Independent relationship between sleep apnea-specific hypoxic burden and glucolipid metabolism disorder: a cross-sectional study.

OBJECTIVES: Obstructive sleep apnea (OSA) is associated with abnormal glucose and lipid metabolism. However, whether there is an independent association between Sleep Apnea-Specific Hypoxic Burden (SASHB) and glycolipid metabolism disorders in patients with OSA is unknown. METHODS: We enrolled 2,173 participants with suspected OSA from January 2019 to July 2023 in this study. Polysomnographic variables, biochemical indicators, and physical measurements were collected from each participant. Multiple linear regression analyses were used to evaluate independent associations between SASHB, AHI, CT90 and glucose as well as lipid profile. Furthermore, logistic regressions were used to determine the odds ratios (ORs) for abnormal glucose and lipid metabolism across various SASHB, AHI, CT90 quartiles. RESULTS: The SASHB was independently associated with fasting blood glucose (FBG) (ß = 0.058, P = 0.016), fasting insulin (FIN) (ß = 0.073, P < 0.001), homeostasis model assessment of insulin resistance (HOMA-IR) (ß = 0.058, P = 0.011), total cholesterol (TC) (ß = 0.100, P < 0.001), total triglycerides (TG) (ß = 0.063, P = 0.011), low-density lipoprotein cholesterol (LDL-C) (ß = 0.075, P = 0.003), apolipoprotein A-I (apoA-I) (ß = 0.051, P = 0.049), apolipoprotein B (apoB) (ß = 0.136, P < 0.001), apolipoprotein E (apoE) (ß = 0.088, P < 0.001) after adjustments for confounding factors. Furthermore, the ORs for hyperinsulinemia across the higher SASHB quartiles were 1.527, 1.545, and 2.024 respectively, compared with the lowest quartile (P < 0.001 for a linear trend); the ORs for hyper-total cholesterolemia across the higher SASHB quartiles were 1.762, 1.998, and 2.708, compared with the lowest quartile (P < 0.001 for a linear trend) and the ORs for hyper-LDL cholesterolemia across the higher SASHB quartiles were 1.663, 1.695, and 2.316, compared with the lowest quartile (P < 0.001 for a linear trend). Notably, the ORs for hyper-triglyceridemia{1.471, 1.773, 2.099} and abnormal HOMA-IR{1.510, 1.492, 1.937} maintained a consistent trend across the SASHB quartiles. CONCLUSIONS: We found SASHB was independently associated with hyperinsulinemia, abnormal HOMA-IR, hyper-total cholesterolemia, hyper-triglyceridemia and hyper-LDL cholesterolemia in Chinese Han population. Further prospective studies are needed to confirm that SASHB can be used as a predictor of abnormal glycolipid metabolism disorders in patients with OSA. TRIAL REGISTRATION: ChiCTR1900025714 { http://www.chictr.org.cn/ }; Prospectively registered on 6 September 2019; China.

Genome-Wide Association Study of Obstructive Sleep Apnea and Objective Sleep-related Traits Identifies Novel Risk Loci in Han Chinese Individuals.

Rationale: Previous genetic studies of obstructive sleep apnea (OSA) have limitations in terms of precise case definition, integrated quantitative traits, and interpretation of genetic functions; thus, the heritability of OSA remains poorly explained. Objectives: To identify novel genetic variants associated with OSA and objective sleep-related traits and to explore their functional roles. Methods: A genome-wide association study was performed in 20,590 Han Chinese individuals (5,438 OSA and 15,152 control samples). Human samples and point mutation knockin mice were used for follow-up investigation of gene functions. Measurements and Main Results: Two characteristic study-wide significant loci (P < 2.63 × 10-9) for OSA were identified: the PACRG intronic variant rs6455893 on 6q26 (odds ratio [OR] = 1.62; 95% confidence interval [CI], 1.39-1.89; P = 6.98 × 10-10) and the missense variant rs3746804 (p.Pro267Leu) in the riboflavin transporter SLC52A3 on 20p13 (OR = 0.83; 95% CI, 0.79-0.88; P = 7.57 × 10-10). In addition, 18 genome-wide significant loci associated with quantitative OSA and objective sleep-related traits were identified, 5 of which exceeded the study-wide significance threshold. Rs3746804 was associated with elevated serum riboflavin concentrations, and the corresponding mutation in mice increased riboflavin concentrations, suggesting that this variant may facilitate riboflavin uptake and riboflavin-dependent physiological activity. Conclusions: We identified several novel genome-wide significant loci associated with OSA and objective sleep-related traits. Our findings provide insight into the genetic architecture of OSA and suggest that SLC52A3 might be a therapeutic target, whereas riboflavin might be a therapeutic agent.

