSA. 12-14 Screening questionnaires are simple, low-cost tools that can be used to prioritize patients eligible for PSG.
OSA screening questionnaires (OSA-SQs) were evaluated in surgical patients in a systematic review by Abrishami et al. 15 In addition to being easy-to-use, the STOP and STOP-Bang questionnaires were found to have a higher methodological quality. Over the past few years, the accuracy of OSA-SQs has been an area of growing research interest and a number of studies have been published on the subject. This systematic review aimed to assess the accuracy of OSA-SQs including the Berlin questionnaire (BQ), STOP-Bang questionnaire (SBQ), STOP questionnaire (SQ), and Epworth Sleepiness Scale (ESS), based on an updated search of the literature.
We performed a literature search using Medline, Cochrane Database of Systematic Reviews, and Scopus for articles published between January 2010 and April 2017 using the following terms: OSA or OSAHS (obstructive sleep apnea hypopnea syndrome), hypopnea or hypopnoea, obstructive sleep apnea or sleep apnea syndrome and sensitivity, specificity, validity, or validation, sleep apnea questionnaires, and screening sleep apnea. The reference list of identified studies was also searched manually to detect eligible studies for inclusion. The flow diagram of study selection process is depicted in Figure 1 .
Flow diagram of study selection.
Two authors independently reviewed the titles and abstracts of the search results and disagreements were solved in group discussion. The studies had to meet the following criteria to be included: a) participant age > 18 years; b) the accuracy of the screening questionnaire had been assessed against various apnea-hypopnea indexes (AHI) or respiratory disturbance indexes (RDI) based on PSG as the gold standard; and c) studies were published in English. We also included studies if the validity of screening questionnaires was reported as a secondary outcome. Letters to the editor, review articles, case reports, and commentaries were excluded.
Two independent reviewers extracted the following information from each study that met the inclusion criteria: name of the first author, country and year of publication, study design, number of participants, age, gender, body mass index (BMI), neck circumference, validation tool (various types of PSG included), sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for each AHI or RDI cut-off point including, AHI or RDI of ≥ 5 events/hour (mild OSA), ≥ 15 events/hour (moderate OSA), and ≥ 30 events/hour (severe OSA).
Thirty-nine studies qualified for inclusion in the present review, 11,16-54 with sample sizes ranging from 30 to 4770. These studies were carried out in seven different geographic regions including, North America, 17,18,20,22,27,38,47,50,52 West Asia, 11,16,24,29,30,42,51,53 East Asia, 25,26,28,32,36,49,54 Europe, 19,31,37,39,43,45,46 South Asia, 40,48 North Africa, 21,44 and South America. 23,33-35 The results of our analysis of the relevant studies are presented below for each of the four OSA-SQs.
Overview of studies included looking at the accuracy of screening questionnaires for obstructive sleep apnea against polysomnography (PSG) as the reference test.
