Sleep Breath DOI 10.1007/s11325-015-1150-x
ORIGINAL ARTICLE
Evaluation of the Arabic version of STOP-Bang questionnaire as a screening tool for obstructive sleep apnea Shaikha Alhouqani & Mariam Al Manhali & Awad Al Essa & Mohammed Al-Houqani
Received: 10 December 2014 / Accepted: 25 February 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract Purpose Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that is underdiagnosed. OSA is usually diagnosed by polysomnography (PSG) and, if untreated, could lead to life-threatening complications. Many screening questionnaires have been developed to screen and identify patients at high risk for OSA. This study aimed to evaluate and validate the Arabic version of Stop-Bang questionnaire as a screening tool for patients with OSA symptoms referred to a sleep clinic. Methods All referred Arabic-speaking adult patients presenting to a Sleep Disorders Specialized Clinic in Al Ain for PSG were requested to complete an Arabic STOP-Bang questionnaire. A score of 3 or more out of a possible 8 was taken to indicate high risk for presence of OSA. These scores were then evaluated versus results from the overnight, monitored PSG. Apnea/hypopnea index (AHI) of ≥5/h was considered for diagnosis of OSA. Results One hundred ninety-three sleep clinic patients were enrolled in this study. PSG was positive (AHI ≥5) in 85 % of the studied population. STOP-Bang questionnaire was S. Alhouqani Tawam Hospital, Abu Dhabi, United Arab Emirates e-mail: [email protected] M. Al Manhali Ambulatory Health Services, Abu Dhabi, United Arab Emirates e-mail: [email protected] A. Al Essa Nursing Research, Department of Internal Medicine, College of Medicine and Health Sciences, UAE University, Abu Dhabi, United Arab Emirates e-mail: [email protected] M. Al-Houqani (*) College of Medicine and Health Sciences, UAE University, P.O.Box 17666, Al Ain, Abu Dhabi, United Arab Emirates e-mail: [email protected]
positive (≥3) in 87 % of the population. Reproducibility of STOP-Bang questionnaire was tested, and the intraclass correlation coefficient of the total score of STOP-Bang questionnaire was 0.931 (95 % CI 0.834–0.972). The sensitivities of the STOP-Bang screening tool for an AHI of ≥5, ≥15, and ≥30 were 90, 96.75, and 99.70 %, respectively, with negative predictive values (NPVs) of 36, 84, and 92 %, respectively. ROC curve was 0.77. Conclusion The Arabic version of STOP-Bang questionnaire is an easy-to-use tool that can be implemented as a reliable, quick screening tool for OSA in patients referred to sleep clinic. It demonstrated high sensitivity and NPVespecially for patients with moderate to severe OSA. We believe that this tool will help physicians to earlier identify cases at risk of OSA. Keywords STOP-Bang . Obstructive sleep apnea . Screenings . Validation Abbreviations OSA Obstructive sleep apnea PSG Polysomnography SB Stop-Bang ESS Epworth sleepiness scale AHI Apneas/hypopnea index NPV Negative predictive values PPV Positive predictive values CI Confidence interval ROC Receiver operating characteristic
Introduction Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that involves a decrease or complete halt in airflow despite an ongoing effort to breathe; leading to short- and
Sleep Breath
long-term complications if left undiagnosed. It leads to partial reductions (hypopneas) and complete pauses (apneas) in breathing that last at least 10 s during sleep, resulting in a fragmented quality of sleep that often produces an excessive level of daytime sleepiness. Most people with OSA snore loudly and frequently, with periods of silence when airflow is reduced or blocked. They then make choking, snorting, or gasping sounds when their airway reopens [1]. One of the major OSA risk factors is obesity. In the emirates of Abu Dhabi, 67 % of adults are either overweight or obese, and 57 % have been identified as having central obesity [2]. The prevalence of OSA among the general population is estimated between 2 and 26 % [3, 4]]. In the United Arab Emirates, the prevalence of OSA symptoms among Dubai citizens was found to be around 21 % [6]. However, due to a limited number of sleep laboratories in the United Arab Emirates, OSA remains underdiagnosed. Previous investigators have confirmed that untreated OSA is associated with life-threatening complications such as resistant hypertension and cardiovascular events and could affect overall quality of life [7–9]. The gold standard test for OSA is polysomnography (PSG), which is an expensive, not widely available test in the United Arab Emirates, inconvenient to patients as they need to stay overnight in the sleep laboratory. Many screening questionnaires have been developed to screen and identify patients at high risk for OSA. Examples include Stop-Bang (SB), Epworth sleepiness scale (ESS), Berlin Questionnaire, and modified neck circumference [10–12]. Most of these screening tools have been evaluated and show acceptable sensitivity in primary care settings [13]. The Stop-Bang questionnaire is an easy to administer questionnaire that was initially validated as a screening tool for OSA in a surgical population [5]. It consists of eight independent questions with a score of 3 or more indicating high-risk patients for OSA. Vana and colleagues [14] concluded in their study that STOP-Bang could identify more patients with OSA than ESS in a sleep clinic setting with a sensitivity of 94.7 % compared to a sensitivity of 26.3 % in ESS. Another study by Pecotic and others showed that STOP-Bang had better probability to correctly predict high-risk patients for OSA compared to ESS [15]. To our knowledge, however, there is no study examining the utility and diagnostic accuracy of the Arabic version of the STOPBang questionnaire. This study aims to evaluate and validate the Arabic version of Stop-Bang questionnaire as a screening tool for patients with OSA symptoms referred to a sleep clinic.
