|Year : 2017 | Volume
| Issue : 1 | Page : 16-22
The prevalence of obstructive sleep apnea in adult patients with sickle cell disease
Rajaa Al-Saqqaf1, Roah Merdad1, Siraj O Wali MBBS, FACP, FCCP, FRCPC 1, Fatin Al-Sayes2, Lana Mukharesh3, Sara Batawi3, Ghadah Batwai3, Maysaa Ageel3, Mohammed Hamid1, Nabil Alama3, Ibrahim AlQassas4
1 Sleep Medicine and Research Center, King Abdulaziz University Hospital, Jeddah, Saudi Arabia
2 Department of Hematology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
3 Internal Medicine Department, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
4 Sleep Medicine and Research Center, King Abdulaziz University Hospital, Jeddah; International Medical Center, Jeddah, Saudi Arabia
|Date of Web Publication||12-Apr-2017|
Siraj O Wali
Professor of Medicine, College of Medicine, King Abdulaziz University; Consultant in Pulmonary & Sleep Medicine, Director, Sleep Medicine and Research Center, King Abdulaziz University Hospital, PO Box 80215, Jeddah - 21589
Source of Support: None, Conflict of Interest: None
Purpose: Although few previous studies suggested an increased prevalence of obstructive sleep apnea (OSA) among children with sickle cell disease (SCD) compared to others, there are little data regarding this association in adults. In this study, we aimed to investigate the prevalence of OSA among the patients with SCD and its risk factors.
Materials And Methods: This cross-sectional, observational study was conducted at a specialty hematology clinic. From December 2013 to July 2014, all the patients with SCD and chronic anemia were approached. Data were collected on the risk of OSA using the Berlin questionnaire, and the data on daytime sleepiness were collected using the Epworth sleepiness scale (ESS); medical history of the patients was also obtained. The objective diagnosis of OSA using polysomnography was performed in a subsample of the study population.
Results: The study included 106 patients, 44.3% with SCD and 55.7% with other types of anemia being used as a comparison group. Among the patients with SCD, 14.9% were at a high risk of OSA, and 23% were confirmed to have OSA, whereas 10.1% and 16.7% of those in the comparison group did, respectively. However, there were no statistically significant differences between the two groups. Mean scores of risk factors for OSA among the patients with SCD with OSA were 28 years for age, 22.1 kg/m2for body mass index, 14.5 inches for neck circumference, 122 mmHg for systolic blood pressure, and 6.67 for ESS score.
Conclusion: Although not different from chronic anemia, the OSA is a common, coexisting disease in the patients with SCD. Furthermore, it is suspected that the traditional screening tools may miss potential cases of OSA in the SCD population.
Keywords: Anemia, obstructive sleep apnea, polysomnography, prevalence, risk factors, sickle cell disease
|How to cite this article:|
Al-Saqqaf R, Merdad R, Wali SO, Al-Sayes F, Mukharesh L, Batawi S, Batwai G, Ageel M, Hamid M, Alama N, AlQassas I. The prevalence of obstructive sleep apnea in adult patients with sickle cell disease. J Appl Hematol 2017;8:16-22
|How to cite this URL:|
Al-Saqqaf R, Merdad R, Wali SO, Al-Sayes F, Mukharesh L, Batawi S, Batwai G, Ageel M, Hamid M, Alama N, AlQassas I. The prevalence of obstructive sleep apnea in adult patients with sickle cell disease. J Appl Hematol [serial online] 2017 [cited 2020 Nov 25];8:16-22. Available from: https://www.jahjournal.org/text.asp?2017/8/1/16/204424
| Introduction|| |
Obstructive sleep apnea (OSA) is categorized by periodic episodes of apnea and hypopnea during sleep. The Berlin questionnaire (BQ) is used to screen the risk of developing OSA. The pathophysiology behind OSA is now believed to be multifactorial: abnormal nasopharyngeal anatomy, laxity of muscles of the pharynx, increased loop ventilation, and decreased arousal threshold. The prevalence of OSA in the general population differs with respect to gender: 3–7% in men and 2–5% in women.