Study | No. of patients | Patient type | Age, years | Male, % | Body mass index, kg/m 2 | Validation tool |
---|---|---|---|---|---|---|
Ong et al. 2010 36 | 314 | Sleep clinic patients | 46.8 ± 15 | 70.5 | 27.9 ± 6 | Lab PSG |
Sagaspe et al. 2010 43 | 123 | Sleep clinic patients | 47 ± 13.2 | 67.5 | - | Lab PSG |
Gantner et al. 2010 25 | 143 | Patients with high cardiovascular risk | 62.2 ± 7.6 | 58 | 26.6 ± 3.7 | Level II PSG |
Silva et al. 2011 47 | 4770 | General population | 62.4 ± 10.3 | 51.5 | - | Level II PSG |
Saleh et al. 2011 44 | 100 | Sleep clinic patients | 45.63 ± 9.67 | 51 | 36.34 ± 10.70 | Lab PSG |
Srijithesh et al. 2011 48 | 121 | Acute stroke patients | 56.5 | - | Lab PSG | |
Sforza et al. 2011 46 | 643 | General population | 65.6 ± 0.03 | 40.90 | 25.3 ± 0.2 | Level III PSG |
Enciso et al. 2011 22 | 84 | Dental clinic patients | 54.93 ± 12.63 | 77.38 | 26.60 ± 3.74 | Two-night ambulatory somnography |
Thurtell et al. 2011 50 | 30 | Patients with idiopathic intracranial hypertension | 32 ± 6.3 | 20 | 24.4 ± 4.1 | Lab PSG |
Martinez et al. 2012 34 | 57 | Patients with angina complaints | 54 ± 6.9 | 46 | 23 ± 11 | Level III PSG |
Hesselbacher et al. 2012 27 | 1897 | Sleep clinic patients | 53.84 ± 15 | 57.56 | 35.42 ± 5 | Lab PSG |
El-Seyed et al. 2012 21 | 234 | Sleep clinic patients | 50.38 ± 11.29 | 58.5 | 37.77 ± 9.54 | Lab PSG |
Firat et al. 2012 24 | 85 | Bus drivers | - | 100 | 29.1 ± 3.8 | Daytime PSG |
Amra et al. 2013 11 | 157 | Sleep clinic patients | 52.3 ± 13.6 | 55.4 | 31.5 ± 6 | Lab PSG |
Bouloukaki et al. 2013 19 | 189 | Clinic outpatients | 47 ± 13 | 61.9 | 35.0 ± 25.1 | Lab PSG |
Kang et al. 2013 28 | 1305 | General population | 52.78 ± 16.55 | 47.7 | 22.81 ± 4.86 | Lab PSG |
Best et al. 2013 17 | 82 | Patients with treatment resistant depression | 47.1 ± 9 | 26.83 | 33.34 ± 8.6 | Level II PSG |
Yunus et al. 2013 54 | 150 | Clinic outpatients | 44.7 ± 11.5 | 64 | 36.3 ± 11.2 | Lab PSG |
Boynton et al. 2013 20 | 219 | Sleep clinic patients | 46.3 ± 13.9 | 44.8 | 33.43 ± 8.76 | Lab PSG |
Pereira et al. 2013 38 | 128 | Sleep clinic patients | 50 ± 12.3 | 65.62 | 31 ± 6.6 | Lab PSG |
Scarlata et al. 2013 45 | 254 | Clinic outpatients | 65.8 ± 12.1 | 68.6 | 38.5 ± 7.7 | Lab PSG |
Vana et al. 2013 52 | 47 | Sleep clinic patients | 46.4 ± 13.2 | 34 | 36.3 ± 9.2 | Lab PSG |
Pataka et al. 2014 37 | 1853 | Sleep clinic patients | 52 ± 14 | 74.42 | 32.8 ± 7 | Lab PSG |
Karakoc et al. 2014 29 | 217 | Surgical population | 42.5 ± 10.7 | 88 | 28.10 ± 4.1 | Lab PSG |
Margallo et al. 2014 33 | 422 | Patients with resistant hypertension | 62.4 ± 9.9 | 31 | 31.2 ± 5.7 | Lab PSG |
Ha et al. 2014 26 | 141 | Sleep clinic patients | 44.82 ± 12 | 81.6 | 25.33 ± 5 | Lab PSG |