Methods Setting This study was performed at the Sleep Disorders Specialized Clinic, Al Ain, United Arab Emirates, during the period from
June 2012 to April 2013. The study protocol (no. 13/30) was obtained and approved by the Human Research Ethics Committee of Al Ain Medical District. On their first visit to the clinic, all participants gave informed consent to participate in the study. Translation of STOP-Bang questionnaire The STOP-Bang questionnaires were translated into the Arabic language by two clinicians. The questionnaires were then administered to a small group of 20 patients seen at the Sleep Disorders Specialized Clinic to ensure clarity and face validity. The questionnaires were back translated from Arabic into English by a bilingual professional translator for comparison with the original text. The sentence structure and presentation of the STOP-Bang questionnaires were similar to those of the English version. Because STOP-Bang questions reflected different dimensions of OSA morbidity, internal consistency checking was not applicable, but we performed test–retest reliability of the total score in 20 subjects who completed STOP-Bang on two occasions, 1 week apart. STOP-Bang questionnaire All referred patients presenting to the sleep clinic were requested to complete the questionnaire. We used the eightpoint STOP-Bang format. This format consists of two parts; the first part, “STOP,” includes four questions for patient to answer about snoring, tiredness, obstruction or observed apnea, and blood pressure. Each question requires a “yes” or “no” answer and each “yes” accounts for one point. The second part, “BANG,” was completed by a health care professional (respiratory technician), and questions were about body mass index (if more than 35), age (if more than 50), neck circumference (if more than 40 cm), and gender (if male). The questions were in “yes/no” answer format, and each “yes” accounted for one point. All these parameters were collected during patient’s first visit to the clinic prior to the sleep study.
Subjects/population We reviewed 425 cases that were referred to the Sleep Disorders Specialized Clinic, and from those, a total of 193 were included. Inclusion criteria were as follows: all adults aged 18 years and more, Arabic speaking, not known to have OSA, completed STOP-Bang questionnaire in Arabic, and had PSG. Patients less than 18 years old were excluded because some of the questionnaire’s elements are not applicable to the pediatric population. Demographic data and vital signs (height, weight, and neck circumference) were collected from patients’ files together with the filled questionnaire.
