Prospective assessment of the risk of obstructive sleep apnea in patients attending a tertiary health facility in Sub-Saharan Africa
Obianuju Beatrice Ozoh, Njideka Ulunma Okubadejo, Ayesha Omolara Akinkugbe, Oluwadamilola Omolara Ojo, Chinyere Nkiru Asoegwu, Casmir Amadi, Ifedayo Odeniyi, Amam Chinyere Mbakwem
The Pan African Medical Journal. 2014;17:302. doi:10.11604/pamj.2014.17.302.2898

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Prospective assessment of the risk of obstructive sleep apnea in patients attending a tertiary health facility in Sub-Saharan Africa

Cite this: The Pan African Medical Journal. 2014;17:302. doi:10.11604/pamj.2014.17.302.2898

Received: 31/05/2013 - Accepted: 31/03/2014 - Published: 21/04/2014

Key words: Obstructive sleep apnea, excessive day time sleepiness, tertiary hospital, Nigeria

© Obianuju Beatrice Ozoh et al. The Pan African Medical Journal - ISSN 1937-8688. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Available online at: http://www.panafrican-med-journal.com/content/article/17/302/full

Corresponding author: Obianuju Beatrice Ozoh, Departments of Medicine, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Lagos State, Nigeria (ujuozoh@yahoo.com)


Prospective assessment of the risk of obstructive sleep apnea in patients attending a tertiary health facility in Sub-Saharan Africa

 

Obianuju Beatrice Ozoh1,&, Njideka Ulunma Okubadejo1, Ayesha Omolara Akinkugbe1, Oluwadamilola Omolara Ojo1, Chinyere Nkiru Asoegwu2, Casmir Amadi1, Ifedayo Odeniyi1, Amam Chinyere Mbakwem1

 

1Departments of Medicine, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Lagos State, Nigeria, 2Departments Surgery, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Lagos State, Nigeria

 

 

&Corresponding author
Obianuju Beatrice Ozoh, Departments of Medicine, Faculty of Clinical Sciences, College of Medicine, University of Lagos, Lagos State, Nigeria

 

 

Abstract

Introduction: The impact of Obstructive sleep apnea (OSA) in worsening outcomes is profound, especially in the presence of comorbid conditions. This study aimed to describe the proportion of patients at a high risk of OSA in our practice setting.

 

Methods: The STOP BANG questionnaire and the Epworth Sleepiness scale were used to assess for OSA risk and excessive daytime sleepiness respectively. Hospitalized patients and out-patients were recruited. Intergroup differences in continuous variables were compared using the analysis of variance. The proportion of patients with high risk of OSA and excessive daytime sleepiness was presented as frequencies and group differences compared with the Pearson χ2 test. Independent risk predictors for OSA were assessed in multivariate logistic regression analysis.

 

Results: A total of 1100 patients (53.4% females) participated in the study. Three hundred and ninety nine (36.3%) had a high risk of OSA, and 268 (24.4%) had excessive daytime sleepiness. Of the participants with high OSA risk, 138 (34.6%) had excessive daytime sleepiness compared to 130 (18.5%) of those with low OSA risk (p<0.0001). Age above 65 years, excessive daytime sleepiness, abdominal adiposity, resistant hypertension and high overall cardiovascular risk were independent determinants of a high OSA risk. The magnitude of risk associated with these independent predictors of high risk (Odds ratio) was highest for persons aged above 65 years, those with excessive day time sleepiness, and presence of abdominal adiposity.

 

Conclusion: A significant proportion of patients attending our tertiary care center are at high risk of OSA.

 

 

Introduction

Obstructive sleep apnea (OSA) is a form of sleep disordered breathing characterized by repetitive partial or complete upper airway obstruction during sleep resulting in episodes of hypoxia and frequent arousals [1]. The adverse consequences include excessive daytime sleepiness, impaired cognition, and reduced vigilance with higher risk for motor vehicular and occupational accidents. There is a strong association of OSA with adverse cardiovascular events like stroke, coronary artery disease, diabetes mellitus, and cardiac arrhythmias as well as an overall impairment in the health related quality of life [2-5].