Ulasli et al. 2014 51 | 1450 | Sleep clinic patients | 50 ± 9.83 | 62.96 | 31.25 ± 9.09 | Lab PSG |
Kim et al. 2015 32 | 592 | Sleep clinic patients | 47.8 ± 12.7 | 83.5 | 24.7 ± 3.5 | Lab PSG |
Alhouqani et al. 2015 16 | 193 | Sleep clinic patients | 42.87 ± 11.83 | 77.7 | 34.90 ± 8.60 | Lab PSG |
Sadeghniiat-Haghighi et al. 2015 42 | 603 | Sleep clinic patients | 45.8 ± 12.7 | 74.8 | 29.18 ± 5.9 | Lab PSG |
Yuceege et al. 2015 53 | 433 | Sleep clinic patients | 47.5 ± 10.5 | 65.82 | 31.1 ± 5.6 | Lab PSG |
Nunes et al. 2015 35 | 40 | Coronary artery bypass grafting patients | 56 ± 7 | 73 | 30 ± 4 | Lab PSG |
Nunes et al. 2015 35 | 41 | Abdominal surgery patients | 56 ± 8 | 68 | 29 ± 5 | Lab PSG |
Faria et al. 2015 23 | 91 | Patients with chronic obstructive pulmonary disease | 69.4 ± 9.6 | 63.7 | 23.6 ± 3.9 | Lab PSG |
Popevic et al. 2016 39 | 100 | Commercial drivers | 43.4 ± 10.7 | 100 | 29.0 ± 5.7 | Lab PSG |
Khaledi-Paveh et al. 2016 30 | 100 | Sleep clinic patients | 45.66 ± 11.83 | 60 | 29.5 ± 6.1 | Lab PSG |
Kicinski et al. 2016 31 | 123 | Sleep clinic patients | 54.6 ± 11.1 | 66.40 | 33.5 ± 5.2 | Lab PSG |
Tan et al. 2016 49 | 242 | General population | 48.3 ± 14 | 50.4 | 26.2 ± 5 | Level 3 PSG |
Bhat et al. 2016 18 | 85 | Sleep clinic patients | 50.5 ± 12.6 | 70.6 | 32 ± 1.55 | Lab PSG/Level III PSG |
Prasad et al. 2017 40 | 210 | Sleep clinic patients | 46.5 ± 13.7 | 72.9 | 31.9 ± 7.4 | Lab PSG |
Table 2 shows the BQ data for the sensitivity, specificity, PPV, and NPV for one or more AHI cut-off points as reported in the selected studies. The BQ highest sensitivity (97.3%) and NPV (95.4%) for the detection of OSA was found at AHI cutoffs ≥ 30 events/hour. However, the BQ had the highest detection specificity for moderate OSA (91.7%). Our analysis indicates a PPV ranging from 11.5% to 91% at AHI ≥ 5 events/hour.
Study | AHI ≥ 5 | AHI ≥ 15 | AHI ≥ 30 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Sensitivity % | Specificity % | PPV % | NPV % | Sensitivity % | Specificity % | PPV % | NPV % | Sensitivity % | Specificity % | PPV % | NPV % | |
Berlin | ||||||||||||
Sagaspe et al. 2010 43 | 72 | 73 | 63 | 76 | 61 | 43 | 71 | 53 | 16 | |||
Gantner et al. 2010 25 | - | - | - | - | 89 | 35 | 76 | 58 | 92 | 26 | 49 | 81 |
Saleh et al. 2011 44 | 97 | 90 | 96 | 93 | - | - | - | - | - | - | - | - |
Srijithesh et al. 2011 48 | 68.2 | 58.8 | 68.2 | 58.8 | - | - | - | - | - | - | - | - |
Sforza et al. 2011 46 | - | - | - | - | 76.69 | 39.34 | 63.17 | 55.44 | - | - | - | - |
Enciso et al. 2011 22 | - | - | - | - | 67.9 | 54.8 | 72 | 50 | - | - | - | - |
Thurtell et al. 2011 50 | 83.3 | 58.3 | 75 | 70 | - | - | - | - | - | - | - | - |