Prevalence, characteristics, and respiratory arousal threshold of positional obstructive sleep apnea in China: a large scale study from Shanghai Sleep Health Study cohort.

PURPOSE: To evaluate the prevalence, characteristics, and respiratory arousal threshold (ArTH) of Chinese patients with positional obstructive sleep apnea (POSA) according to the Cartwright Classification (CC) and Amsterdam Positional Obstructive Sleep Apnea Classification (APOC). METHODS: A large-scale cross-sectional study was conducted in our sleep center from 2007 to 2018 to analyze the clinical and polysomnography (PSG) data of Chinese POSA patients. Low ArTH was defined based on PSG indices. RESULTS: Of 5,748 OSA patients, 36.80% met the CC criteria, and 42.88% the APOC criteria, for POSA. The prevalence of POSA was significantly higher in women than men (40.21% and 46.52% vs. 36.13% and 42.18% for CC and APOC, respectively). Chinese POSA patients had a lower apnea hypopnea index (AHI) and lower oxygen desaturation index, shorter duration of oxygen saturation (SaO2) < 90%, and a higher mean SaO2 and higher lowest SaO2 value compared to subjects with non-positional OSA (NPOSA). More than 40% of the POSA patients had a low ArTH; the proportion was extremely high in the supine-isolated-POSA (si-POSA) group and APOC I group. In multivariate logistic regression analyses, higher mean SaO2 and lower AHI during sleep were positive predictors of POSA. CONCLUSIONS: According to the CC and APOC criteria, more than 1/3 of our Chinese subjects with OSA had POSA. Chinese POSA patients had less severe OSA and nocturnal hypoxia. Compared to NPOSA patients, significantly more patients with POSA had a low ArTH. A low ArTH may be an important endotype in the pathogenesis of POSA, especially in patients with si-POSA and APOC I. Further studies are necessary to develop personalized management strategies for POSA patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry; URL: http://www.chictr.org.cn ; No. ChiCTR1900025714 (retrospectively registered).

Risk factors for non-positional obstructive sleep apnea-hypopnea syndrome.

OBJECTIVE: To explore the main risk factors for non-positional obstructive sleep apnea (NPOSA). METHODS: A total of 560 patients with obstructive sleep apnea-hypopnea syndrome (OSAHS) were divided into non-positional obstructive sleep apnea (NPOSA) and positional obstructive sleep apnea (POSA) groups. All patients were assessed by the Friedman staging system and anthropometry before overnight polysomnography. Blood tests were performed to determine the fasting blood glucose level and lipid profile. Forward logistic regression analysis was performed to evaluate the effects of all parameters on positional dependency. RESULTS: The study sample consisted of 318 NPOSA patients and 242 POSA patients (88% and 85% were men, respectively). The mean apnea-hypopnea index (AHI) was 57.0 events/h in the NPOSA group, compared with 25.7 events/h in the POSA group. The POSA group had a significantly smaller neck circumference (NC), waist circumference (WC), hip circumference (HC), lower body mass index (BMI), AHI, fasting blood glucose, and apolipoprotein-B (apoB) levels than did the NPOSA group (all, P < 0.01). The minimal nocturnal oxyhemoglobin saturation (minSpO2) and apoB/apoA ratio were higher in the POSA group than in the NPOSA group (both, P < 0.001). The AHI, minSpO2, WC, and fasting blood glucose level were included in the logistic regression models. CONCLUSION: The AHI, WC, minSpO2, and fasting blood glucose level are the main independent risk factors for NPOSA.

Sea level nocturnal minimal oxygen saturation can accurately detect the presence of obstructive sleep apnea in a population with high pretest probability.