There is a wide variation in published prevalence of OSA (assessed by polysomnography) ranging from 2 to 30%, presumably consequent upon varying methodologies including sampling schemes, instrument and technique used for monitoring sleep and breathing, diagnostic criteria and population studied [6-11]. The prevalence of a high risk of OSA using screening questionnaires ranges from 20 - 80%, with higher rates from hospital-based compared to population-studies [12-14].

The strongest risk association for OSA is with obesity (including central obesity) [6,11].Other risk factors for OSA include male gender, menopause, increasing age (with a plateau at 65 years), and altered craniofacial anatomy such as retrognathia, tonsilar hypertrophy, enlarged tongue or soft palate, inferiorly positioned hyphoid bone, maxillary and mandibular retroposition, and decreased posterior airway space [8-11,15,16]. Cigarette smoking (including second-hand smoke), polycystic ovarian syndrome, hypothyroidism and pregnancy have also been implicated as risk factors [17-20]. Large scale studies have confirmed a role for inheritance and familial factors in the genesis of OSA [21-23].

The gold standard for diagnosis of OSA is laboratory polysomnography (PSG) however, polysomnography is expensive and not readily available, and only approximately 10% of the demand for PSG testing in patients with suspected OSA is met [24,25]. The diagnosis of OSA however can be enhanced by use of validated questionnaires to identify those at high risk for further assessment [26,27].

There is limited data on the burden of OSA in Nigeria. Available data reports a 20% prevalence of high risk OSA among hospital workers [12]. This risk is expected to be higher in a hospital based population due to the presence of comorbid conditions. Increased awareness, early diagnosis and appropriate intervention are particularly important in persons at high risk especially in the presence of co-morbidities including medical and surgical conditions. The burden of OSA in such patients in the Nigerian context is unclear. This study was therefore designed to screen for the risk of OSA and daytime sleepiness in both hospitalized patients and outpatients attending the Lagos University Teaching Hospital (LUTH) Lagos, Nigeria. This study will improve our appreciation of the burden of OSA in Nigerian patients and provide data for comparison with other populations.

 

 

Methods

Study Description

 

This was a descriptive cross sectional study conducted over a 12 week period. The study protocol was approved by the Lagos University Teaching Hospital Health Research Ethics Committee (LUTHHREC) (ADM/DCST/HREC/185), a multi-specialty tertiary care facility in Lagos State, south western Nigeria. The study recruited adult patients (aged≥15 years) from the inpatient and outpatient services of the LUTH. Recruitment in the inpatient setting was from the adult surgical and medical wards and included all patients hospitalized over a 2-week period. Ambulatory outpatient recruitments were from one surgical clinic (otorhinolaryngology) and six medical clinics (respiratory, neurology, endocrinology/diabetology, cardiology, nephrology, and dermatology). Informed consent was obtained from all patients or their proxies.

Study instrument and administration

Demographic and clinical information were obtained from patients and their case records, and included the age, gender, tentative or final diagnosis, and presence of cardiovascular risk factors based on historical, prior diagnostic evaluation, or physical examination. Specifically, the presence any of the following - diabetes mellitus, hypertension, current cigarette smoking, obesity, and central adiposity, were documented, with patient's having any of these categorized as high cardiovascular risk. Standard current diagnostic criteria for the preceding conditions were employed [28-31]. Resistant hypertension was defined as the presence of uncontrolled hypertension despite the use of maximal doses of three antihypertensive drugs, one of which included a diuretic [32].

To assess the risk of OSA and daytime sleepiness, we employed the STOP-BANG questionnaire and Epworth Sleepiness Scale (ESS) respectively. All questionnaires were interviewer administered, and all interviewers were physicians trained in the administration of the questionnaires as part of the study protocol.