OSA has been extensively studied in pediatric patients with sickle cell disease (SCD).,,,,, Existing evidence suggests that children with SCD are at an increased risk of disordered breathing during sleep and OSA, which was up to 69% in one report. However, the prevalence of OSA among the adult patients with SCD has not been widely investigated. A recent survey based on a sleep questionnaire revealed that more than 70% of the adult patients with SCD had sleep disturbance. More recently, Sharma et al. reported from a small cohort objective study that 44% of the patients with SCD who referred to the sleep center actually had sleep apnea.
Multiple factors play a role in the development of sleep-disordered breathing at least in children and adolescents; these include higher risk of developing tonsillar hypertrophy and concomitant small upper airway. In addition, the patients with SCD suffer from acute painful crises, neuropathic pain, and chronic pain syndrome leading to poor quality of sleep. It has been suggested that having untreated OSA in the patients with SCD may lead to persistent nocturnal hypoxia with more adverse effects. Hence, identifying and appropriately treating the patients with SCD with OSA may actually reduce the rate of acute crises and the consequent hazards.
Consequently, it is important to explore the prevalence of OSA among this cohort of patients to identify whether individuals with SCD warrant regular screening. We, therefore, aimed in this study to: (1) document the rate of excessive daytime sleepiness (EDS) and OSA, both by a screening tool and by objective diagnosis among the patients with SCD, and to compare it to a group of patients with other chronic anemia, and (2) describe the risk profile and polysomnography (PSG) findings of the patients with SCD at a high risk of OSA, and those who are objectively diagnosed with OSA.
| Materials and Methods|| |
Study design, patients, and ethics
In this cross-sectional, observational, exploratory study, we recruited consecutive patients with SCD and consecutive patients with other types of chronic anemia attending the hematology clinic at King Abdulaziz University Hospital (KAUH). The patients were interviewed between December 2013 and July 2014. Our target population was all consecutive patients with SCD and chronic anemia seen at the clinic during the survey duration. All the patients were interviewed individually; information collected included sociodemographics data, medical history, BQ to assess risk of OSA, and the Epworth sleepiness scale (ESS) to assess daytime sleepiness. In addition, anthropometric measurements, neck circumference (NC), and body mass index (BMI) of all the patients were taken. A confirmatory test for OSA in the form of full PSG level 1 was planned for all high-risk patients and 25% of those with low-risk for OSA. However, 8/13 (61.5%) of high-risk patients and 17/93 (18.3%) of low-risk patients underwent the diagnostic test due to limited funds to support the research.
The patients with SCD who are homozygous for sickle cell hemoglobin (HbSS) and the patients with chronic anemia including thalassemia and anemia of chronic illness were included in the study. The patients less than 18 years of age, the patients with acute respiratory illness, and pregnant women were excluded from the study. All participation was voluntary, and the Ethics Committee at the Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia granted ethics approval.
Risk of OSA was determined by the BQ., The BQ is a reliable and valid tool that is widely used to screen for patients who are at risk for OSA. This tool consists of three categories that assess snoring/sleep cessation during sleep, fatigue during waking hours, and having high blood pressure or high BMI. Respondents were asked to indicate the frequency and characteristics of these symptoms. The scoring system presented by the developers of the tool was used to create a categorical variable reflecting low versus high risk of OSA.
Daytime sleepiness. The level of daytime sleepiness was determined using the ESS., The ESS is a reliable and validated questionnaire that assesses the level of subjective daytime sleepiness by asking the respondent to indicate how likely he or she is to doze off in situations that people experience on a daily basis. For each situation, the respondent chooses an answer on a scale from 0 (would never doze off) to 3 (high chance of dozing). The answers to eight statements are summed up to give each respondent a score reflecting sleep propensity. The range is between 0 and 24, with a higher score indicating a higher level of daytime sleepiness. The ESS is used as a continuous variable in the analysis when indicated, and a categorical variable is created to reflect normal levels of daytime sleepiness (score between 0 and 9) and above average daytime sleepiness (score 10 or above). This categorization is guided by the scoring system used by the developer of the ESS. Above average daytime sleepiness is labeled EDS in this study.