PURPOSE: To evaluate whether a predictive model based on nocturnal minimal oxygen saturation (SpO2) alone can accurately detect the presence of obstructive sleep apnea (OSA) in a population with suspected OSA. METHODS: A total of 4297 participants with suspected OSA were enrolled in this study, and laboratory-based polysomnography (PSG) tests were performed at sea level in all subjects. Nocturnal minimal SpO2 was obtained automatically as part of the PSG test. Stratified sampling was used to divide the participants' data into the training set (75%) and the test set (25%). An OSA detection model based on minimal SpO2 alone was created using the training set data and its performance was evaluated using the independent test set data ("hold-out" evaluation). Gender-specific models, and models based on minimal SpO2 in combination with other predictive factors (age, body mass index, waist-to-hip ratio, snoring grade, Epworth Sleepiness Scale score, and comorbidities), were also created and compared in terms of OSA detection performance. RESULTS: The prevalence of OSA was 85.6% in our study population. The models including multiple predictors, and the gender-specific models, failed to outperform the model based solely on minimal SpO2, which showed good predictive performance (C statistic, 0.922) having an overall accuracy rate of 0.86, sensitivity of 0.87, specificity of 0.84, positive predictive value of 0.97, and positive likelihood ratio of 5.34. In addition, the model based on minimal SpO2 alone could also accurately predict the presence of moderate-to-severe OSA and severe OSA, with C statistics of 0.914 and 0.900, respectively. CONCLUSIONS: A predictive model based on nocturnal minimal SpO2 alone may be an alternative option to detect the presence of OSA in a high-risk population when standard diagnostic tests are unavailable.

The association between obesity indices and obstructive sleep apnea is modified by age in a sex-specific manner.

BACKGROUND: The beneficial effects of weight reduction on obstructive sleep apnea (OSA) are highly variable. Whether or not the variability is associated with the effects of age and sex remains unclear. This study examined this issue with large cross-sectional data. METHOD: Anthropometric measurements, polysomnographic variables, biochemical indicators, and medical history were collected for each participant. Multivariable linear regression with interaction terms was used to estimate the modification effect of age on the associations between OSA severity (assessed by apnea-hypopnea index, AHI) with obesity indices (body mass index, BMI; neck circumference, NC; waist circumference, WC; waist-to-hip ratio, WHR) in a sex-specific manner, and vice versa. To facilitate interpretation of the results, participants were further classified into six subpopulations according to both sex and age, and population-specific beta-coefficients were calculated and compared. RESULTS: A total of 5756 adults (4600 men) with suspected OSA were included in the study. BMI, NC, WC, and WHR were all positively correlated with AHI after adjusting for potential confounders in all populations. In men, these associations were much stronger and more significant in younger than older individuals (P for interaction < 0.001). For example, a 10% increase in BMI was independently associated with a 32% increase in AHI for men < 40 years old, whereas the corresponding increases were 21% and 17% for men 40-60 and > 60 years old, respectively. By contrast, no modification effect of age was observed in women (P for interaction > 0.05). A 10% increase in BMI was associated with 26%, 27%, and 24% increases in AHI for women < 40, 40-60, and > 60 years old, respectively. CONCLUSIONS: Age modifies the associations between obesity indices and OSA severity in a sex-specific manner. These findings may broaden the understanding of age- and sex-related heterogeneities in the pathogenic role of obesity in OSA, and may be beneficial for individualized risk evaluation and treatment management for patients with OSA.

Interaction between obstructive sleep apnea and short sleep duration on insulin resistance: a large-scale study : OSA, short sleep duration and insulin resistance.

OBJECTIVES: Both short sleep duration and obstructive sleep apnea (OSA) seem to be associated with insulin resistance. We aimed to explore whether short sleep duration modifies the relationship between OSA and insulin resistance. METHODS: Participants were consecutively enrolled from our sleep center during the period from 2007 to 2017. The index of homeostasis model assessment insulin resistance (HOMA-IR) was calculated from insulin and glucose. Sleep duration was determined by standard polysomnography. The associations between sleep duration and insulin resistance were estimated by logistic regression analyses. RESULTS: A total of 5447 participants (4507 OSA and 940 primary snorers) were included in the study. OSA was independently correlated with insulin resistance after adjusting for all potential confounders (OR, 1.319; 95% CI, 1.088-1.599), but not short sleep duration. In stratified analysis by sleep duration, compared with primary snorers, in the OSA group only extremely short sleep duration (< 5 h) was significantly associated with insulin resistance after adjusting for all covariates (OR, 2.229; 95% CI, 1.283-3.874). Rapid eye movement predominant OSA was significantly associated with insulin resistance (OR = 1.355, 95% CI: 1.019-1.802) after adjustment for confounding factors including age, sex and body mass index. CONCLUSIONS: OSA, but not short sleep duration, was independently associated with insulin resistance. It is worth noting that OSA combined with extremely short sleep duration showed a greater detrimental effect than OSA itself with regard to insulin resistance.