Sleep Breath
Polysomnography The nocturnal PSG consisted of continuous polysomnographic (Compumedics Grael and Somte PSG, Australia) recordings of a standard electroencephalographic montage consisting of six electroencephalograms (F3-M2, F4-M1, C3–M2, C4–M1, O1–M2, O2–M1), right and left electroocculogram, submental and bilateral tibial electromyogram, and electrocardiogram using surface electrodes. Respiration was monitored with oronasal thermocouples and with nasal pressure transducers. Thoracoabdominal movements were monitored using respiratory inductance plethysmography (RIP). Continuous pulse oximetry was also monitored. Sleep stage scoring was performed in 30-s epochs by certified registered polysomnographic technologists according to American Association of Sleep Medicine (AASM) criteria. Apnea was defined as cessation of airflow for more than 10 s. Hypopneas were scored as at least 30 % decrease in airflow with 3 % oxygen desaturation and/or arousal. The apnea/ hypopnea index was defined as the total number of apneas and hypopneas per hour of sleep time. An AHI of ≥5 was considered for diagnosis of OSA. Subjects with sleep apnea were classified into three subgroups according to their AHI: mild subgroup (subjects with AHI 35, n (%) Neck circumference (cm) AHI Total sleep time % Sleep efficiency Respiratory disturbance index % Lowest SpO2
42.87±11.838 150 (77.7) 34.90±8.602 67 (34.7) 39.54±3.463 34.87±31.276 311.90±79.634 81.43±14.917 37.83±30.156 78.10±12.737
BMI body mass index, AHI apnea/hypopnea index
of the studied population. STOP-Bang questionnaire was positive (≥3) in 87 % of the population. Reliability of the Arabic version of STOP-Bang questionnaire Reproducibility of STOP-Bang questionnaire was tested in 20 subjects, and the intraclass correlation coefficient of the total score of STOP-Bang questionnaire was 0.931 (95 % CI 0.834–0.972). STOP-Bang performance
Statistical analysis Data were analyzed using SPSS software for Windows version 20. Continuous data are presented as means±standard deviation, whereas categorical variables are presented as whole numbers and percentages. The test–retest variability was examined by the intraclass correlation coefficient of the total score. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were calculated from 2×2 cross tabulation of OSA classification from PSG and OSA risk classification by STOP-Bang and presented as percentage with 95 % confidence interval (CI). Receiver operating characteristic (ROC) curve was calculated for highrisk patients for the STOP-Bang score ≥3 points
Results
The STOP-Bang Questionnaire was able to detect 168 patients as high risk (≥3) out of total population of 193 patients. Characteristics of questionnaire results are presented in Table 2. Of those classified in the high-risk group 29 (15 %), patients were identified by the sleep study as mild, 34 (17.6 %) as moderate, and 85 (44 %) as severe OSA. Twenty-five patients scored as of low risk on STOP-Bang of whom nine (36 %) patients had normal sleep study outcomes with AHI 50? N: Neck circumference >40 cm? G: Gender male?
123/193 (63.7)
13 (6.7)
167/193 (86.5) 107/193 (55.4) 62/193 (32.1) 67/193 (34.7) 51/193 (26.4) 65/193 (33.7) 150/193 (77.7)
6 (3.1) 19 (9.8) 6 (3.1) 0 0 5 (2.6) 0
important for this tool to pick up most of the patients with OSA severe enough to warrant treatment so that they can be referred on for further treatment (high sensitivity), as well as identification of low-risk patients enabling practitioners to be reasonably sure that patients are unlikely to have OSA (high negative predictive value). Other important characteristics of a good screening tool are ease of administration and scoring, inexpensive, and reliable. STOP-Bang fulfills these criteria, and in our studied population, the first part (STOP questions) was completed by study participants without the help of any health care professional. Among our study population, 85 % were diagnosed to have OSA with AHI of 5 or more. The Arabic STOP-Bang screening tool has very high sensitivity of 97.7 % and NPV of 92 % in picking up patients with severe OSA (AHI ≥30). Based on the evidence, these are the patients at increased mortality and treatment with continuous positive airway pressure (CPAP) has led to improvement in blood pressure control, decreased cardiovascular events, and improved quality of life [16]. In patients with mild OSA (AHI 5 to 5 [14]. These differences in predictive parameters may be due to differences in study population characteristics, morbidities, and differences in methodology. In our patient population, we noticed that 6.7 % of patients did not answer the first question about snoring and 9.8 % did not answer the fourth question about obstruction. An explanation for this may be that the majority of patients were attending without their partners, and they were not sure if their snoring was loud enough to be heard through closed door or if they were having apnea during sleep. One of the major risk factors for OSA is obesity. Interestingly, in our study population, we noticed that the STOP-Bang questionnaire detected only 27 % of those having BMI more
Sleep Breath Table 4 Predictive parameters of the STOP-Bang
AHI apnea/hypopnea index, NPV negative predictive value, PPV positive predictive value, ROC receiver operating characteristic
Sensitivity (%) Specificity (%) PPV (%) NPV (%) Area under ROC curve
AHI ≥5
AHI ≥15
AHI ≥30
90.24 (84.64–94.32) 31.03 (15.32–50.83) 88.10 (82.21–92.57) 36.00 (18.01–57.47) 0.777 (0.701–0.853)
96.75 (91.87–99.09) 30.00 (19.63–42.13) 70.83 (63.34–77.58) 84.00 (63.90–95.36) 0.774 (0.704–0.843)
97.70 (91.92–99.65) 21.70 (14.28–30.76) 50.60 (42.79–58.38) 92.00 (73.93–98.78) 0.784 (0.719–0.850)
than 35 as a high-risk population. For the gold standard test, only 24 % of those having a BMI >35 were classified as moderate to severe OSA. Many studies have been published regarding the association of BMI and ethnicity; however, current WHO cutoff points do not provide an adequate basis for taking action on risks related to overweight and obesity in many populations in Asia [18]. The strength of our study is that the sample size was statistically convenient to test the STOP-Bang questionnaire as a screening tool and all subjects underwent the gold standard test to diagnose OSA. Also, this study confirmed the ability of this tool to detect a high-risk population in a sleep clinic setting. Because we included referred undiagnosed adults to a sleep clinic, this can be counted as a weakness and it may explain why our results showed low specificity and high sensitivity. Other authors have recommended development of a modified STOP-Bang for use in primary care settings with improved specificity which does not compromise sensitivity [19]. Further research needs to be conducted to modify the STOP-Bang questionnaire generally, to improve its specificity.