The objective diagnosis of OSA. A level-I overnight PSG test was performed at the Sleep Medicine and Research Center in KAUH, Jeddah, Saudi Arabia to determine the apnea–hypopnea index (AHI) of individuals. OSA is diagnosed based on the American Academy of Sleep Medicine guidelines. A categorical variable reflecting the diagnosis of OSA (no vs. yes) and another variable reflecting severity of OSA were used in the analysis. A score of AHI between 5 and 14 reflects mild OSA, 15–29 reflects moderate OSA, and 30 or more reflects severe OSA. Finally, details of PSG findings for the patients with SCD with and without OSA are presented as continuous variables. These include AHI, average oxygen saturation in mmHg, lowest oxygen saturation in mmHg, percent oxygen below 90 mmHg, and sleep efficiency.
Sex, smoking status (non or ex-smoker vs. smoker), and history of tonsillectomy were all used as categorical variables in the analysis. Age and BMI were used as continuous variables.
SCD and other types of chronic anemia were the basis upon which patients were recruited to the study. These diagnoses were obtained from the electronic system at the hematology clinics at KAUH.
Analysis was performed using STATA version 13 software (StataCorp, College Station, TX, USA). Means and standard deviations (SDs) were presented for continuous variables, and numbers and percentages were presented for categorical variables. The chi-square test and Fisher’s exact test (when expected values in any of the cells were below 5) or t-test were used as appropriate to compare the PSG parameters between the patients with SCD and those with other types of chronic anemia, as well as to compare between those with an OSA diagnosis and those without within the SCD group. Unadjusted and adjusted logistic regression analyses were performed to assess whether a significant association was present among the factors including age, sex, BMI, history of tonsillectomy, and smoking and the odds of being at a high risk of OSA and of having EDS. These analyses were performed and presented for the SCD group and the group of patients with other types of chronic anemia separately. Odds ratios (ORs) with 95% confidence interval (CI) were presented. All the tests were of two-tailed type with a significance value set at 0.05.
| Results|| |
Characteristics of the study population
The number of recruited adult subjects, who were included in the analysis, was 106; among them, 47 (44.3%) were with SCD and 59 (55.7%) were with other types of chronic anemia. The mean age of patients was 30.3 years (SD 10.1; range 18–71); the mean BMI was 22.7 kg/m2 (SD 5.5), with 59.4% being female. A comparison between the patients with SCD and those with other types of chronic anemia is presented in [Table 1]. The two groups were comparable in age, sex, BMI, NC, and smoking status. Systolic blood pressure differed significantly between the two groups, with a mean of 121 mmHg among the patients with SCD and 115 mmHg among the comparison group (P = 0.049). However, both measurements still lie within the normal range. In addition, the significantly more patients with SCD have undergone tonsillectomy (31.7%) compared to those without SCD (10.5%), P = 0.009.
|Table 1: Characteristics of the whole study sample, and a comparison between the patients with SCD and those with other chronic anemia. Continuous variables are presented as mean and standard deviation, and categorical variables are presented as n and percentage. (n = 106)|
Click here to view
The mean ESS score of the study sample was 6.32 (SD 3.89), with a prevalence of EDS (ESS ≥ 10) equal to 9.4% (n = 10). The patients with SCD did not have a significantly higher proportion of EDS compared to the comparison group (8.5 and 10.1%, respectively) [Table 2]. Furthermore, logistic regression analysis revealed that the patients with SCD were not at increased risk of having EDS, compared to those without SCD [Table 3], and the OR was not statistically significant (OR = 0.82, 95% CI 0.22–3.09). After adjusting for significant confounders (age, sex, BMI, smoking, and history of tonsillectomy), the direction of association and lack of significance remained the same (OR = 0.93, 95% CI 0.19–4.66).
|Table 2: The prevalence of EDS, high risk of OSA, and objectively diagnosed OSA by anemia group. (n = 106)|
Click here to view
|Table 3: Unadjusted multivariable logistic regression models of being at high risk of OSA (by Berlin questionnaire) and having excessive daytime sleepiness (by ESS), regressed on a group of independent factors. (n = 106)|
Click here to view
Risk of OSA
On the basis of the BQ categorization, 12.3% (n = 13) of the study patients were at high risk of OSA, with a higher proportion among the patients with SCD (approximately 15%) compared to the comparison group (approximately 10%); the difference, however, was not statistically significant. [Table 4] presents a comparison between low- and high-risk OSA groups among patients with SCD and the comparison group.