Interrelationships among common predictors of cardiovascular diseases in patients of OSA: A large-scale observational study.

BACKGROUND AND AIMS: The apolipoprotein B/apolipoprotein A-I (ApoB/ApoA-I) and insulin resistance has been recognized as common cardiovascular diseases (CVD) risk factors. However, whether they were biomarkers for 10-year CVD risk in obstructive sleep apnea (OSA) had been rarely studied. Besides, interrelationships between the ApoB/ApoA-I, insulin resistance and OSA remain unclear. METHODS AND RESULTS: A total of 4010 subjects were finally included. Anthropometric, fasting biochemical, and polysomnographic parameters were collected. 10-year Framingham CVD risk score (FRS) was calculated for each subjects. The relationships between insulin resistance, OSA risk and the ApoB/ApoA-I was evaluated through logistic regressions analysis, restricted cubic spline (RCS) analysis and mediation analysis. ApoB/ApoA-I, HOMA-IR and AHI were all risk factors for high10-year CVD risk as assessed by FRS (odds ratios (OR) = 5.365, 1.094, 1.010, respectively, all P < 0.001)). The fully adjusted OR (95% confidence intervals) for both OSA [1 (reference), 1.308 (1.027-1.665), 1.517 (1.178-1.953), and 1.803 (1.371-2.372)] and insulin resistance [1 (reference), 1.457 (1.173-1.711), 1.701 (1.369-2.113), 2.051(1.645-2.558)] increased from the first to the fourth quartiles of the ApoB/ApoA-I. The RCS mapped a nonlinear dose-effect relationship between the ApoB/ApoA-I and risk of insulin resistance and OSA. Mediation analyses showed HOMA-IR explain 9.7%, 4.7% and 10.8% of the association between apnea-hypopnea index, oxygen desaturation index, micro-arousal index and ApoB/ApoA-I, respectively. CONCLUSIONS: Our study revealed that ApoB/ApoA-I, insulin resistance and OSA were risk factors for CVD. Insulin resistance may serve as a potential mediator in OSA-related lipoprotein disorders and further increase CVD risk.

Association of the serum irisin level with obstructive sleep apnea: a body mass index- and physical activity-matched study.

Obesity is strongly correlated with the pathogenesis of obstructive sleep apnea (OSA); myokines may play important roles in this condition. We performed a body mass index- (BMI) and physical activity- (PA) matched study to explore the relationship between the irisin level and OSA. Ninety-six consecutive participants were recruited. After matching in terms of BMI and PA, 28 OSA patients and 28 healthy controls were finally included. Whole-night laboratory-based polysomnography was used to identify OSA. The Recent Physical Activity Questionnaire and Epworth Sleepiness Scale Questionnaire were employed to assess PA over the past 4 weeks, and daytime sleepiness. We measured serum irisin, fasting blood glucose, and insulin levels in blood samples. The serum irisin concentrations differed significantly between the control, mild OSA, moderate OSA, and severe OSA groups (p < 0.001) and correlated significantly with the apnea/hypopnea index (AHI) (r = -0.787, p < 0.001). All of age, BMI, neck, waist and hip circumferences, fasting blood glucose level, and the Epworth Sleepiness Scale and PA scores were associated with irisin levels (p < 0.05). After adjustment for these factors, the serum irisin level was independently correlated with the AHI (r = -0.428, p = 0.002). On forward logistic regression analysis, the association remained significant in the final multiple regression model (ß = -0.107, p < 0.001). The serum irisin concentration was significantly correlated with OSA severity, independently of BMI and PA. Further studies are needed to determine the molecular mechanisms in play.

The use of visceral adiposity variables in the prediction of obstructive sleep apnea: evidence from a large cross-sectional study.

