Risk factors for obstructive sleep apnoea in obese children: a systematic review and meta-analysis.

To describe characteristics and surgical and clinical outcomes of obese children with obstructive sleep apnea (OSA). At our institution from 2000 to 2010, 143 obese children with an overnight polysomnography (OPSG) diagnosis of OSA, excluding children with comorbidities, were identified. Relationships between demographics, clinical findings, and the severity of OSA were assessed. Presurgery and postsurgery OPSG indices were compared. We defined cure as an apneahypopnea index (AHI) < 1.5/h on the postsurgery OPSG, and we compared the cure rates of different surgeries. A total of 143 children, median age 12.4 y (interquartile range [IQR] 9.6-14.9) and BMI z-scores 2.8 (IQR 2.6-2.9), were included. Seventy-eight (55%) (Median age 12 y [IQR 9-15]) underwent surgery: 1 had tonsillectomy; 1 tonsillectomy + uvulopharyngopalatoplasty (UPPP); 23 adenotonsillectomy (AT); 27 AT + UPPP; 11 adenoidectomy + UPPP; 8 UPPP; and 7 AT + turbinate trim ± tongue base suspension. Overall, surgery cured 19 children (26%), but AHI improved in the majority of children (p = 0.001). Similarly, the arousal index, PETCO2, and SpO2 nadir improved significantly (p < 0.002, p = 0.019, p < 0.001, respectively). AHI improved significantly in children with mild-to-moderate OSA in comparison to severe OSA (p < 0.001). Children with enlarged tonsils and no history of prior surgery benefitted more often from surgery (p < 0.004 and p = 0.002, respectively). AT was the only surgery reducing the AHI significantly (p = 0.008). Children did not lose weight despite intervention. Adherence with PAP was poor. Surgery improved OPSG indices in the majority of obese children with OSA.

Physical exercise and lifestyle modification are recognized as adjunct therapy for obstructive sleep apnea (OSA) in overweight adults. The objectives of this study were to investigate the effects of long-term physical exercise combined with a balanced diet on sleep architecture, sleep duration, and OSA in adolescents with severe obesity. This interventional study was conducted in a nursing institution. Participants were aged 14.6 ± 1.2 years with obesity (body mass index (BMI) = 40.2 ± 6.5 kg/m2). At admission and at 9 months, participants underwent ambulatory polysomnography and incremental maximal exercise testing to determine cardiorespiratory fitness. Twenty-four subjects completed the study. Analyses were performed on the whole population and on a subgroup of subjects with OSA (OSA-subgroup). OSA, defined as obstructive apnea-hypopnea index (OAHI) ≥ 2 events/h, was diagnosed in 58.3% of the population. OAHI was only associated with fat mass in males (r = .75, P < .05). At 9 months postintervention, weight loss (-11.1 kg, P < .0001) and improved cardiorespiratory fitness (VO2peak: +4.9 mL/min/kg, P < .001) were found in the whole population. Sleep duration was increased (+34 minutes, P < .05) and sleep architecture was changed with an increase of rapid eye movement sleep (+2.5%, P < .05) and a decrease of stage N3 sleep (-3.1%, P < .001). Similar results were found in the OSA subgroup. However, OAHI remained unchanged (P = .18). A combination of supervised aerobic exercise and a balanced diet led to weight loss, improved aerobic capacity, and modified sleep architecture without changes in OSA. A commentary on this article appears in this issue on page 907. Registry: ClinicalTrials.gov, Title: Exercise and Venous Compression on Upper Airway Resistance in Obese Teenagers With OSA (OBESOMAC), URL: https://clinicaltrials.gov/ct2/show/NCT02588469, Identifier: NCT02588469.

We demonstrated differential risk factors for OSA in obese children, which suggest that a different mechanism may be involved in OSA development in preschool and school-age children. Various risk factors have been reported in obese children with OSA owing to the different age and different study design. Obese children have a higher prevalence and severity of obstructive sleep apnea (OSA). OSA risk factors in obese children are affected by different ages and study designs. A differential prevalence and risk factors for obese preschool and school-age children with OSA has been demonstrated.