The STOP-BANG questionnaire is a simple validated 8 item instrument that asks about symptoms of Snoring, Tiredness, Observed apnea and a history of high blood Pressure [26,33]. It also includes a section to document the body mass index, age, neck circumference, and gender. The STOP-BANG questionnaire was initially developed after factor analysis and reliability check in a cohort of 2467 patients of whom 211 underwent polysomnography for validation. The sensitivity of the STOP-BANG questionnaire in accurately diagnosing OSA in persons with AHI index greater than 5, 15 and 30 was 83.6, 92.9 and 100% respectively [26]. There was no significant difference between the sensitivities of the STOP-BANG, Berlin questionnaire and the American Society of Anaesthesiology checklist for OSA screening as demonstrated among 117 patients who underwent polysomnography (65.6-75.9%, 68.9-87.2%, and 72.1-87.2% respectively) [33]. A systematic review of the various screening tools for OSA recommends using the STOP-BANG questionnaire because it has higher methodological quality and easy to use features [34]. To use the STOP-BANG questionnaire, a total score of 3 and above is considered a high risk of OSA [33].

The Epworth Sleepiness Scale© (ESS ©MW Johns 1990-1997) used with permission, is a validated 8-item questionnaire that measures the ease of falling asleep in the daytime under various circumstances as a measure of daytime hypersomlonence [35]. In the setting of OSA, the ESS has been shown to distinguish between patients with primary snoring and OSA [36]. A total score of 10 and above is suggestive of a sleep disorder possibly OSA [35].

Data analysis

Data obtained was analyzed using the Statistical Software for Social Sciences (SPSS) version 17. Continuous variables are expressed as means and standard deviation, and intergroup differences compared using Analysis of variance (ANOVA). Group differences in discrete variables (presented as frequencies), are compared with the Pearson chi square. Independent risk predictors for OSA were assessed in multivariate logistic regression analysis. A p value of <0.05 was considered significant.

 

 

Results

Baseline characteristics of study participants

The baseline data of the 1100 patients studied is shown in Table 1, and includes the gender distribution, age parameters, location of participants (in-patient or out-patient), specialty category (medical or surgical), anthropometric indices (body mass index, neck circumference, waist circumference). Hypertension was present in 456(41.5%) and 84(7.6%) had resistant hypertension. One hundred and nineteen (10.8%) had diabetes and 58(5.3%) were current smokers. However, the overall cardiovascular risk was high in 685 (62.3%).

Risk of obstructive sleep apnea and determinants in study participants

The risk of OSA (based on the STOP-BANG questionnaire) was low in 701 (63.7%) and high in 399 (36.3%) of the participants. None of the patients had a previous diagnosis of OSA. The proportion of medical patients with a high risk of OSA was significantly higher (361, 38%) compared to surgical patients (38, 25.3%) (P=0.003). Risk of OSA was high in 59 (42.4%) inpatients and 340 (35.3%) outpatients (P=0.1)

An initial univariate logistic regression analysis showed that all the variables explored (age, diabetes, resistant hypertension, cigarette smoking, abdominal adiposity and ESS score) were significantly associated with high risk of OSA (P<0.001). All the parameters were thus imputed in a multiple logistic regression model to identify the independent determinants of high risk of OSA (Table 2). Age above 65 years, excessive daytime sleepiness (ESS score≥10), presence of abdominal adiposity, resistant hypertension and high overall cardiovascular risk were independent determinants of a high risk of OSA. The magnitude of risk associated with these independent predictors of high risk (represented by the Odds ratio) was highest for persons aged above 65 years, those with excessive day time sleepiness, and presence of abdominal adiposity (Table 2)

Relationship between OSA risk and excessive daytime sleepiness

Based on the ESS score, 268 (24.4%) of the participants had excessive daytime sleepiness. Figure 1 shows a positive correlation between the STOP-BANG scores and the ESS scores. Of the participants with high risk of OSA, 138 (34.6%) also had excessive daytime sleepiness compared to 130 (18.5%) of those with low risk of OSA with excessive daytime sleepiness (p<0.0001).

