The aim was to validate a new seven‐item “TASC” (Trøndelag Apnoea Score) proxy for obstructive sleep apnoea (OSA) against polysomnography in the general population. Objectives included validation against different polysomnographic criteria, stratification by age and gender, and estimation of OSA prevalence. From the fourth wave of the Trøndelag Health Study (HUNT4), 1,201 participants were randomly invited to a substudy focusing on sleep and headaches, of whom 232 accepted and 84 (64% women, mean age 55.0 years, and standard deviation 11.5 years) underwent polysomnography. The TASC proxy sums seven binary items for snoring, observed breathing pauses, restricted daytime activities, hypertension, body mass index (≥30 kg/m2), age (≥50 years), and gender (male). A single night of ambulatory (home) polysomnography was analysed using both the recommended and optional hypopnoea criteria of the American Academy of Sleep Medicine (AASM). We found 65% sensitivity and 87% specificity (Cohen’s κ = 0.53, 95% confidence interval 0.34−0.72) for TASC ≥ 3 against AHI ≥ 15 (recommended AASM criteria). Validity was similar against AHI ≥ 30 but lower against AHI ≥ 5 and against the optional AASM criteria. Sensitivity and overall validity were higher among men and those above 50 years of age. The prevalence of an apnoea‐hypopnoea index (AHI) of at least 5, 15, or 30 using the recommended (and optional) AASM criteria was 73% (46%), 37% (18%), or 15% (5%). A seven‐item TASC proxy for OSA showed good validity and may be useful in screening and epidemiological settings. Sensitivity, specificity, and validity vary considerably by cut‐off, by polysomnographic scoring criteria, and by gender and age strata.
Background. This study is aimed at determining the quality of life, mental health, and adherence to continuous positive airway pressure (CPAP) therapy for obstructive sleep apnea (OSA) among Thai OSA patients during the coronavirus disease 2019 (COVID-19) pandemic as this data has been lacking. Methods. A cross-sectional study was conducted at a university hospital between September 2021 and April 2022. OSA patients aged 18 years or older who required home CPAP treatment were included. Sleep Apnea Quality of Life Index (SAQLI) and Depression Anxiety Stress Scales-21 (DASS-21) were used to assess quality of life and mental health, respectively. Results. A total of 142 participants (62% male) were included, with a mean age of 54.4±14.7 years and a body mass index of 29.9±6.8 kg/m2. Polysomnographic data showed a mean apnea-hypopnea index of 48.0±32.4 events/hour and a mean lowest oxygen saturation of 79.2±12.2%. Severe OSA was observed in 66.9%. CPAP compliance was reported in 50.7%. The SAQLI score was 2.32±1.12. Depression, anxiety, and stress scores in DASS-21 were 2.89±3.31, 3.94±3.67, and 4.82±4.00, respectively. Compared to the CPAP compliance group, the CPAP noncompliance group had higher daily activity scores in SAQLI (2.98±1.25 vs. 2.45±1.33, P=0.015). Conclusions. The quality of life for Thai OSA patients during the COVID-19 era was moderate degree. Poor CPAP compliance was significantly associated with limited daily activity. Enhancing CPAP compliance could improve the quality of life in these patients. This trial is registered with TCTR20211104004.
Perioperative sleep disturbances may impact healing and negatively affect the patient's perception of well-being. Therefore, accurately assessing postoperative sleep characteristics is necessary to treat sleep disturbances. This study is a secondary data analysis of research investigating the association between sleep and cognition in a perioperative setting. This study compares sleep characteristics between the St. Mary's Hospital Sleep Questionnaire and WatchPAT, a portable sleep apnea testing device. The goal of this study is to compare an objective measurement of sleep quality (WatchPAT) with a traditional questionnaire. One hundred and one patients who underwent elective, noncardiac surgical procedures wore a WatchPAT and completed the St. Mary's Hospital Sleep Questionnaire for three nights: two preoperative and one postoperative night. In the preoperative period, a Bland-Altman analysis showed an agreement Watch PAT and the St Mary's hospital sleep questionnaire except for sleep fragmentation. A good to fair correlation during the preoperative period was observed with both sleep latency and total sleep time. In the postoperative period, no correlation was observed between the St. Mary's Hospital Sleep Questionnaire data and WatchPAT data. Our study indicates that some potential factors affecting sleep and cognition such as admission type, depression, anesthesia type, and sleep apnea may limit patients' ability to report their sleep characteristics after surgery. Therefore, relying solely on one sleep assessment method is not advisable.