BackgroundAnthropometric measurements are simple and reachable tools for self-evaluating and screening patients with a high risk of obstructive sleep apnea (OSA). However, the accumulated relationship of obesity on the anthropometric characteristics of OSA is not well understood. The aim of the study was to show the time-dependent trend of OSA patients and compare overall and regional anthropometric between two ethnicities.MethodsA cumulative meta-analysis was performed to assess obesity metrics in patients with and without OSA between Asians and Caucasians. We searched PubMed, Web of Science, Embase, and Scopus up to Jun 2020. Included studies used body mass index (BMI), neck circumference (NC), waist circumference (WC) and waist-to-hip ratio (WHR) as measures of anthropometric features in the adult OSA population and controls, utilized in-lab polysomnography or home sleep testing with apnea-hypopnea index (AHI) or respiratory disturbance index (RDI) classification, reported ethnicity/race, and were published in English. Any studies lacking one of these criteria or sufficient data were excluded.ResultsForty studies with a total of 19,142 subjects were investigated. Comparison of changes between patients with and without OSA showed that OSA patients had a higher BMI [mean difference (MD) 3.12, 95% confidence interval (CI): 2.51–3.73], NC (MD 3.10, 95% CI: 2.70–3.51), WC (MD 9.84, 95% CI: 8.42–11.26) and waist-hip ratio (MD 0.04, 95% CI: 0.03–0.05) than the control subjects. The accumulated time-dependent increase in population with OSA was significantly apparent with all anthropometric features. BMI increased from 2000 (MD 0.50) to 2012 (MD 3.08–3.48) and remained stable afterwards (MD 2.70–3.17), NC increased from 2000 (MD 0.40) to 2013 (MD 3.09) and remained stable afterwards too (MD 3.06–3.21). WC increased from 2000 (MD 2.00) to 2012 (MD 9.37–10.03) and also remained stable afterwards (MD 8.99–9.84). WHR was stable from 2000 to 2004 with an MD of 0.01 and then stable from 2007 onwards with an increased MD of 0.03–0.04. Compared with Caucasian patients, Asian patients had lower obesity relevant variates.ConclusionsBMI, NC, WC and WHR are associated with OSA in both ethnic groups. Anthropometry for overall and regional obesity could facilitate differentiation of patients with OSA from individuals without OSA by ethnicity.

To estimate the frequency of obstructive sleep apnea syndrome (OSAS) in dental patients with tooth wear, and to assess the role of dentists in the identification of patients at risk of OSAS. Dental patients with tooth wear and treated with occlusal splint were prospectively recruited to perform sleep study. The severity of tooth wear was established by the treating dentist before patient referral to sleep disorders unit. Sleep questionnaires, anthropometric measurements, and validated respiratory polygraphy were performed. All patients with dental wear were offered a sleepiness analysis. Of 31 recruited patients, 30 (77% males) participated in this study. Patients' mean age was 58.5 ± 10.7 years (range: 35-90 years) and the body mass index was 27.9 ± 3.4 kg/m(2). Tooth wear was mild in 13 patients, moderate in 8 and severe in 9. The mean apnea-hypopnea index (AHI) was 32.4 ± 24.9. AHI < 5 was reported in 2 patients, AHI of 5-29 in 17, and AHI ≥ 30 in 11. A statistically significant association was found between AHI severity and tooth wear severity (Spearman R = 0.505; p = 0.004). Tooth wear could be a tool to identify those patients at risk of having OSAS. This highlights the importance of dental professionals to identify and refer patients with OSAS.

Management of Snoring.

Opioids are associated with higher risk for ataxic breathing and sleep apnea. We conducted a systematic literature review and meta-analysis to assess the influence of long-term opioid use on the apnea-hypopnea and central apnea indices (AHI and CAI, respectively). A systematic review protocol (Cochrane Handbook guidelines) was developed for the search and analysis. We searched Embase, Medline, ACP Journal Club, and Cochrane Database up to November 2014 for three topics: (1) narcotics, (2) sleep apnea, and (3) apnea-hypopnea index. The outcome of interest was the variation in AHI and CAI in opioid users versus non-users. Two reviewers performed the data search and extraction, and disagreements were resolved by discussion. Results were combined by standardized mean difference using a random effect model, and heterogeneity was tested by χ(2) and presented as I(2) statistics. Seven studies met the inclusion criteria, for a total of 803 patients with obstructive sleep apnea (OSA). We compared 2 outcomes: AHI (320 opioid users and 483 non-users) and 790 patients with CAI (315 opioid users and 475 non-users). The absolute effect size for opioid use was a small increased in apnea measured by AHI = 0.25 (95% CI: 0.02-0.49) and a medium for CAI = 0.45 (95% CI: 0.27-0.63). Effect consistency across studies was calculated, showing moderate heterogeneity at I(2) = 59% and 29% for AHI and CAI, respectively. The meta-analysis results suggest that long-term opioid use in OSA patients has a medium effect on central sleep apnea.