Conclusion The Arabic version of STOP-Bang questionnaire is an easyto-use tool that can be utilized as a reliable and quick screening tool for OSA in patients referred to sleep clinic. It demonstrated high sensitivity and NPV especially for patients with moderate to severe OSA. We believe that this tool will assist physicians in earlier identification of cases at risk of OSA. Recommendations We should aim to increase awareness about OSA among physicians in our context. Additionally, further studies involving the general population needs to be conducted to assess performance of this screening tool and to examine its utility for
identification of patients with other comorbidities. It is hoped that a modified Arabic STOP-Bang with improved specificity can be developed. Acknowledgments The authors thank Prof. Nico Nagelkerke for his help in the statistical analysis, Prof. Margaret Ann Elzubeir for language editing the manuscript, and Dr. Sarah Elzubeir for her help in the literature review. Conflict of interest interest
The authors declare they have no conflict of
Authors’ contributions S. Alhouqani contributed to the design of the study, data collection, and writing the manuscript. M. Al Manhali contributed to the design of the study, data collection, and writing the manuscript. A. Al Essa contributed to data analysis. M. Al-Houqani contributed to the design of the study, data collection, data analysis, and writing the manuscript.
References 1. AASM Obstructive Sleep Apnea. http://www.aasmnet.org/resources/ factsheets/sleepapnea.pdf. Accessed 10 Sep 2014 2. Hajat C, Harrison O, Shather Z (2012) A profile and approach to chronic disease in Abu Dhabi. Glob Health 8:18. doi:10.1186/ 1744-8603-8-18 3. Young T, Palta M, Dempsey J et al (1993) The occurrence of sleepdisordered breathing among middle-aged adults. N Engl J Med 328: 1230–1235. doi:10.1056/NEJM199304293281704 4. Durán J, Esnaola S, Rubio R, Iztueta A (2001) Obstructive sleep apnea-hypopnea and related clinical features in a population-based sample of subjects aged 30 to 70 yr. Am J Respir Crit Care Med 163: 685–689. doi:10.1164/ajrccm.163.3.2005065 5. Abrishami A, Khajehdehi A, Chung F (2010) A systematic review of screening questionnaires for obstructive sleep apnea. Can J Anaesth J Can Anesth 57:423–438. doi:10.1007/s12630-010-9280-x 6. Mahboub B, Afzal S, Alhariri H et al (2013) Prevalence of symptoms and risk of sleep apnea in Dubai, UAE. Int J Gen Med 6:109–114. doi:10.2147/IJGM.S40001 7. Marin JM, Carrizo SJ, Vicente E, Agusti AGN (2005) Long-term cardiovascular outcomes in men with obstructive sleep apnoeahypopnoea with or without treatment with continuous positive airway pressure: an observational study. Lancet 365:1046–1053. doi:10. 1016/S0140-6736(05)71141-7
Sleep Breath 8. Campos-Rodriguez F, Peña-Griñan N, Reyes-Nuñez N et al (2005) Mortality in obstructive sleep apnea-hypopnea patients treated with positive airway pressure. Chest 128:624–633. doi:10.1378/chest.128. 2.624 9. Yaggi HK, Concato J, Kernan WN et al (2005) Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med 353: 2034–2041. doi:10.1056/NEJMoa043104 10. Chung F, Yegneswaran B, Liao P et al (2008) STOP questionnaire: a tool to screen patients for obstructive sleep apnea. Anesthesiology 108:812–821. doi:10.1097/ALN.0b013e31816d83e4 11. Rosenthal LD, Dolan DC (2008) The Epworth sleepiness scale in the identification of obstructive sleep apnea. J Nerv Ment Dis 196:429– 431. doi:10.1097/NMD.0b013e31816ff3bf 12. Netzer NC, Stoohs RA, Netzer CM et al (1999) Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med 131:485–491 13. Ong TH, Raudha S, Fook-Chong S et al (2010) Simplifying STOPBANG: use of a simple questionnaire to screen for OSA in an Asian population. Sleep Breath SchlafAtm 14:371–376. doi:10.1007/ s11325-010-0350-7