Obstructive sleep apnea (OSA) pathologically stresses the cardiovascular system. Apneic events cause significant oscillatory surges in nocturnal blood pressure (BP). Trajectories of these surges vary widely. This variability challenges the quantification, characterization, and mathematical modeling of BP surge dynamics. We present a method of aggregating trajectories of apnea-induced BP surges using a sample-by-sample averaging of continuously recorded BP. We applied the method to recordings of overnight BP (average total sleep time: 4.77 ± 1.64 h) for 10 OSA patients (mean AHI: 63.5 events/h; range: 18.3-105.4). We studied surges in blood pressure due to obstructive respiratory events separated from other such events by at least 30 s (274 total events). These events increased systolic (SBP) and diastolic (DBP) BP by 19 ± 7.1 mmHg (14.8%) and 11 ± 5.6 mmHg (15.5%), respectively, relative to mean values during wakefulness. Further, aggregated SBP and DBP peaks occurred on average 9 s and 9.5 s after apnea events, respectively. Interestingly, the amplitude of the SBP and DBP peaks varied across sleep stages, with mean peak ranging from 128.8 ± 12.4 to 166.1 ± 15.5 mmHg for SBP and from 63.1 ± 8.2 to 84.2 ± 9.4 mmHg for DBP. The aggregation method provides a high level of granularity in quantifying BP oscillations from OSA events and may be useful in modeling autonomic nervous system responses to OSA-induced stresses.
Aim . This study aimed to determine the association between quality of sleep and metabolic syndrome (MetS) and physical activity level in young adults at the University of Ghana. Method . In a cross-sectional design, 340 university students, aged between 20-30 years were recruited. Quality of sleep was assessed using the Pittsburgh Sleep Quality index (PSQI) and physical activity with the short form of the International Physical Activity Questionnaire (IPAQ-SF). Poor quality of sleep was defined as a global PSQI score>5 and low physical activity level as those not meeting the criteria for vigorous-moderate physical activity. Anthropometric features and blood pressures were measured, and fasting blood samples were collected from the participants to measure plasma levels of glucose, lipid profile, urea, and creatinine. MetS was defined using the Joint Scientific Statement criteria. Results . In our study population of young adults from Ghana, the prevalence of poor quality of sleep as measured by PSQI was 54.1%, and MetS was 12.4%. MetS was associated with poor quality of sleep in females [OR (95 % CI) = 2.11 (1.04–4.25), p = 0.038] and entire study participants [2.18 (1.09–4.37) p = 0.029] in both crude and adjusted models; no association was found in male participants. Low physical activity status was not associated with poor sleep status. Obesity [1.32 (1.02–3.56), p = 0.043], but not overweight [0.99 (0.58–2.34), p = 0.862], was associated with poor quality of sleep. Conclusion . Young adults in a Ghanaian university have a high prevalence of poor quality of sleep and is associated with MetS and obesity. Physical activity status was not associated with poor quality of sleep.
Purpose:To determine the prevalence of central apnea (CA) events and central sleep apnea (CSA) in children with sleep-disordered breathing (SDB) and to assess the effect of tonsillectomy and adenoidectomy (TA) on CSA in children with obstructive sleep apnea (OSA). Material and Methods. The medical charts of children with SDB were reviewed to obtain information on past medical history, polysomnography (PSG) findings, and surgical management. Counts and indexes of obstructive apnea, obstructive hypopnea, and central apnea were evaluated before and after TA. The prevalence of CSA and the effect of age, gender, obesity, and comorbid conditions on CSA were assessed in children with SDB as well as in children with PSG proven OSA.Results:Seven hundred twelve children with SDB (age range: 1 to 18 yrs, mean: 5.8 ± 3.4) were identified. CA events occurred in 640 of 712 (89.5%) patients. Of the 712 patients, 315 (44.2%) met the criteria for the diagnosis of CSA. CSA was more prevalent in toddlers and preschoolers (p < 0.001). Obese children had a higher prevalence of CSA compared to nonobese children (p < 0.001). The prevalence of CSA in patients with OSA was 45.4%. The number of CA events, CAI, and OAHI after TA was less than that of before TA (p < 0.001). Residual CSA after TA occurred in 20 children (26%).Conclusion:Central apnea events and central sleep apnea occur in children who present to a pediatric otolaryngology clinic for evaluation of sleep disordered breathing. Central sleep apnea and obstructive sleep apnea both improve after tonsillectomy and adenoidectomy.