|Table 4: The risk profile of SCD and comparison group by BQ group. Means and standard deviations are presented. (n = 106)|
Click here to view
Within the same anemia group, age did not significantly differ between those with low risk and those with high risk of OSA. However, the average age of the patients with SCD with high risk of OSA was 32.3 years, and that of the comparison group was 39.5 years (P = 0.232). As expected, the patients who were at high risk of OSA in both the SCD and comparison group had a significantly higher BMI and ESS score, compared to those with low risk; P < 0.05 in both groups. However, those at high risk for OSA among the SCD group had an average BMI of 25.5 kg/m2, whereas those at high risk in the comparison group had an average BMI of 33.8 kg/m2 (P = 0.050). Although the mean systolic blood pressure measurement was significantly higher for the patients with high-risk OSA within the comparison group (134 mmHg) compared to those with low risk (114 mmHg), P < 0.05, this difference was not seen in the SCD group, as the high risk for patients with OSA had a mean systolic blood pressure of 124 mmHg. The logistic regression analysis performed [Table 3] showed that when compared to those with other types of chronic anemia, the patients with SCD were not at an increased risk of having OSA (OR 1.55, 95% CI 0.48–4.96). Among the entire study sample, significant independent predictors of being at high risk of OSA included BMI (OR 1.24, 95% CI 1.10–1.40), P < 0.001 and NC (OR 1.82, 95% CI 1.06–3.13), P < 0.05. In addition, when compared to those with low risk of OSA, the patients with high risk of OSA had a higher systolic BP (OR 1.04, 95% CI 1.00–1.07), P < 0.05, and had a higher risk of having diabetes mellitus (OR 5.28, 95% CI 1.09–25.5). After adjusting for age, sex, BMI, smoking, and history of tonsillectomy, BMI was the only factor that persisted to show a significant association with being at high risk of OSA. Specifically, a one-unit increase in BMI increased the odds of being at high risk of OSA by approximately 21% (OR 1.21, 95% CI 1.05–1.38), P = 0.006.
Objectively diagnosed OSA, SCD, and other factors
The overall number of patients who were assessed for OSA by full PSG was 25, and comprised 23.6% of the study sample. Among those 25 patients, eight were individuals from the group of 13 patients identified as having a high risk of OSA by the BQ (61.5% of the high risk group). Among this group, the majority did not have OSA (n = 7, 87.5%). In [Table 5], a comparison between the PSG characteristics of individuals with OSA and those without as well as a comparison between traditional risk factors in the two groups is presented. These results are confined for the group of patients with SCD. The AHI, lowest oxygen saturation, and percentage of oxygen below 90 mmHg were all significantly different between the two groups (P < 0.05 for all). However, no significant difference was seen for average oxygen saturation, sleep efficiency, or ESS score. For those diagnosed with OSA (AHI ≥ 5), the average age was 28 years, BMI was 22.1 kg/m2, and systolic blood pressure was 122 mmHg. Except for NC, none of the traditional risk factors for suspecting OSA were significantly higher among the OSA group compared to the group without OSA [Table 5].
|Table 5: A comparison between patients with OSA and those with OSA-free SCD in PSG parameters, ESS, and traditional OSA risk factors. Means and standard deviations are presented. (n = 13)|
Click here to view
| Discussion|| |
In this exploratory study, differences were not noted between the patients with SCD and the comparison group in the prevalence of OSA risk by using a screening tool or in objectively diagnosed OSA by PSG. However, assessing the risk profile of the patients with SCD with OSA showed that this group of patients may potentially deviate from the typical presentation of patients with OSA by having a lower BMI, normal blood pressure measurements, and no EDS as measured by the ESS.
Despite the high prevalence of OSA observed in children with SCD,, which in part may be due to adenotonsillar hypertrophy causing obstruction of the airway during sleep, this remains unclear in the adult population with SCD. There are very limited data that assess the risk of OSA in adult SCD population. In our study, we found that among the 47 patients with SCD enrolled, 14.7% were found to be at high risk of OSA as identified by the BQ, and 23% of the thirteen patients with SCD who underwent PSG had OSA. These proportions are lower than those found in other studies. A cohort study conducted by Sharma et al. reported that 44% of the adult patients with SCD, who were referred to the sleep clinic for the evaluation of EDS, were found to have sleep-disordered breathing. However, the study accompanied with several limitations, which included having a small sample size and a potentially biased sample that over-represented OSA prevalence, as only those who were symptomatic when visiting the sleep clinic were enrolled.