14. Vana KD, Silva GE, Goldberg R (2013) Predictive abilities of the STOP-Bang and Epworth Sleepiness Scale in identifying sleep clinic patients at high risk for obstructive sleep apnea. Res Nurs Health 36: 84–94. doi:10.1002/nur.21512 15. Pecotic R, Dodig IP, Valic M et al (2012) The evaluation of the Croatian version of the Epworth sleepiness scale and STOP questionnaire as screening tools for obstructive sleep apnea syndrome. Sleep Breath Schlaf Atm 16:793–802. doi:10.1007/s11325-011-0578-x 16. Park JG, Ramar K, Olson EJ (2011) Updates on definition, consequences, and management of obstructive sleep apnea. Mayo Clin Proc 86:549–554. doi:10.4065/mcp.2010.0810, quiz 554–555 17. Littner MR (2007) Mild obstructive sleep apnea syndrome should not be treated. Con J Clin Sleep Med JCSM Off Publ Am Acad Sleep Med 3:263–264 18. Expert Consultation WHO (2004) Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 363:157–163. doi:10.1016/S0140-6736(03) 15268-3 19. Cowan DC, Allardice G, Macfarlane D et al (2014) Predicting sleep disordered breathing in outpatients with suspected OSA. BMJ Open 4:e004519. doi:10.1136/bmjopen-2013-004519
ORIGINAL ARTICLE
Evaluation of the Arabic version of STOP-Bang questionnaire as a screening tool for obstructive sleep apnea Shaikha Alhouqani & Mariam Al Manhali & Awad Al Essa & Mohammed Al-Houqani
Received: 10 December 2014 / Accepted: 25 February 2015 # Springer-Verlag Berlin Heidelberg 2015
Abstract Purpose Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that is underdiagnosed. OSA is usually diagnosed by polysomnography (PSG) and, if untreated, could lead to life-threatening complications. Many screening questionnaires have been developed to screen and identify patients at high risk for OSA. This study aimed to evaluate and validate the Arabic version of Stop-Bang questionnaire as a screening tool for patients with OSA symptoms referred to a sleep clinic. Methods All referred Arabic-speaking adult patients presenting to a Sleep Disorders Specialized Clinic in Al Ain for PSG were requested to complete an Arabic STOP-Bang questionnaire. A score of 3 or more out of a possible 8 was taken to indicate high risk for presence of OSA. These scores were then evaluated versus results from the overnight, monitored PSG. Apnea/hypopnea index (AHI) of ≥5/h was considered for diagnosis of OSA. Results One hundred ninety-three sleep clinic patients were enrolled in this study. PSG was positive (AHI ≥5) in 85 % of the studied population. STOP-Bang questionnaire was S. Alhouqani Tawam Hospital, Abu Dhabi, United Arab Emirates e-mail: [email protected] M. Al Manhali Ambulatory Health Services, Abu Dhabi, United Arab Emirates e-mail: [email protected] A. Al Essa Nursing Research, Department of Internal Medicine, College of Medicine and Health Sciences, UAE University, Abu Dhabi, United Arab Emirates e-mail: [email protected] M. Al-Houqani (*) College of Medicine and Health Sciences, UAE University, P.O.Box 17666, Al Ain, Abu Dhabi, United Arab Emirates e-mail: [email protected]
positive (≥3) in 87 % of the population. Reproducibility of STOP-Bang questionnaire was tested, and the intraclass correlation coefficient of the total score of STOP-Bang questionnaire was 0.931 (95 % CI 0.834–0.972). The sensitivities of the STOP-Bang screening tool for an AHI of ≥5, ≥15, and ≥30 were 90, 96.75, and 99.70 %, respectively, with negative predictive values (NPVs) of 36, 84, and 92 %, respectively. ROC curve was 0.77. Conclusion The Arabic version of STOP-Bang questionnaire is an easy-to-use tool that can be implemented as a reliable, quick screening tool for OSA in patients referred to sleep clinic. It demonstrated high sensitivity and NPVespecially for patients with moderate to severe OSA. We believe that this tool will help physicians to earlier identify cases at risk of OSA. Keywords STOP-Bang . Obstructive sleep apnea . Screenings . Validation Abbreviations OSA Obstructive sleep apnea PSG Polysomnography SB Stop-Bang ESS Epworth sleepiness scale AHI Apneas/hypopnea index NPV Negative predictive values PPV Positive predictive values CI Confidence interval ROC Receiver operating characteristic
Introduction Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that involves a decrease or complete halt in airflow despite an ongoing effort to breathe; leading to short- and
Sleep Breath