Background and Objective. Patients with cardiovascular problems experience sleep disorders. Due to the importance of adequate sleep and rest for the growth and repair of damaged cells, it is necessary to use appropriate interventions to improve it. This study determined the effect of sleep intervention programs during cardiac rehabilitation on patients’ sleep quality. Materials and Methods. In this quasi-experimental study with unequal control group design, 35 individuals participated in the cardiac rehabilitation program as the experimental group and 35 served as the control group. The program included 12 weeks of exercise, 3 sessions per week, 3 sessions of training programs each lasting for 45 minutes, and a special two-session sleep improvement program. Data were collected using the Pittsburgh Sleep Quality Index and analysed with descriptive and inferential statistical methods. Results. There were not any significant differences between the two groups in age, sex, marital status, smoking, and indication for cardiac rehabilitation (P>0.05). The scores of sleep quality of patients were 9.2±1.58 before and 4.40±1.14 after intervention in the experimental group and 9.02±2.56 before and 7.48±1.86 after intervention in the control group. There was no significant difference between the two groups before intervention (P=0.73). yet there was a significant difference after intervention (P=0.0001). In addition, scores of sleep quality of patients were significantly different in the experimental and control groups before and after intervention (P=0.0001). Conclusion. Findings indicated that the quality of sleep of cardiac patients improved after the sleep intervention program during the cardiac rehabilitation program. Therefore, it is suggested to implement sleep improvement programs for cardiac patient care as an effective, easy, and feasible technique. In addition, it is necessary to pay more attention to the sleep improvement program in cardiac rehabilitation. Trial Registration. The trial was retrospectively registered on https://en.irct.ir/trial/50799 on 14 September 2020 (14.09.2020) with registration number IRCT20140307016870N6.
Background. Assessing sleep disorders and understanding their causes are essential for the proper treatment and management of the disorders. The Holland Sleep Disorders Questionnaire (HSDQ) is a self-assessment questionnaire that measures sleep problems and symptoms based on the six categories of sleep disorders described in the International Classification of Sleep Disorders-2 (ICSD-2). The aim of this study was at validating and assessing the psychometric properties of the HSDQ in Iranian adults. Method. The study was carried out as a methodological and validation work. The guidelines for translation and cultural adaptation of patient-reported outcome measures were followed for the translation and the cultural validation of the tool. To examine construct validity, exploratory factor analysis (EFA) with 216 participants and confirmatory factor analysis (CFA) with 355 participants were used. As to the reliability, the test-retest method and, as to internal consistency, Cronbach’s alpha were employed. Data analyses were done in SPSS-25 and LISREL-8. Results. The CFA and EFA results confirmed the tool with six factors and 31 items. The R 2 index of the model was 0.99, which indicated that 99% of changes in the dependent variable (adults’ sleep problem) were attributed to the independent variable (the 31 items). In other words, 0.99 of the changes in the dependent variable were due to the independent variables. The main indices of CFA ( χ 2 / DF = 2.65 , CFI = 0.91 NNFI / TLI = 0.92 GFI = 0.81 , REMSEA = 0.043 , R 2 = 0.99 ) were acceptable. In addition, a correlation coefficient below 0.05 was considered as significant. Reliability of the tool based on internal correlation (Cronbach’s alpha) was in the 0.701–0.924 range for the subscales and equal to 0.789 for the whole tool. Conclusion. In general, the results showed that the Farsi version of HSDQ (six factors and 31 items) had acceptable and applicable indices and it can be used as a valid tool in the Iranian society. The tool can be used as a reliable tool in different fields of medical sciences.