Novel methods to diagnose obstructive sleep apnea in children

Exercise capacity is impaired in obstructive sleep apnea (OSA). There are conflicting reports on the effect of continuous positive airway pressure (CPAP) on maximal exercise capacity. The objective of this review was to determine if there is a change in exercise capacity and anaerobic threshold following CPAP treatment in OSA patients. We conducted a systematic review and meta-analyses to summarize the changes in peak rate of oxygen uptake (V̇O₂ peak) or maximum rate of oxygen uptake (V̇O2 max) and anaerobic threshold (AT) during cardiopulmonary exercise testing following CPAP intervention in patients with OSA. A systematic literature review was conducted to identify published literature on markers of V̇O₂ peak, V̇O₂ max, and AT pre- vs post-CPAP using a web-based literature search of PubMed/MEDLINE, Embase, CINAHL, and Cochrane review (CENTRAL) databases. Two independent reviewers screened the articles for data extraction and analysis. The total search of all the databases returned 470 relevant citations. Following application of eligibility criteria, 6 studies were included in the final meta-analysis for V̇O₂ peak, 2 studies for V̇O₂ max, and five studies for AT. The meta-analysis showed a mean net difference in V̇O₂ peak between pre- and post-CPAP of 2.69 mL·kg-1·min-1, P = .02, favoring treatment with CPAP. There was no difference in V̇O₂ max or AT with CPAP treatment (mean net difference 0.66 mL·kg-1·min-1 [P = .78] and -144.98 mL·min-1 [P = .20] respectively). There is a paucity of high-quality studies investigating the effect of CPAP on exercise capacity. Our meta-analysis shows that V̇O₂ peak increases following CPAP treatment in patients with OSA, but we did not observe any change in V̇O₂ max or AT. Our findings should be considered preliminary and we recommend further randomized controlled trials to confirm our findings and to clarify the peak and maximum rates of oxygen uptake adaptations with CPAP therapy.

The accuracy of obstructive sleep apnea (OSA) screening instruments in seniors may change as the predictive role of sex, age, and body mass index (BMI) changes with aging. We investigated the diagnostic performance of the STOP-BANG questionnaire in older individuals with aging-adapted scores and thresholds. Independent community-dwelling adults aged 65 years or older were screened for OSA. The STOP-BANG questionnaire was tested with different configurations and compared to the apnea-hypopnea index (AHI) obtained from home sleep apnea testing (HSAT). Epworth Sleepiness Scale (ESS) and Athens Insomnia Scale (AIS) were tested as possible supplementary screening criteria. We recruited 458 individuals with a mean age of 71 ± 5 years, 41% men, BMI of 28.5 ± 4.6 kg/m². Mild, moderate, and severe OSA were present in, respectively, 34%, 30%, and 19% of the sample. The STOP questions had an area under the curve (AUC) of the receiver operating characteristic curve significantly lower than the STOP-BANG and the STOP+BMI > 28 kg/m² (STOP-B28). Both STOP-BANG and STOP-B28 had high sensitivity and low specificity in all OSA levels with similar AUC to predict AHI ≥ 5 events/h, 0.64. ESS and AIS were nonsignificant as adjunctive instruments. Novel modifications of a standard instrument created the STOP-B28, a simpler-to-obtain and similarly performing variation of the STOP-BANG using fewer inputs, and useful to exclude OSA. Screening seniors via questionnaires to detect OSA is problematic. Considering the 83% OSA prevalence in this age group, it may be a sensible option to indicate objective tests, oximetry, HSAT, or even polysomnography, as a first step in OSA investigation.