long-term complications if left undiagnosed. It leads to partial reductions (hypopneas) and complete pauses (apneas) in breathing that last at least 10 s during sleep, resulting in a fragmented quality of sleep that often produces an excessive level of daytime sleepiness. Most people with OSA snore loudly and frequently, with periods of silence when airflow is reduced or blocked. They then make choking, snorting, or gasping sounds when their airway reopens [1]. One of the major OSA risk factors is obesity. In the emirates of Abu Dhabi, 67 % of adults are either overweight or obese, and 57 % have been identified as having central obesity [2]. The prevalence of OSA among the general population is estimated between 2 and 26 % [3, 4]]. In the United Arab Emirates, the prevalence of OSA symptoms among Dubai citizens was found to be around 21 % [6]. However, due to a limited number of sleep laboratories in the United Arab Emirates, OSA remains underdiagnosed. Previous investigators have confirmed that untreated OSA is associated with life-threatening complications such as resistant hypertension and cardiovascular events and could affect overall quality of life [7–9]. The gold standard test for OSA is polysomnography (PSG), which is an expensive, not widely available test in the United Arab Emirates, inconvenient to patients as they need to stay overnight in the sleep laboratory. Many screening questionnaires have been developed to screen and identify patients at high risk for OSA. Examples include Stop-Bang (SB), Epworth sleepiness scale (ESS), Berlin Questionnaire, and modified neck circumference [10–12]. Most of these screening tools have been evaluated and show acceptable sensitivity in primary care settings [13]. The Stop-Bang questionnaire is an easy to administer questionnaire that was initially validated as a screening tool for OSA in a surgical population [5]. It consists of eight independent questions with a score of 3 or more indicating high-risk patients for OSA. Vana and colleagues [14] concluded in their study that STOP-Bang could identify more patients with OSA than ESS in a sleep clinic setting with a sensitivity of 94.7 % compared to a sensitivity of 26.3 % in ESS. Another study by Pecotic and others showed that STOP-Bang had better probability to correctly predict high-risk patients for OSA compared to ESS [15]. To our knowledge, however, there is no study examining the utility and diagnostic accuracy of the Arabic version of the STOPBang questionnaire. This study aims to evaluate and validate the Arabic version of Stop-Bang questionnaire as a screening tool for patients with OSA symptoms referred to a sleep clinic.
Methods Setting This study was performed at the Sleep Disorders Specialized Clinic, Al Ain, United Arab Emirates, during the period from
June 2012 to April 2013. The study protocol (no. 13/30) was obtained and approved by the Human Research Ethics Committee of Al Ain Medical District. On their first visit to the clinic, all participants gave informed consent to participate in the study. Translation of STOP-Bang questionnaire The STOP-Bang questionnaires were translated into the Arabic language by two clinicians. The questionnaires were then administered to a small group of 20 patients seen at the Sleep Disorders Specialized Clinic to ensure clarity and face validity. The questionnaires were back translated from Arabic into English by a bilingual professional translator for comparison with the original text. The sentence structure and presentation of the STOP-Bang questionnaires were similar to those of the English version. Because STOP-Bang questions reflected different dimensions of OSA morbidity, internal consistency checking was not applicable, but we performed test–retest reliability of the total score in 20 subjects who completed STOP-Bang on two occasions, 1 week apart. STOP-Bang questionnaire All referred patients presenting to the sleep clinic were requested to complete the questionnaire. We used the eightpoint STOP-Bang format. This format consists of two parts; the first part, “STOP,” includes four questions for patient to answer about snoring, tiredness, obstruction or observed apnea, and blood pressure. Each question requires a “yes” or “no” answer and each “yes” accounts for one point. The second part, “BANG,” was completed by a health care professional (respiratory technician), and questions were about body mass index (if more than 35), age (if more than 50), neck circumference (if more than 40 cm), and gender (if male). The questions were in “yes/no” answer format, and each “yes” accounted for one point. All these parameters were collected during patient’s first visit to the clinic prior to the sleep study.