Martinez et al. 2012 34 | - | - | - | - | 72 | 50 | 53 | 70 | - | - | - | - |
El-Seyed et al. 2012 21 | 95.07 | 25 | 92.79 | 33.33 | 95.48 | 7.41 | 87.11 | 20 | 97.3 | 10.71 | 74.23 | 60 |
Firat et al. 2012 24 | - | - | - | - | 45.6 | 84.6 | 77.1 | 56.8 | - | - | - | - |
Amra et al. 2013 11 | 84.0 | 61.5 | 96.0 | 25.8 | 87.9 | 36.7 | 75.3 | 58.0 | 87.8 | 26.5 | 51.5 | 70.9 |
Bouloukaki et al. 2013 19 | 76 | 40 | 94 | 12 | 84 | 61 | 86 | 52 | 79 | 39 | 80 | 36 |
Kang et al. 2013 28 | 69 | 83 | - | - | 89 | 63 | - | - | - | - | - | - |
Best et al. 2013 17 | 25.0 | 85.4 | 56.5 | 60.0 | 24.5 | 91.7 | 35.5 | 93.3 | - | - | - | - |
Yunus et al. 2013 54 | 92 | 17 | 97 | 29 | - | - | - | - | - | - | - | - |
Pereira et al. 2013 38 | 86 | 25 | 91.7 | 15.8 | 91 | 28 | 73.4 | 57.9 | 89 | 18 | 45.9 | 68.4 |
Pataka et al. 2014 37 | 71.8 | 17.2 | 11.5 | 80.2 | 78 | 18 | 16.5 | 80.4 | 90 | 28.5 | 56 | 74 |
Karakoc et al. 2014 29 | 83.4 | 22.2 | 76.4 | 30.8 | 89.3 | 22.6 | 42.1 | 76.9 | - | - | - | - |
Margallo et al. 2014 33 | 68 | 46 | 85 | 24 | 69 | 40 | 58 | 50 | 76 | 40 | 39 | 77 |
Ha et al. 2014 26 | 75 | 30.29 | 83.17 | 28.21 | 75 | 32.14 | 62.38 | 46.15 | 80.39 | 32.58 | 40.59 | 74.36 |
Ulasli et al. 2014 51 | 73.1 | 44.5 | - | - | 76.4 | 39.5 | - | - | 80.3 | 35.3 | - | - |
Kim et al. 2015 32 | 71.5 | 32.0 | 84.3 | 18.0 | 75.5 | 35.4 | 62.1 | 50.6 | - | - | - | - |
Yuceege et al. 2015 53 | - | - | - | - | 84.2 | 31.7 | 48.7 | 63.4 | - | - | - | - |
Nunes et al. 2015 35 | - | - | - | - | 67 | 26 | 50 | 42 | - | - | - | - |
Nunes et al. 2015 35 | - | - | - | - | 82 | 62 | 61 | 83 | - | - | - | - |
Faria et al. 2015 23 | 40 | 68.4 | 25 | 81.2 | - | - | - | - | - | - | - | - |
Popevic et al. 2016 39 | 50.9 | 86.0 | 82.9 | 56.9 | 78.3 | 77.9 | 51.4 | 92.3 | 75 | 70.4 | 25.7 | 95.4 |
Khaledi-Paveh et al. 2016 30 | 77.3 | 23.1 | 68 | 22 | 58.5 | 45.7 | - | - | 30.8 | 80 | - | - |
Kicinski et al. 2016 31 | - | - | - | - | 93.10 | 16.20 | 1.11 | 42 | - | - | - | - |
Prasad et al. 2017 40 | 33.5 | 39.1 | 83 | 40 | 87.5 | 37.8 | 72.1 | 62.2 | 89.4 | 32.1 | 56.4 | 75.6 |
STOP-Bang | ||||||||||||
Ong et al. 2010 36 | 84.7 | 52.6 | 84.4 | 53.2 | 91.1 | 40.4 | 60.8 | 81.3 | 95.4 | 35.0 | 43.5 | 93.5 |
Silva et al. 2011 47 | - | - | - | - | 87 | 43.3 | - | - | 70.4 | 59.5 | ||
El-Seyed et al. 2012 21 | 97.55 | 26.32 | 93.43 | 50 | 97.74 | 3.7 | 86.93 | 20 | 98.65 | 5.36 | 73.37 | 60 |
Firat et al. 2012 24 | - | - | - | - | 87 | 48.7 | 66.6 | 76 | - | - | - | - |
Boynton et al. 2013 20 | 82.2 | 48.0 | 84.2 | 44.4 | 93.2 | 40.5 | 58.2 | 87.0 | 96.8 | 33.1 | 36.4 | 96.3 |
Pereira et al. 2013 38 | 90 | 42 | 93.7 | 29.4 | 93 | 28 | 73.9 | 64.7 | 96 | 21 | 48.6 | 88.2 |