Introduction:Sleep disorders are extremely prevalent in the general population. College students are more susceptible to sleep problems. This is due to the increased competition in getting a job position and the current alterations in the labor market. Poor sleep is prevalent and has deleterious effects on college students, but its frequency among college students has not been documented in Jordan. So, the aims of this study are to assess the prevalence of daytime sleepiness among medical college students in Jordan and to look for any links between daytime sleepiness and academic performance.Methods:A cross-sectional study performed on medical and paramedical specialties students and Epworth sleepiness Sscale (ESS) was used. To assess the students' academic performance, the cumulative grade point average was utilized.Results:977 students from five medical colleges participated in the study. ESS scores were abnormal in 34.4% of students and were considered to have daytime sleepiness. Significant lower ESS scores were associated with students who reported good sleep quality than students who reported poor sleep quality. Significant lower ESS scores were reported by students who slept more than 7 hours compared with students who slept less than 6 hours. The ESS scores were not significantly associated with students' CPGA.Conclusion:Daytime sleepiness is highly prevalent among medical students in Jordan. The data of this study might be very helpful to assess the academic policy makers to develop intervention strategies that resolve the sleep disturbances in college students and reduce its impact on the academic achievements.
Background. Acute hypercapnic respiratory failure (AHRF) is a common life-threatening event in patients with obesity hypoventilation syndrome (OHS). Objectives. To study the clinical pattern, noninvasive ventilatory support, as well as the short- and long-term outcomes of patients with OHS admitted in a ward because of AHRF. Methods. We conducted a retrospective cohort study including all adults with OHS aged≥18−year−old, admitted in a 90-bed-ward for AHRF. Results. A total of 44 patients were included. Fifteen (34.1%) and 29 (65.9%) patients were diagnosed with malignant OHS (mOHS) and nonmalignant OHS (non-mOHS), respectively, while 36 (81.8%) had coexisting obstructive sleep apnea hypopnea syndrome (OSAHS). Patients with mOHS had a significantly higher rate of heart failure (100% vs. 31%; p<0.001), chronic renal insufficiency (CRI) (73.3% vs. 41.4%; p=0.04), and dyslipidemia (66.7% vs. 34.5%; p=0.04) than those with non-mOHS. The mean forced vital capacity (FVC) in our patients was of 59.5%±18.5 of the predicted value, lower than what is usually reported in stable patients with OHS. At hospital admission, more than two-thirds (n=34, 77.3%) were misdiagnosed as having asthma exacerbation (n=4, 4.9.1%), chronic obstructive pulmonary disease (COPD) exacerbation (n=12, 27.3%) and/or heart failure (n=29, 65.9%). Acute pulmonary oedema (ACPE) (n=16, 36.4%) and acute viral bronchitis (n=12, 27.3%) were the main identified causal factors, while no cause could be determined in 5 (11.4%) patients. Noninvasive positive pressure ventilation (NIPPV) using bilevel positive airway pressure (BIPAP) was very highly effective to treat AHRF, with only 2.27% of patients failing the modality. Median overall duration of ventilation was 9 hours per day (1.3–20) and was significantly longer in patients with mOHS than in those with non-mOHS (10 [6–18] vs. 8 [1.3–20], respectively; p=0.01). Forty two of the forty-three patients discharged alive were treated with BIPAP or continuous positive airway pressure (CPAP) in 26 and 16 patients, respectively. The probability of survival was 90% at 12 months, while the probability of readmission for a new episode of AHRF was 56% at 6 months and 22% at 12 months, respectively. Conclusion. AHRF in OHS patients is a life-threatening event which can be successfully and safely treated with BIPAP, with a low long-term mortality even in patients with mOHS.
Poor sleep quality has been reported to be common amongst medical students and healthcare professionals worldwide. Sleep disturbance has been associated with increased rates of burnout and depression. As a result, this has been negatively impacting performance and functioning. Research on this topic is limited in the United Arab Emirates (UAE). This study is aimed at exploring sleep pattern and the emotional state of medical and dental students in Dubai, UAE. This cross-sectional study was based on an electronic survey sent to 181 medical and dental students. Of the 181 invitations, 96 individuals agreed to participate and complete the rating scales. The Pittsburgh Sleep Quality Index was utilized to explore sleep duration, quality, and daytime functioning. The Positive and Negative Affect Scale was used to assess the emotional states of the participants. Overall, the findings revealed diminished sleep duration. The average duration of sleep amongst the study participants was 5 hours and 24 minutes, which is significantly below the recommended duration as per sleep guidelines. Results also showed a significant positive correlation between total sleep duration and overall sleep quality with enthusiasm during the day. Future research designed to explore factors contributing to sleep efficiency, in more depth, as well as strategies to enhance sleep quality is highly warranted.