 

 

Discussion

Under-recognition of obstructive sleep apnea (OSA) worsens co-morbid cardiovascular diseases and impairs global quality of life, both cognitive and physical. The main finding in this study is that a significant proportion (36%) of patients attending our tertiary care hospital for diverse medical and surgical conditions is at a high risk of OSA. Other important findings are that those at high risk of OSA also have a high risk of excessive daytime sleepiness and that presence of abdominal adiposity and age above 65 years confer an increase in OSA risk, thus highlighting specific subgroups of patients who require formal diagnostic evaluation using polysomnography.

The prevalence of high risk of OSA in this study is comparable to that in earlier studies from other populations [10,12-13]. Interestingly, none of the patients in our study had a prior diagnosis of OSA or was on treatment. This high rate of under-diagnosis in our practice setting possibly represents a low index of suspicion or physician unawareness of the burden of the disease, risk factors and the health hazards of untreated OSA. Among surgical patients, untreated OSA increases the risk of perioperative complications including difficult intubation, post-operative respiratory and cardiovascular complications, increased admission to the intensive care unit, prolonged hospital stay, and death [37,38]. OSA also increases cardiovascular risk, as repeated episodes of apnea during sleep result in hypoxia, hypercapnia, raised intra-thoracic pressures, repeated arousals and sleep deprivation leading to sympathetic activation, metabolic dysregulation, endothelial dysfunction, systemic inflammation, hypercoagulability and left atrial enlargement [2]. Therefore untreated OSA worsens outcome in a wide range of medical conditions including hypertension, heart failure, cardiac arrhythmias, renal disease, stroke, myocardial infarction, asthma, epilepsy, reactive bladder, and urinary incontinence [2-4,39-41].

Our findings corroborate the increased risk and prevalence of OSA with advancing age [8-11]. We found that age above 65 years was associated with the highest risk for OSA (Odds ratio 6.96) implying a further increase in risk of adverse cardiovascular outcomes in the elderly who often have other comorbid conditions. The mechanisms for the age related increase in the prevalence of OSA include increased deposition of fat in the pharyngeal area, lengthening of the soft palate, and changes in body structure surrounding the pharynx [42,43].

In our study, high risk of OSA was associated with a high risk of excessive daytime sleepiness similar to findings in earlier reports of excessive daytime sleepiness as a major effect of OSA [44]. Excessive daytime sleepiness occurs due to lack of restful sleep and is of major public health concern as it increases the risk of road traffic accidents and other occupational injuries [5]. Also, there is an overall reduction in productivity arising from impaired neurocognitive functioning leading to poor concentration, depression, occupational difficulties, poor libido and overall negative impact on the quality of life [45,46].

Our study demonstrates that OSA is a common co-morbidity in many hospital patients and therefore highlights the need to identify and treat these patients. Treatment strategies in OSA are specific to the individual scenario, but may include weight loss (which improves overall cardiovascular risk), use of oral appliances that keep the airway open during sleep, surgery (uvulopalatopharyngoplasty, tonsillectomy, radiofrequency ablation of the base of the tongue, mandibular advancement), and the use of continuous positive airway pressure (CPAP) [44,47-50]. CPAP has been shown to be the most effective treatment in controlling symptoms and improving cardiovascular risk [50]. Smoking cessation, avoiding alcohol, sedatives and sleeping pills in the evenings are adjunctive modalities that improve symptoms [47].

The findings in this study are limited by some factors identified here. Risk assessment of OSA using questionnaires is not diagnostic but identifies persons at high risk in whom further evaluation by polysomnography is warranted. The STOP-BANG questionnaire though previously validated was not re-validated in our patient population using polysomnography, however, the format of the questions (yes/no) and the standardization of the measurements make its use as a screening tool generalizable. This study was tertiary hospital-based and the study population comprised of a heterogeneous group of patients with potential over-representation of more severely ill persons and those with clinical conditions that independently increase OSA risk (cardiovascular, oto-rhinolaryngology). However it does provide data on those at highest risk of adverse outcome. Community-based evaluation would have its own benefit of defining the risk burden in the general population and for comparison with other populations.