Pataka et al. 2014 37 | 90 | 4.9 | 12.2 | 76.8 | 94 | 5.5 | 17 | 84 | 98.7 | 9.9 | 52.7 | 88.4 |
Ha et al. 2014 26 | 81.08 | 57.14 | 88.24 | 43.24 | 85.71 | 45.45 | 70.59 | 67.57 | 86.27 | 34.09 | 43.14 | 81.08 |
Alhouqani et al. 2015 16 | 90.24 | 31.03 | 88.10 | 36.00 | 96.75 | 30.00 | 70.83 | 84.00 | 97.70 | 21.70 | 50.60 | 92.00 |
Kim et al. 2015 32 | 97.0 | 18.6 | 85.9 | 54.6 | 98.0 | 10.6 | 60.6 | 78.8 | - | - | - | - |
Sadeghniiat-Haghighi et al. 2015 42 | 91.6 | 45.2 | 78.2 | 71.6 | 97.1 | 35.2 | 56.9 | 93.3 | 98 | 29.4 | 41.8 | 96.6 |
Tan et al. 2016 49 | - | - | - | - | 66.2 | 74.7 | 50.6 | 85.0 | 69.2 | 67.1 | 20.2 | 94.8 |
Prasad et al. 2017 40 | 89 | 43.5 | 84.9 | 52.6 | 93.4 | 39.2 | 73.8 | 76.3 | 96.2 | 32.1 | 58.1 | 89.5 |
STOP | ||||||||||||
Silva et al. 2011 47 | - | - | - | - | 62 | 56.3 | - | - | 68.8 | 59.5 | - | - |
El-Seyed et al. 2012 21 | 91.67 | 25 | 92.57 | 22.73 | 94.35 | 25.93 | 89.3 | 41.18 | 95.95 | 19.64 | 72.55 | 64.71 |
Firat et al. 2012 24 | - | - | - | - | 41.3 | 92.3 | 86.4 | 57.1 | - | - | - | - |
Boynton et al. 2013 20 | 74.6 | 34.0 | 79.2 | 28.3 | 80.6 | 34.5 | 52.2 | 66.7 | 83.9 | 31.8 | 32.7 | 83.3 |
Pataka et al. 2014 37 | 91.7 | 6.4 | 12.8 | 84 | 92.7 | 6.6 | 17.3 | 72 | 97 | 11 | 52.3 | 78.4 |
Ha et al. 2014 26 | 74.77 | 50.00 | 85.57 | 33.33 | 76.19 | 40.00 | 65.98 | 52.38 | 80.39 | 36.36 | 42.27 | 76.19 |
Sadeghniiat-Haghighi et al. 2015 42 | 86.3 | 46.5 | 81.9 | 54.8 | 91.1 | 37.1 | 61.5 | 79 | 94.1 | 30.7 | 40.2 | 91.1 |
Nunes et al. 2015 35 | - | - | - | - | 100 | 5 | 54 | 100 | - | - | - | - |
Nunes et al. 2015 35 | - | - | - | - | 88 | 13 | 42 | 60 | - | - | - | - |
Prasad et al. 2017 40 | 87.8 | 43.5 | 84.7 | 50 | 91.9 | 39.2 | 73.5 | 72.5 | 95.2 | 33 | 58.2 | 87.5 |
Epworth Sleepiness Scale | ||||||||||||
Silva et al. 2011 47 | - | - | - | - | 39 | 71.4 | 46.1 | 70.4 | - | - | ||
Hesselbacher et al. 2012 27 | - | - | - | - | 54 | 57 | 64 | 47 | - | - | - | - |
El-Seyed et al. 2012 21 | 72.55 | 75 | 96.73 | 21.13 | 75.71 | 48.15 | 90.54 | 23.23 | 79.73 | 46.43 | 79.73 | 46.43 |
Scarlata et al. 2013 45 | - | - | - | - | - | - | - | - | - | - | - | - |
Vana et al. 2013 52 | 31.3 | 53.3 | 58.8 | 26.7 | - | - | - | - | - | - | - | - |
Pataka et al. 2014 37 | 33.3 | 50.6 | 9.1 | 83.6 | 44.5 | 52.1 | 17 | 81 | 57 | 62.4 | 59 | 60 |
Ulasli et al. 2014 51 | 46.9 | 60 | - | - | 49.9 | 61.1 | - | - | 52.8 | 58.2 | - | - |
Faria et al. 2015 23 | 60 | 73.7 | 37.5 | 87.5 | - | - | - | - | - | - | - | - |
Kicinski et al. 2016 31 | - | - | - | - | 53.20 | 58.80 | 1.90 | 79 | - | - | - | - |
Bhat et al. 2016 18 | - | - | - | - | 46.2 | 65.2 | 75 | 34.9 | - | - | - | - |
Prasad et al. 2017 40 | 55.5 | 67.4 | 85.9 | 29.8 | 59.6 | 66.2 | 76.4 | 47.1 | 66.4 | 65.1 | 65.1 | 66.4 |