To analyze differences in mandibular cortical width (MCW) among children diagnosed with obstructive sleep apnea (OSA) or at high- or low-risk for OSA. A total of 161 children were assessed: 60 children with polysomnographically diagnosed OSA, 56 children presenting symptoms suggestive of high-risk for OSA, and 45 children at low risk for OSA. Children at high- and low-risk for OSA were evaluated through the Pediatric Sleep Questionnaire. MCW was calculated using ImageJ software from panoramic radiograph images available from all participants. Differences between MCW measurements in the 3 groups were evaluated using analysis of covariance and Bonferroni post-hoc tests, with age as a covariate. The association between MCW and specific cephalometric variables was assessed through regression analysis. The participants' mean age was 9.6 ± 3.1 years (59% male and 41% female). The mean body mass index z-score was 0.62 ± 1.3. The polysomnographically diagnosed OSA group presented smaller MCW than the group at low-risk for OSA (mean difference = -0.385 mm, P = .001), but no difference with the group at high-risk for OSA (polysomnographically diagnosed OSA vs high-risk OSA: P = .085). In addition, the MCW in the group at high-risk for the OSA was significantly smaller than the group at low-risk for the OSA (mean difference = -0.301 mm, P = .014). The cephalometric variables (Sella-Nasion-A point angle (SNA) and Frankfort - Mandibular Plane angle (FMA)) explained only 8% of the variance in MCW. Reductions in MCW appear to be present among children with OSA or those at high-risk for OSA, suggesting potential interactions between mandibular bone development and/or homeostasis and pediatric OSA. Fernandes Fagundes NC, d'Apuzzo F, Perillo L, et al. Potential impact of pediatric obstructive sleep apnea on mandibular cortical width dimensions. J Clin Sleep Med. 2021;17(8):1627-1634.

Obstructive sleep apnea (OSA) is a common disorder in modern society and closely associated with obesity. Because OSA increases the likelihood of complications in the perioperative period, preoperative recognition is very important for bariatric patients. Polysomnography (PSG) remains the gold standard for diagnosis, but it is a time-consuming and expensive examination. Our study is aimed at identifying practical clinical predictors of OSA for bariatric patients. From April 2006 to December 2007, 101 morbid obese patients [41 men and 60 women, mean age 30.3 +/- 8.5, mean body mass index (BMI) 43.3 +/- 6.9] who underwent PSG before bariatric surgery were retrospectively studied. The severity of OSA was categorized by the apnea-hypopnea index (AHI) as follows: normal, 0 to 4.9; mild, 5 to 14.9; moderate, 15 to 29.9; and severe, >/=30. Chi-squared tests and linear regression models were used to assess associations between clinical parameters and AHI; P < 0.05 was considered statistically significant. The mean Epworth sleepiness scale (ESS) score was 8.2 +/- 4.7, and the mean AHI was 28.9 +/- 33.8 per hour. Of 101 patients, 83 patients had OSA; including severe (32.7%), moderate (17.8%), and mild (31.7%) OSA; 18.5% had no OSA. Patients with severe OSA are significantly male predominant and had higher BMI, systolic blood pressure, hemoglobin, neck and waist circumference, and ESS scores. In linear regression model analysis, the parameters which positively correlated with AHI were body weight, BMI, systolic blood pressure, diastolic blood pressure, hemoglobin, waist and neck circumferences, and the scores of ESS. Multivariate analysis confirmed that BMI, neck circumference, and scores of ESS are independent predictors of the increasing of AHI. OSA is highly prevalent (82.2%) in Asian bariatric patients. BMI, neck circumference, and scores of ESS are independent predictors of OSA in these patients.

The purpose of this study is to conduct a systematic review and meta-analysis evaluating the effects of respiratory muscle therapy (ie, oropharyngeal exercises, speech therapy, breathing exercises, wind musical instruments) compared with control therapy or no treatment in improving apnea-hypopnea index ([AHI] primary outcome), sleepiness, and other polysomnographic outcomes for patients diagnosed with obstructive sleep apnea (OSA). Only randomized controlled trials with a placebo therapy or no treatment searched using PubMed, EMBASE, Cochrane, and Web of Science up to November 2018 were included, and assessment of risk of bias was completed using the Cochrane Handbook. Nine studies with 394 adults and children diagnosed with mild to severe OSA were included, all assessed at high risk of bias. Eight of the 9 studies measured AHI and showed a weighted average overall AHI improvement of 39.5% versus baselines after respiratory muscle therapy. Based on our meta-analyses in adult studies, respiratory muscle therapy yielded an improvement in AHI of -7.6 events/h (95% confidence interval [CI] = -11.7 to -3.5; P ≤ .001), apnea index of -4.2 events/h (95% CI = -7.7 to -0.8; P ≤ .016), Epworth Sleepiness Scale of -2.5 of 24 (95% CI= -5.1 to -0.1; P ≤ .066), Pittsburgh Sleep Quality Index of -1.3 of 21 (95% CI= -2.4 to -0.2; P ≤ .026), snoring frequency (P = .044) in intervention groups compared with controls. This systematic review highlights respiratory muscle therapy as an adjunct management for OSA but further studies are needed due to limitations including the nature and small number of studies, heterogeneity of the interventions, and high risk of bias with low quality of evidence.