 

 

Conclusion

In conclusion, OSA is a prevalent but under-diagnosed condition in patients attending our tertiary care center. Additional risk factors observed include increasing age (above 65 years) and abdominal adiposity. Excessive daytime sleepiness commonly occurs in those at high risk of OSA putting them at risk of accidents and neuro-cognitive impairment in the daytime. Increased awareness of OSA among health care providers and patients will improve overall patient care and disease outcome and ultimately reduce mortality. Despite limited resources and difficulty in confirming the diagnosis of OSA as may occur in our setting, treatment of patients who are at high risk from screening and in whom symptoms are suggestive of OSA should be considered especially in the presence of comorbid conditions.

 

 

Competing interests

The authors declare no competing interests.

 

 

Authorsí contributions

All authors contributed substantially to the concept and design of the study, data acquisition and interpretation of the data. OBO and NUO analyzed the data and drafted the initial manuscript. All authors participated in revision of the manuscript for intellectual content and gave final approval to the version to be published. OBO stands as guarantor to the entire manuscript.

 

 

Tables and figures

Table 1: Baseline data and test scores of participants

Table 2: Determinants of high risk for obstructive sleep apnea

Figure 1: Relationship between STOP-bang score and Epworth Sleepiness Scale score

 

 

References

  1. White DP. Sleep related breathing disorder: Pathophysiology of obstructive sleep apnea. Thorax. 1995 Jul;50(7):797-804. PubMed | Google Scholar

  2. Somers VK, White DP, MD, Amin R, et al. Sleep apnea and cardiovascular disease. Circulation. 2008 Sep 2;118(10):1080-111. PubMed | Google Scholar

  3. Yaggi H, Concato J, Kernan WN. Obstructive sleep apnea as a risk factor for stroke and death. N Engl J Med. 2005 Nov 10;353(19):2070-3. PubMed | Google Scholar

  4. Punjabi NM, Sorkin JD, Katzel LI, et al. Sleep-disordered breathing and insulin resistance in middle-aged and overweight men. Am J Respir Crit Care Med. 2002 Mar 1;165(5):677-82. PubMed | Google Scholar

  5. Pack AI, Dinges D, Maislin G. A study of prevalence of sleep apnea among commercial truck drivers: Federal Motor Carrier Safety Administration Publication. 2002. No DOT-RT-02-030. PubMed | Google Scholar

  6. Young T, Palta M, Dempsey J, et al. The occurrence ofsleep-disordered breathing among middle-aged adults. N Engl J Med. 1993 Apr 29;328(17):1230-5. PubMed | Google Scholar

  7. Ip MS, Lam B, Lauder IJ, et al. A community study of sleep-disordered breathing in middle-aged Chinese men in Hong Kong. Chest. 2001 Jan;119(1):62-9. PubMed | Google Scholar

  8. Bixler EO, Vgontzas AN, Lin HM, et al. Prevalence of sleep-disordered breathing in women: effects of gender. Am J RespirCrit Care Med. 2001 Mar;163(3 Pt 1):608-13. PubMed | Google Scholar

  9. Udwadia ZF, Doshi AV, Lonkar SG, et al. Prevalence of sleep-disordered breathing and sleep apnea in middle-aged urban Indian men. Am J Respir Crit Care Med. 2004 Jan 15;169(2):168-73. PubMed | Google Scholar

  10. TufikS, Santos-Silva R, Taddei JA, et al. Obstructive sleep apnea in the Sao Paulo epidemiologic sleep study. Sleep Med. 2010 May;11(5):441-6. PubMed | Google Scholar

  11. Punjabi NM. The epidemiology of adult obstructive sleep apnea. Proc Am Thorac Soc. 2008 February 15; 5(2): 136-143. PubMed | Google Scholar

  12. Adewole AA, Hakeem A, Ayeni F, et al. Obstructive sleep apnea among adults in Nigeria. J Natl Med Assoc. 2009 Jul;101(7):720-5. PubMed | Google Scholar

  13. Menon L, Rudraraju P, Daniel V, et al. Prevalence of symptoms of obstructive sleep apnea in patients attending an inner city primary care clinic. The Internet Journal of Public Health. 2011;1:1. PubMed | Google Scholar