Background . Sleep apnea syndrome (SAS), a growing public health threat, is an emerging condition in sub-Saharan Africa (SSA). Related SSA studies have so far used an incomplete definition. This study is aimed at assessing SAS using an American Academy of Sleep Medicine (AASM) complete definition and at exploring its relationship with comorbidities, among patients hospitalized in a Cameroonian tertiary hospital. Methods . This cross-sectional study was conducted in cardiology, endocrinology, and neurology departments of the Yaoundé Central Hospital. Patients aged 21 and above were consecutively invited, and some of them were randomly selected to undergo a full night record using a portable sleep monitoring device, to diagnose sleep-disordered breathing (SDB). SAS was defined as an apnea − hypopnea index (AHI) ≥ 5/h, associated with either excessive daytime sleepiness or at least 3 compatible symptoms. Moderate to severe SAS (MS-SAS) stood for an AHI ≥ 15/h. We used chi-square or Fisher tests to compare SAS and non-SAS groups. Findings . One hundred and eleven patients presented a valid sleep monitoring report. Their mean age ± standard deviation (range) was 58 ± 12.5 (28–87) years, and 53.2% were female. The prevalence (95% confident interval (CI)) of SAS was 55.0 (45.7, 64.2)% and the one of MS-SAS 34.2 (25.4, 43.1)%. The obstructive pattern (90.2% of SAS and 86.8% of MS-SAS) was predominant. The prevalence of SAS among specific comorbidities ranged from 52.2% to 75.0%. Compared to SAS free patients, more SAS patients presented with hypertension (75.4% vs. 48.0%, p = 0.005 % ), history of stroke (36.7% vs. 32.0%, p = 0.756), cardiac failure (23.0% vs. 12.0%, p = 0.213), and combined cardiovascular comorbidity (80.3% vs. 52.0%, p = 0.003). Similar results were observed for MS-SAS. Metabolic and neuropsychiatric comorbidities did not differ between SAS and SAS-free patients. Conclusion . The SAS diagnosed using modified AASM definition showed high prevalence among patients hospitalized for acute medical conditions, as it was found with SDB. Unlike HIV infection, metabolic and brain conditions, cardiovascular comorbidities (hypertension and cardiac failure) were significantly more prevalent in SAS patients.
Study Objective. This study is aimed at figuring out the role of abnormal sleep duration in predicting cardiovascular diseases. Methods. We searched the online database PubMed on 30 August 2020 for our data collection. We used the following keywords: sleep duration AND (cardiovascular disease OR cardiovascular event) AND (cohort OR prospective OR retrospective). We identified 653 studies, and after excluding studies that were published before 2015, we obtained 306 studies. After filtering the 306 studies through title and abstract screening and applying the inclusion and exclusion criteria, we further reviewed fourteen studies with full-text reading. We excluded three studies because of insufficient data required and included eleven studies in this systematic review. Results. A total of 361,041 participants from ten studies were included in this systematic review. The incidence of hypertension, myocardial infarction, coronary artery disease, heart failure, cardiovascular events, and cardiovascular diseases in the short sleep duration group is 46.12%, 0.59%, 5.43%, 0.09%, 7.18%, 1.48%, and 6.8%, consecutively, while the incidence of hypertension, myocardial infarction, coronary artery disease, and heart failure in the long sleep duration group is 30.71%, 0.61%, 6.55%, 1.11%, and 6.04%, consecutively. Nine studies reported an association between sleep duration and cardiovascular diseases while one study reported no association. Seven studies reported that short sleep duration was significantly associated with CVD. Short sleep duration in this study was associated with hypertension and heart failure. Atrial fibrillation and coronary artery disease were associated with both short and long sleep duration. Conclusion. Abnormal sleep duration (short and long sleep duration) may act as the predictor of cardiovascular diseases. The importance of having normal sleep duration should be stressed with other lifestyle modification to avoid the risk of getting cardiovascular diseases. However, further studies are needed to overcome the limitation of this systematic review.
Periodic limb movement disorder (PLMD) involves repetitive episodes of muscle movements that usually occur in the legs. These movements are described as jerking motions or an upward flexion of the feet. PLMD is considered a sleep disorder when these movements disrupt sleep and lead to symptoms such as daytime sleepiness or behavioral issues. Most children and adolescents with this condition are unaware of the movements taking place. The exact cause of the disorder is unknown. Periodic limb movements in sleep can be seen in conditions such as restless leg syndrome and narcolepsy. In addition to history, overnight polysomnography is used to diagnose PLMD. Certain laboratory studies are also sometimes ordered to check for metabolic abnormalities that may be contributing to PLMD. Treatment usually involves avoidance of triggers such as caffeine, behavioral interventions, and/or treatment of nutritional deficiencies. Certain medications may also be used for refractory cases.