Similarly, a retrospective study using the historical data identified the patients with SCD, who were referred to the sleep laboratory over a 2-year period. Overall, 67% of those patients with SCD were diagnosed with OSA. The risk of OSA was unrelated to obesity, as mean BMI for the patients with SCD with OSA was 16.9 compared to a mean BMI of 22.9 in the patients with SCD with no OSA. Similarly, the profile of the small sample of patients with SCD who were diagnosed objectively for OSA shows that the mean BMI was 22.1, which reflects normal weight. However, the SD is 8.14, which reflects the need for a larger sample to understand whether these findings are a true representation of the weight of the patients with SCD with OSA. Because it has been well-established that obesity is the strongest risk factor for developing OSA among the general adult population, the potentially unique presentation of the patients with SCD suffering from OSA must be taken into consideration.,
Usual clinical suspicion and using traditional screening tools such as the BQ to identify the patients with SCD, who may be at risk of OSA is potentially further challenged by looking at the age, systolic blood pressure, and ESS scores of those, who were diagnosed with OSA in our study. The fact that mean scores of these three factors are all lying within the normal range means that physicians may overlook cases of OSA, and potential cases may be missed. A similar argument was made by Whitesell et al. in their recent study assessing sleep-disordered breathing in adults with SCD. They found that traditional clinical indicators such as obesity, snoring, and sleep complaints were not present in most of the examined SCD adults, who had an AHI of over 5.
It is well-established that one of the long-term complications of OSA in the general population is systemic hypertension., Early evaluation and monitoring of patients with OSA are crucial in the prevention of the long-term debilitating complications. It is then pertinent to understand the implications of a raised mean systolic blood pressure that is within the normal range in the patients with SCD with OSA. Whether those normal ranges still reflect potential cardiovascular compromise is a matter to be assessed. It has been shown that even a mild OSA among the patients with SCD is associated with impaired left ventricular diastolic function and a trend toward reduced 6-min walk test distances.
The main limitation of our study is the sample size, which may have led to miss significant associations even when they truly exist. The gold standard diagnostic test to confirm OSA is an overnight PSG study; unfortunately, our target size of the PSG population was not met, mainly because of the poor patient compliance and acceptance of the procedure. The enrollment of those who visited the hematology clinic may also lead to a selection bias and hence limit generalizability of results. Most of our cases exhibited a mild form of SCD with no reported complications.
However, as the "average" numbers are increasingly being seen as a challenge in providing patient-centered and individualized care, it is being encouraged that researchers report findings even from small number of individuals, because their unique clinical presentations and findings may help guide more individualized clinical practice. In addition, a research study such as ours in combination with other studies can help in generating new study questions to be assessed.
In conclusion, our exploratory study suggests that OSA may be an important disease coexisting in a good proportion of the patients with SCD. In addition, it is suspected that usual clinical criteria and traditional screening tools may miss many potential cases of OSA among this population.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Epstein LJ, Kristo D, Strollo PJ Jr, Friedman N, Malhotra A, Patil SP et al.
Clinical guideline for the evaluation, management and long-term care of obstructive sleep apnea in adults. J Clin Sleep Med 2009;5:263-76.
Chung F, Yegneswaran B, Liao P, Chung SA, Vairavanathan S, Islam S et al.
Validation of the Berlin questionnaire and American Society of Anesthesiologists checklist as screening tools for obstructive sleep apnea in surgical patients. Anesthesiology 2008;108:822-30.
Wellman A, Eckert DJ, Jordan AS, Edwards BA, Passaglia CL, Jackson AC et al.
A method for measuring and modeling the physiological traits causing obstructive sleep apnea. Randomized controlled trial. J Appl Physiol 2011;110:1627-37.
Lurie A. Obstructive sleep apnea in adults: Epidemiology, clinical presentation, and treatment options. Adv Cardiol 2011;46:1-42.