  14. Kumar S, McElligott D, Goyal A, et al. Risk of obstructive sleep (OSA) apnea in hospitalized patients [abstract]. Chest. 2010;138:779A. PubMed | Google Scholar

  15. Young T, Shahar E, Nieto FJ, et al. Sleep Heart Health Study Research group: Predictors of sleep-disordered breathing in community-dwelling adults: the Sleep Heart Health Study. Arch Intern Med. 2002 Apr 22;162(8):893-900. PubMed | Google Scholar

  16. Cistulli PA. Craniofacial abnormalities in obstructive sleep apnoea: implications for treatment. Respirology. 1996 Sep;1(3):167-74. PubMed | Google Scholar

  17. Franklin KA, Gislason T, Omenaas E, et al. The influence of active and passive smoking on habitual snoring. Am J Respir Crit Care Med. 2004 Oct 1;170(7):799-803. PubMed | Google Scholar

  18. Fogel RB, Malhotra A, Pillar G, et al. Increased prevalence of obstructive sleep apnea syndrome in obese women with polycystic ovary syndrome. J Clin Endocrinol Metab. 2001 Mar;86(3):1175-80. PubMed | Google Scholar

  19. Pelttari L, Rauhala E, Polo O, et al. Upper airway obstruction in hypothyroidism. J Intern Med. 1994 Aug;236(2):177-81. PubMed | Google Scholar

  20. Izci B, Vennelle M, Liston WA, et al. Sleep-disordered breathing and upper airway size in pregnancy and post-partum. Eur Respir J. 2006 Feb;27(2):321-7. PubMed | Google Scholar

  21. Redline S, Tishler PV. The genetics of sleep apnea. Sleep Med Rev. 2000 Dec;4(6):583-602. PubMed | Google Scholar

  22. Palmer LJ, Buxbaum SG, Larkin EK, et al. Whole genome scan for obstructive sleep apnea and obesity in African-American families. Am J Respir Crit Care Med. 2004 Jun 15;169(12):1314-21. PubMed | Google Scholar

  23. Gottlieb DJ, DeStefano AL, Foley DJ, et al. APOE epsilon4 is associated with obstructive sleep apnea/hypopnea: the Sleep Heart Health Study. Neurology. 2004 Aug 24;63(4):664-8. PubMed | Google Scholar

  24. Polysomnography Task Force, American Sleep Disorders Association Standards of Practice Committee. Practice parameters for the indications for polysomnography and related procedures. Sleep. 1997 Jun;20(6):406-22. PubMed | Google Scholar

  25. Pagel JF. Obstructive sleep apnea (OSA) in primary care: evidence-based practice. J Am Board Fam Med. 2007 Jul-Aug;20(4):392-8. PubMed | Google Scholar

  26. Chung F, Yegneswaran B, Liao P, et al. STOP questionnaire; a tool to screen patients with obstructive sleep apnea. Anesthesiology. 2008 May;108(5):812-21. PubMed | Google Scholar

  27. Netzer NC, Stoohs RA, Netzer CM, et al. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999 Oct 5;131(7):485-91. PubMed | Google Scholar

  28. The Seventh report of the Joint National Committee on the Prevention, Detection, Evaluation and Treatment of High Blood Pressure. NIH publication. 2004; No 04-5230. Google Scholar

  29. IDF Clinical Guidelines Task Force. Global guidelines for Type 2 diabetes. Brussels: International Diabetes Federation publication. 2005. PubMed | Google Scholar

  30. Eknoyan G. Adolphe Quetlet: the average man and the indices of obesity. Nephrol Dial Transplant.23 (1): 47-51. PubMed | Google Scholar

  31. The IDF consensus worldwide definition of the metabolic syndrome. Available at idf.org/ VAT BE433.674.528. PubMed | Google Scholar

  32. Calhoun DA, Jones D, Textor S, et al. American Heart Association Professional Education Committee: Resistant hypertension: diagnosis, evaluation, and treatment / A scientific statement from the American Heart Association Professional Education Committee of the Council for High Blood Pressure Research. Hypertension. 2008;51:1403. PubMed | Google Scholar