AHI: apnea-hypopnea index; PPV: positive predictive value; NPV: negative predictive value.
The SBQ includes four subjective (STOP: Snoring, tiredness, observed apnea, and high blood pressure) and four demographics items (BANG: BMI, 56 Age, Neck circumference, Gender). A score of 5–8 is categorized as high risk for OSA. 57
For the SBQ, we included 13 studies with a total 9584 subjects and sample sizes ranging from 85 to 4770. The studies mostly included sleep clinic patients with an age range of 42.8 to 62.4 years old [ Table 1 ]. Overnight laboratory PSG was used as the validation tool in 10 studies. 24,47,49 The highest sensitivity and NPV were reported at AHI thresholds of ≥ 30 events/hour. The PPV value ranged between 12.2% and 93.7% at AHI cutoffs ≥ 5 events/hour. The SBQ showed the highest specificity (74.7%) in detecting moderate OSA [ Table 2 ].
The SQ is a concise and easy-to-use screening tool for OSA with high sensitivity. SQ can classify patients as being at high risk of having OSA if they answer yes to two or more questions. 57 SQ was evaluated in nine studies (8196 subjects) of which six studies were carried out on sleep clinic patients and three on the general, community population, 47 surgical patients, 35 and bus drivers. 24 The number of subjects in the studies varied from 40 to 4770 and the mean age was 44.8–62.4 years. Two studies used type II and daytime PSG for validation, 24,47 while the others used overnight laboratory PSG. Our review indicates that the SQ had the highest prediction sensitivity (100%), specificity (92.3%), and NPV (100%) in the case of moderate OSA, while in the case of mild OSA the PPV ranged from 12.8% to 92.5% [ Table 2 ].
The ESS is an eight-item questionnaire to measure daytime sleepiness; it uses a four-point Likert response format (0–3), and the score ranges from 0 to 24. An ESS score ≥ 11 indicates excessive daytime sleepiness and high risk for OSA. 58 Eleven of the 39 studies investigated the accuracy of ESS with a total of 11 014 subjects. The sample size in the 11 studies ranged from 47 to 4770 with an average age between 46.4 and 69.4 years. Eight of the 11 studies were conducted on sleep clinic patients, while the remaining three studies were carried out on respiratory patients, 23 the general population, 47 and clinic outpatients. 45 The laboratory PSG was used by the majority of the reviewed studies [ Table 1 ]. The highest ESS sensitivity was observed at AHI ≥ 30 events/hour and ranged between 46.1% and 79.73%. However, the highest values for specificity (75%), NPV (87.5%), and PPV (96.7%) were found in mild OSA with a decreasing trend from mild to severe OSA [ Table 2 ].