Most Asian countries have limited resources for polysomnography. Risk factors for Obstructive Sleep Apnea (OSA) in Asian populations may be different from the Western countries. Knowing the physical risk factors for OSA may be a helpful tool for clinicians to select suitable patients to be tested for OSA. We enrolled consecutive OSAsuspected patients between October 1st, 2006 and September 30th, 2007. Physical factors including Body Mass Index (BMI), Neck Circumference (NC), and Waist Circumference (WC) were recorded. The correlations of BMI, NC, WC and Apnea-Hypopnea Index (AHI) were executed. Various cut points of BMI, NC, and WC were calculated for sensitivity and specificity of severity of OSA. During the study period, there were 66 patients enrolled. All three parameters (BMI, NC, and WC) were significantly correlated with AHI. The highest correlation index was between BMI and AHI (0.604), whereas the correlation index of AHI-WC and AHI-NC were 0.571 and 0.440, respectively. Only BMI and WC, but not NC, were significantly related to severity of OSA. The BMI of more than 25 kg/m2 had the highest sensitivity (93.8%) for severe OSA, whereas WC more than 101.8 cm had the highest specificity (92%). In conclusion, BMI, WC, and NC are correlated with AHI in OSA suspected Thai patients. BMI and WC, but not NC, were associated with severity of OSA. In resource-limited facilities, these parameters may be helpful for clinicians to evaluate the risk of OSA more appropriately.

Introduction Type-2 diabetes mellitus is a highly prevalent multisystemic disorder having bidirectional association with Obstructive sleep apnoea. These disorders, when present as co-morbidities, can lead to life-threatening cardiovascular complications. The current prevalence of Obstructive sleep apnoea in Type-2 diabetics is largely unknown, especially in developing nations like India. This study was aimed at determining its prevalence and other risk factors in Type-2 diabetics visiting a tertiary-care hospital in Western India. Methods Adult patients with Type 2 diabetes mellitus visiting the Departments of Pulmonary medicine and Non-communicable diseases on an out-patient basis at a tertiary-care hospital were recruited for the study. Those with unstable medical illnesses or other forms of diabetes were excluded. Participants were interviewed and examined based on a case-study form, including Epworth Sleepiness Scale, STOP-BANG and OSA-50 questionnaires, followed by a Home Sleep Apnoea Test. Apnoea-Hypopnoea Index(AHI) was used to evaluate for Obstructive sleep apnoea. Results A sample of 62 diabetics (median age: 61(16) years; 34 males; 28 females) was analysed. Obstructive sleep apnoea(Apnea-Hypopnea Index [AHI] ≥ 5.0/h) was diagnosed in 55 subjects(88.7%, median AHI – 20.95/h). 62.9% had moderate-to severe Obstructive sleep apnoea(OSA)(AHI ≥ 15/h), 21% had positional OSA and 48.4% had OSA syndrome(OSAS). AHI had significant positive correlation with waist circumference(rho- 0.318, p- 0.012), neck circumference(rho-0.363, p-0.004), Modified Mallampati score(rho-0.372, p-0.003) and Epworth Sleepiness Scale(rho-0.403, p-0.001). No significant association of glycaemic control, duration of Type-2 diabetes and Random Blood Sugar level with AHI was identified. Sensitivity and specificity of STOP-BANG questionnaire for diagnosing OSA was 69.1% and 71.4% and that of OSA-50 questionnaire was 94.5% and 14.3%, respectively. Conclusion Obstructive sleep apnoea(OSA) is more prevalent in adult population with Type-2 diabetes mellitus(T2DM) than in the general population. A high index of suspicion for OSA in patients with T2DM is warranted, because they may not have overt daytime sleepiness or presence of high-risk predictors. Waist and neck circumferences are better predictors of OSA syndrome than body mass index(BMI). Home Sleep Apnoea Test is a more reliable test for OSA detection compared to screening questionnaires and hence can be a useful tool for diagnosis and management planning of OSA in high-burden, low-resource settings. Support (If Any)