Subjects/population We reviewed 425 cases that were referred to the Sleep Disorders Specialized Clinic, and from those, a total of 193 were included. Inclusion criteria were as follows: all adults aged 18 years and more, Arabic speaking, not known to have OSA, completed STOP-Bang questionnaire in Arabic, and had PSG. Patients less than 18 years old were excluded because some of the questionnaire’s elements are not applicable to the pediatric population. Demographic data and vital signs (height, weight, and neck circumference) were collected from patients’ files together with the filled questionnaire.
Sleep Breath
Polysomnography The nocturnal PSG consisted of continuous polysomnographic (Compumedics Grael and Somte PSG, Australia) recordings of a standard electroencephalographic montage consisting of six electroencephalograms (F3-M2, F4-M1, C3–M2, C4–M1, O1–M2, O2–M1), right and left electroocculogram, submental and bilateral tibial electromyogram, and electrocardiogram using surface electrodes. Respiration was monitored with oronasal thermocouples and with nasal pressure transducers. Thoracoabdominal movements were monitored using respiratory inductance plethysmography (RIP). Continuous pulse oximetry was also monitored. Sleep stage scoring was performed in 30-s epochs by certified registered polysomnographic technologists according to American Association of Sleep Medicine (AASM) criteria. Apnea was defined as cessation of airflow for more than 10 s. Hypopneas were scored as at least 30 % decrease in airflow with 3 % oxygen desaturation and/or arousal. The apnea/ hypopnea index was defined as the total number of apneas and hypopneas per hour of sleep time. An AHI of ≥5 was considered for diagnosis of OSA. Subjects with sleep apnea were classified into three subgroups according to their AHI: mild subgroup (subjects with AHI 35, n (%) Neck circumference (cm) AHI Total sleep time % Sleep efficiency Respiratory disturbance index % Lowest SpO2
42.87±11.838 150 (77.7) 34.90±8.602 67 (34.7) 39.54±3.463 34.87±31.276 311.90±79.634 81.43±14.917 37.83±30.156 78.10±12.737
BMI body mass index, AHI apnea/hypopnea index
of the studied population. STOP-Bang questionnaire was positive (≥3) in 87 % of the population. Reliability of the Arabic version of STOP-Bang questionnaire Reproducibility of STOP-Bang questionnaire was tested in 20 subjects, and the intraclass correlation coefficient of the total score of STOP-Bang questionnaire was 0.931 (95 % CI 0.834–0.972). STOP-Bang performance
Statistical analysis Data were analyzed using SPSS software for Windows version 20. Continuous data are presented as means±standard deviation, whereas categorical variables are presented as whole numbers and percentages. The test–retest variability was examined by the intraclass correlation coefficient of the total score. Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) were calculated from 2×2 cross tabulation of OSA classification from PSG and OSA risk classification by STOP-Bang and presented as percentage with 95 % confidence interval (CI). Receiver operating characteristic (ROC) curve was calculated for highrisk patients for the STOP-Bang score ≥3 points
Results
The STOP-Bang Questionnaire was able to detect 168 patients as high risk (≥3) out of total population of 193 patients. Characteristics of questionnaire results are presented in Table 2. Of those classified in the high-risk group 29 (15 %), patients were identified by the sleep study as mild, 34 (17.6 %) as moderate, and 85 (44 %) as severe OSA. Twenty-five patients scored as of low risk on STOP-Bang of whom nine (36 %) patients had normal sleep study outcomes with AHI 50? N: Neck circumference >40 cm? G: Gender male?