Sleep apnea is a common and potentially serious disorder in which breathing stops and repeatedly restarts during sleep. Hundreds of such breathing interruptions can occur over the course of a single night with each interruption lasting 10 to 20 seconds. Following each of the long apneic periods, the individual is jolted out of the normal sleep phase - the sleep rhythm is disrupted and the individual suffers from fatigue and daytime sleepiness. Other indicative signs of serious sleep apnea include long apneic periods (> 15 seconds), loud snoring, choking or gasping during sleep, irritability, headache, depression, and nightmares. If untreated, sleep apnea can lead to serious disorders including obesity, diabetes, hypertension, and stroke. There are three main types of sleep apnea depending on their cause. The most common variety is OSA, which results from upper airway obstruction because of hypotonia and collapse of the posterior pharyngeal muscles. OSA is characterized by cyclic loud snoring, which is a common problem in obese individuals and patients with endocrine disorders such as hypothyroidism and acromegaly. A common cause of OSA in children is hypertrophy of the tonsils and/or the adenoids. Central sleep apnea results from the reduced central respiratory drive. Complex sleep apnea is a combination of both obstructive and central apneas. 59
In light of the profound impact of OSA on the health and quality of life, 5,18,40 it is essential that patients are adequately screened to receive the necessary medical care. It is estimated that over 80% of people with moderate to severe OSA remain undiagnosed. 60 Thus, a screening tool is necessary to stratify patients based on their clinical symptoms and anthropometric risk factors.
Some easy-to-use questionnaires have been developed as low-cost alternatives to PSG for detecting OSA. In this review, we assessed the accuracy of four self-reported OSA-SQs against PSG as the reference test. The SBQ had the highest sensitivity for the prediction of mild and severe OSA (97.55% and 98.7%, respectively). However, the BQ showed the highest specificity for the detection of mild and severe OSA (90% and 80%, respectively). Compared to other questionnaires, the SQ had the highest sensitivity (100%) and specificity (92.3%) for predicting moderate OSA. The validity of our results for the general population may be questioned based on the fact that most of the subjects in the studies we reviewed were sleep clinic patients where the prevalence of OSA is relatively high. In addition, there is no standard definition of OSA unifying the various validation studies. Features of an appropriate screening questionnaire vary according to the population being surveyed. For example, cultural differences in urban and rural populations require the questionnaire is modified according to those being surveyed. However, it must be noted that it was not our objective of this review. Diagnosis of true positive OSA patients in a clinical setting using a questionnaire with high sensitivity minimizes negative health consequences and avoids unnecessary and costly diagnostic tests. PSG, the gold standard for OSA diagnosis, is an expensive and time-demanding procedure. Therefore, it is necessary to decrease the number of false-positive subjects in the general population using a screening tool with high specificity. An effective screening tool must also have a high sensitivity to minimize the number of false negatives.
There was no standard definition for OSA in various studies that investigated the validity of OSA screening questionnaires against PSG. A recent meta-analysis indicated that the BQ has a moderate sensitivity and specificity in the general population for detecting hypopnea defined as a 3% oxygen desaturation. However, its sensitivity decreased when the hypopnea definition of 4% oxygen desaturation was applied. 39 Based on these observations it is clear that the definition of OSA significantly affects the accuracy of validation studies.
Therefore, it is necessary to test the validity of various OSA-SQs in the general population against the reference standard PSG. Because sleep clinic patients constituted the majority of the subjects in the reviewed studies, it is not possible to extend our conclusions to the general population.
SBQ and SQ are appropriate screening tools to determine OSA in sleep clinic patients. Further validation studies designed specifically for the general population are necessary.
The authors declared no conflicts of interest. No funding was received for this study.