Ambrusko SJ, Gunawardena S, Sakara A, Windsor B, Lanford L, Michelson P et al.
Elevation of tricuspid regurgitant jet velocity, a marker for pulmonary hypertension in children with sickle cell disease. Pediatr Blood Cancer 2006;47:907-13.
Mullin JE, Cooper BP, Kirkham FJ, Rosen CL, Strunk RC, DeBaun MR et al.
Stability of polysomnography for one year and longer in children with sickle cell disease. J Clin Sleep Med 2012;8:535-9.
Needleman JP, Franco ME, Varlotta L, Reber-Brodecki D, Bauer N, Dampier C et al.
Mechanisms of nocturnal oxyhemoglobin desaturation in children and adolescents with sickle cell disease. Pediatr Pulmonol 1999;28:418-22.
Rogers VE, Lewin DS, Winnie GB, Geiger-Brown J. Polysomnographic characteristics of a referred sample of children with sickle cell disease. J Clin Sleep Med 2010;6:374-81.
Salles C, Ramos RT, Daltro C, Barral A, Marinho JM, Matos MA. Prevalence of obstructive sleep apnea in children and adolescents with sickle cell anemia. J Bras Pneumol 2009;35:1075-83.
Spivey JF, Uong EC, Strunk R, Boslaugh SE, DeBaun MR. Low daytime pulse oximetry reading is associated with nocturnal desaturation and obstructive sleep apnea in children with sickle cell anemia. Pediatr Blood Cancer 2008;50:359-62.
Wallen GR, Minniti CP, Krumlauf M, Eckes E, Allen D, Oguhebe A et al.
Sleep disturbance, depression and pain in adults with sickle cell disease. BMC Psychiatry 2014;14:207.
Sharma S, Efird JT, Knupp C, Kadali R, Liles D, Shiue K et al.
Sleep disorders in adult sickle cell patients. J Clin Sleep Med 2015;11:219-23.
Rosen CL, Debaun MR, Strunk RC, Redline S, Seicean S, Craven DI et al.
Obstructive sleep apnea and sickle cell anemia. Pediatrics 2014;134:273-81.
Sun K, Xia Y. New insights into sickle cell disease: A disease of hypoxia. Curr Opin Hematol 2013;20:215-21.
Ahmadi N, Chung SA, Gibbs A, Shapiro CM. The Berlin questionnaire for sleep apnea in a sleep clinic population: Relationship to polysomnographic measurement of respiratory disturbance. Sleep Breath 2008;12:39-45.
Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med 1999;131:485-91.
Johns MW. A new method for measuring daytime sleepiness: The Epworth sleepiness scale. Sleep 1991;14:540-5.
Johns M, Hocking B. Daytime sleepiness and sleep habits of Australian workers. Sleep 1997;20:844-9.
American Academy of Sleep Medicine. International Classification of Sleep Disorders. 3rd ed. Darien: American Academy of Sleep Medicine; 2014.
Eng J, Apergis GA, Fahmy S. Sickle cell disease is a risk factor for obstructive sleep apnea. Chest 2010;138:322A.
Young T, Skatrud J, Peppard PE. Risk factors for obstructive sleep apnea in adults. JAMA 2004;291:2013-6.
Peppard PE, Young T, Barnet JH, Palta M, Hagen EW, Hla KM. Increased prevalence of sleep-disordered breathing in adults. Am J Epidemiol 2013;177:1006-14.
Whitesell PL, Owoyemi PO, Oneal MB, Nouraie AB, Klings ES, Rock TA et al.
Sleep-disordered breathing and nocturnal hypoxemia in young adults with sickle cell disease. Sleep Med 2016;22:47-9.
Peppard PE, Young T, Palta M, Skatrud J. Prospective study of the association between sleep-disordered breathing and hypertension. N Engl J Med 2000;342:1378-84.
Lavie P, Herer P, Hoffstein V. Obstructive sleep apnoea syndrome as a risk factor for hypertension: Population study. BMJ 2000;320:479-82.
Sacristán JA. Patient-centered medicine and patient-oriented research: Improving health outcomes for individual patients. BMC Med Inform Decis Mak 2013;8:13-6.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]