123/193 (63.7)
13 (6.7)
167/193 (86.5) 107/193 (55.4) 62/193 (32.1) 67/193 (34.7) 51/193 (26.4) 65/193 (33.7) 150/193 (77.7)
6 (3.1) 19 (9.8) 6 (3.1) 0 0 5 (2.6) 0
important for this tool to pick up most of the patients with OSA severe enough to warrant treatment so that they can be referred on for further treatment (high sensitivity), as well as identification of low-risk patients enabling practitioners to be reasonably sure that patients are unlikely to have OSA (high negative predictive value). Other important characteristics of a good screening tool are ease of administration and scoring, inexpensive, and reliable. STOP-Bang fulfills these criteria, and in our studied population, the first part (STOP questions) was completed by study participants without the help of any health care professional. Among our study population, 85 % were diagnosed to have OSA with AHI of 5 or more. The Arabic STOP-Bang screening tool has very high sensitivity of 97.7 % and NPV of 92 % in picking up patients with severe OSA (AHI ≥30). Based on the evidence, these are the patients at increased mortality and treatment with continuous positive airway pressure (CPAP) has led to improvement in blood pressure control, decreased cardiovascular events, and improved quality of life [16]. In patients with mild OSA (AHI 5 to 5 [14]. These differences in predictive parameters may be due to differences in study population characteristics, morbidities, and differences in methodology. In our patient population, we noticed that 6.7 % of patients did not answer the first question about snoring and 9.8 % did not answer the fourth question about obstruction. An explanation for this may be that the majority of patients were attending without their partners, and they were not sure if their snoring was loud enough to be heard through closed door or if they were having apnea during sleep. One of the major risk factors for OSA is obesity. Interestingly, in our study population, we noticed that the STOP-Bang questionnaire detected only 27 % of those having BMI more
Sleep Breath Table 4 Predictive parameters of the STOP-Bang
AHI apnea/hypopnea index, NPV negative predictive value, PPV positive predictive value, ROC receiver operating characteristic
Sensitivity (%) Specificity (%) PPV (%) NPV (%) Area under ROC curve
AHI ≥5
AHI ≥15
AHI ≥30
90.24 (84.64–94.32) 31.03 (15.32–50.83) 88.10 (82.21–92.57) 36.00 (18.01–57.47) 0.777 (0.701–0.853)
96.75 (91.87–99.09) 30.00 (19.63–42.13) 70.83 (63.34–77.58) 84.00 (63.90–95.36) 0.774 (0.704–0.843)
97.70 (91.92–99.65) 21.70 (14.28–30.76) 50.60 (42.79–58.38) 92.00 (73.93–98.78) 0.784 (0.719–0.850)
than 35 as a high-risk population. For the gold standard test, only 24 % of those having a BMI >35 were classified as moderate to severe OSA. Many studies have been published regarding the association of BMI and ethnicity; however, current WHO cutoff points do not provide an adequate basis for taking action on risks related to overweight and obesity in many populations in Asia [18]. The strength of our study is that the sample size was statistically convenient to test the STOP-Bang questionnaire as a screening tool and all subjects underwent the gold standard test to diagnose OSA. Also, this study confirmed the ability of this tool to detect a high-risk population in a sleep clinic setting. Because we included referred undiagnosed adults to a sleep clinic, this can be counted as a weakness and it may explain why our results showed low specificity and high sensitivity. Other authors have recommended development of a modified STOP-Bang for use in primary care settings with improved specificity which does not compromise sensitivity [19]. Further research needs to be conducted to modify the STOP-Bang questionnaire generally, to improve its specificity.
Conclusion The Arabic version of STOP-Bang questionnaire is an easyto-use tool that can be utilized as a reliable and quick screening tool for OSA in patients referred to sleep clinic. It demonstrated high sensitivity and NPV especially for patients with moderate to severe OSA. We believe that this tool will assist physicians in earlier identification of cases at risk of OSA. Recommendations We should aim to increase awareness about OSA among physicians in our context. Additionally, further studies involving the general population needs to be conducted to assess performance of this screening tool and to examine its utility for
identification of patients with other comorbidities. It is hoped that a modified Arabic STOP-Bang with improved specificity can be developed. Acknowledgments The authors thank Prof. Nico Nagelkerke for his help in the statistical analysis, Prof. Margaret Ann Elzubeir for language editing the manuscript, and Dr. Sarah Elzubeir for her help in the literature review. Conflict of interest interest
The authors declare they have no conflict of
Authors’ contributions S. Alhouqani contributed to the design of the study, data collection, and writing the manuscript. M. Al Manhali contributed to the design of the study, data collection, and writing the manuscript. A. Al Essa contributed to data analysis. M. Al-Houqani contributed to the design of the study, data collection, data analysis, and writing the manuscript.
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