  33. Chung F, Yegneswaran B, Liao P, et al. Validation of the Berlin questionnaire, the American Society of Anesthesiologist checklist as screening tools for obstructive sleep apnea in surgical patients. Anesthesiology. 2008 May;108(5):822-30. PubMed | Google Scholar

  34. Abrishami A, Khajehdehi A, Chung F. A systematic review of screening questionnaires for obstructive sleep apnea. Can J Anaesth. 2010 May;57(5):423-38. PubMed | Google Scholar

  35. John MW. A new method to measure daytime sleepiness: the Epworth Sleepiness Scale. Sleep. 1999;14:540-545. PubMed | Google Scholar

  36. Johns MW. Daytime sleepiness snoring and obstructive sleep apnea: The Epworth sleepiness scale. Chest. 1993 Jan;103(1):30-6. PubMed | Google Scholar

  37. Gupta RM, Parvizi J, Hanssen AD, et al. Postoperative complications in patients with obstructive sleep apnea syndrome undergoing hip or knee replacement: A case-control study. Mayo Clin Proc. 2001 Sep;76(9):897-905. PubMed | Google Scholar

  38. Liao P, Yegneswaran B, Vairavanathan S, et al. Respiratory complications among obstructive sleep apnea (OSA) patients who underwent surgery [abstract]. Sleep. 2007; 30:0582. PubMed | Google Scholar

  39. Teodorescu M, Polomis DA, Hall SV, et al. Association of obstructive sleep apnea risk and asthma control in adults. Chest. 2010 Sep;138(3):543-50. PubMed | Google Scholar

  40. Chihorek AM, Abou-Khalil B, Malow BA. Obstructive sleep apnea is associated with seizure occurrence in older adults with epilepsy. Neurology. 2007 Nov 6;69(19):1823-7. PubMed | Google Scholar

  41. Kemmer H, Mathes AM, Dilk O, et al. Obstructive sleep apnea is associated with over-reactive bladder and urgency incontinence in men. Sleep. 2009 Feb;32(2):271-5. PubMed | Google Scholar

  42. Malhotra A, Huang Y, Fogel R, et al. Aging influences on pharyngeal anatomy and physiology: the predisposition to pharyngeal collapse. Am J Med. ; 2006 January; 119(1): 72.e9-72. PubMed | Google Scholar

  43. Eikermann M, Jordan AS, Chamberlin NL et al. The influence of aging on pharyngeal collapsibility during sleep. Chest. 2007 Jun;131(6):1702-9. PubMed | Google Scholar

  44. Wright J, Johns R, Watt I, et al. Health effects of obstructive sleep apnea and the effect of continuous positive airway pressure: a systematic review of the research evidence. BMJ. 2007;314:851. PubMed | Google Scholar

  45. Shroder CM, O'Hara R. Depression and Obstructive Sleep Apnea (OSA). Annals of General Psychiatry. 2005;4:13. PubMed | Google Scholar

  46. Omachi TA, Claman DM, Blanc PD, et al. Obstructive sleep apnea: a risk factor for work disability. Sleep. 2009 Jun;32(6):791-8. PubMed | Google Scholar

  47. Johansson K, Neovius M, Lagerros YT, et al. Effect of low energy diet on moderate and severe obstructive sleep apnoea in obese men: a randomized controlled trial. BMJ.2009;339:b4609. PubMed | Google Scholar

  48. Ferguson KA, Cartwright R, Rogers R, et al. Oral appliances for snoring and obstructive sleep apnea: a review. SLEEP 2006;29(2): 244-262. Google Scholar

  49. Mehra P, Wolford LM. Surgical management of obstructive sleep apnea. ProcBaylUniv Med Cent. 2000 October; 13(4): 338-342. PubMed | Google Scholar

  50. Wright J, White J, Ducharme F. Continuous positive airways pressure for obstructive sleep apnoea (Cochrane Review). In: The Cochrane Library. Issue 1, 2002.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


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