Obstructive sleep apnea affects up to 38% of the general population, and up to 49% of patients in the advanced age groups. According to recent prevalence estimates, moderate to severe OSA may be present in 6–17% of the population. Despite prevalence estimates that resemble those of diabetes mellitus, it remains underdiagnosed and undertreated. It is highly likely providers will care for patients with sleep-related breathing disorders during their practice. This chapter reviews, through clinical cases and short clinical vignettes, disorders commonly encountered in clinical practice. Moderate to severe untreated OSA increases morbidity and mortality and is costly. Benefits of screening with questionnaires such as STOP-Bang remain unknown, but providers should identify common symptoms such as snoring, nonrestorative sleep, and choking or gasping from sleep as an indication for further evaluation (home sleep apnea testing or polysomnography), referral to sleep center, and treatment, of which continuous positive airway pressure (CPAP) is considered first line in most patients. Additional challenges, diagnostic approaches, and treatments options are reviewed for sleep-related breathing disorders including treatment-emergent central sleep apnea (previously known as complex sleep apnea), central sleep apnea with Cheyne-Stokes breathing, central sleep apnea due to a medication or substance and obesity hypoventilation syndromes. We hope for the healthcare provider to feel comfortable screening for these disorders, recommending common diagnostic approaches and treatments, and recognizing associated medical comorbidities. The following cases are meant to demonstrate common presentations and clinical pearls to consider when approaching patients in the clinic.
Part A Sleep disordered breathing (SDB) is increasingly recognized as a presenting or major comorbid diagnosis in hospitalized patients. However, there is no clear guidance on indications for inpatient sleep medicine consultation, SDB evaluation in inpatient versus outpatient setting, or optimal timing and type of positive airway pressure (PAP) treatment to be provided. Figure 8.1 gives an algorithmic approach to inpatient sleep medicine. Variations in the availability of diagnostic tests such as inpatient sleep test and pulmonary function test, and insurance coverage of PAP devices upon discharge are potential factors that limit standardized recommendations. Observational studies show that SDB is associated with increased risk for in-hospital and post-discharge adverse outcomes and compliance with PAP therapy decreases this risk. In particular, specific subgroups of patients may benefit from intervention during hospitalization, including (1) chronic respiratory failure due to severe lung disease such as chronic obstructive pulmonary disease, (2) chronic respiratory failure due to neuromuscular or thoracic cage disease, and (3) SDB in heart failure or postoperative individuals. However, the benefits of inpatient consultation on patients’ outcomes are yet to be determined.
Telemedicine is emerging as key healthcare delivery method in management of patients with limited healthcare access, particularly in the wake of the coronavirus pandemic. As sleep medicine is technology driven to begin with, it translates well to telemedicine-based patient care. A wide variety of sleep disorders can be evaluated, diagnosed, and managed via telemedicine, while maintaining the highest quality of patient care. This chapter presents two common sleep complaints as telemedicine cases, sleep-disordered breathing and insomnia. Although these complaints are common, they require a special approach via telemedicine. The challenges and pitfalls of these cases are discussed, as well as the distinct advantages of telemedicine in such scenarios. Additionally, clinical pearls are offered regarding the practice of sleep telemedicine, based on available evidence and guidelines.
Snoring is a common pediatric disorder and one that should be screened for in all children at every well child visit, as it can be a symptom of obstructive sleep apnea (OSA). Obstructive sleep apnea can trigger an inflammatory cascade that can lead to neurocognitive aberrations and metabolic syndrome. Clinically noted symptoms of obstructive sleep apnea are many and can include labored breathing, snoring, nocturnal diaphoresis, and restless sleep. Less commonly recognized symptoms include impaired attention and concentration, hyperactivity, and poor school performance. OSA severity is based on the frequency of apneas and hypopneas averaged per hour of sleep with more moderate to severe sleep apnea causing more severe symptoms and prompting more aggressive intervention. Obstructive sleep apnea is traditionally treated by either intranasal corticosteroids/leukotriene receptor antagonist therapy, adenotonsillectomy, or positive airway pressure. Treatment of obstructive sleep apnea can result in resolution of the negative neurocognitive and health outcomes associated with pediatric sleep apnea.