PURPOSE: The purposes of this study were to evaluate the ability of visceral adiposity variables [the lipid accumulation product (LAP), the visceral adiposity index (VAI), and the triglyceride-glucose index (TyG)] in predicting obstructive sleep apnea hypopnea syndrome (OSAHS) and to determine the effect of sex on the prediction. METHODS: A total of 5539 subjects admitted to the sleep center for suspected OSAHS were consecutively recruited from 2007 to 2016. Anthropometric measurements, biological indicators, Epworth sleepiness scale score, and polysomnographic variables were collected. Prediction models for diagnosing OSAHS were established in the test group by logistic regression and verified in the validation group by receiver operating characteristic (ROC) curves. RESULTS: A total of 4703 patients were included in total. LAP and TyG were of moderate diagnostic accuracy for OSAHS, with the diagnostic efficiency differing between men and women. A prediction model was developed that combined visceral adiposity indicators with waist circumstance and the lowest SpO2. The sensitivity of those indicators were both 84% in men and women, respectively, and their specificity were both 90%. In addition, the model was confirmed in the validation group with a sensitivity and specificity of 83% and 85% in men and 85% and 84% in women. CONCLUSIONS: LAP and TyG were of moderate efficiency in screening for OSAHS. The prediction model provides a simple and practical screening tool for OSAHS.

Analysis of the Salivary Microbiome in Obstructive Sleep Apnea Syndrome Patients.

BACKGROUND: Oral microbiota plays an important role in oral and systemic diseases, while few reports referred to obstructive sleep apnea syndrome (OSAS). Thus, this study aimed to explore the different salivary microbiome in patients with OSAS and controls. MATERIALS AND METHODS: Saliva was collected from 15 OSAS patients and nine healthy controls, and bacterial genomic DNA was extracted for 16S rRNA amplicon sequencing based on the Illumina platform. RESULTS: The alpha and beta diversities were not significantly different between patients with OSAS and controls. The main phyla in the two groups were Firmicutes, Actinobacteria, Bacteroidetes, Proteobacteria, and Fusobacteria, which accounted for 95% of the abundance. The main genera were Streptococcus, Rothia, Actinomyces, Prevotella, and Neisseria. Based on the genus and operational taxonomic units, Peptostreptococcus, Alloprevotella, and Granulicatella were enriched in controls, while only Scardovia species were significantly more abundant in patients with OSAS. CONCLUSIONS: There was no significant difference in the relative abundance of bacteria between OSAS and controls. So, further studies will need to focus on the metagenome of bacteria in OSAS patients.

Excessive daytime sleepiness, metabolic syndrome, and obstructive sleep apnea: two independent large cross-sectional studies and one interventional study.

BACKGROUND: Obstructive sleep apnea (OSA) and excessive daytime sleepiness (EDS) were considered to contribute to MetS. This study was performed to assess the association between MetS and EDS in two independent large-scale populations, and in subjects who underwent upper-airway surgery. METHODS: A total of 6312 patients without self-reported depression and 3578 suspected OSA patients were consecutively recruited, during health screening examinations and from our sleep center, respectively. A total of 57 subjects with OSA who underwent upper-airway surgery were also included. Demographic, anthropometric, biochemical, and polysomnographic data were obtained. RESULTS: In the health screening examination group, 233 (9.23%) women and 350 (10.93%) men had complaints of EDS. A total of 229 (7.04%) women and 1182 (36.88%) men met the criteria for MetS. In the OSA group, 147 (21.18%) women and 1058 (36.69%) men reported EDS. In addition, 93 (13.4%) women and 1368 (47.43%) men reported MetS. In the health screening examination group, EDS did not contribute significantly to MetS (OR = 1.125, 95% CI: 0.907-1.395; p = 0.283). In the OSA group, EDS significantly contributed to MetS (OR = 1.249, 95% CI: 1.063-1.468; p = 0.007); however, the results were not significant after adjusting for sleep variables (OR = 1.071, 95% CI: 0.905-1.268; p = 0.423). Upper-airway surgery did not affect cardio-metabolic variables in OSA patients with or without EDS. CONCLUSIONS: EDS was not associated with MetS in two independent large-scale cohorts. In addition, upper-airway surgery did not affect components of MetS in OSA patients with and without EDS.

The association between obstructive sleep apnea syndrome and metabolic syndrome: a confirmatory factor analysis.

BACKGROUND: Growing evidence suggests an independent relationship between obstructive sleep apnea syndrome (OSAS) and metabolic syndrome (MS). Patients with OSAS always show clustering of metabolic components. However, the understanding of interplay between OSAS and metabolic components is still lacking. METHODS: Participants were consecutively enrolled from our sleep center during the period 2009-2013. Anthropometric variables, metabolic indicators, and sleep parameters were collected from all participants. The factor structure for MS in OSAS and non-OSAS was examined by confirmatory factor analysis. RESULTS: The OSAS and non-OSAS demonstrated clustering of metabolic components. MS in patients with OSAS was strongly associated with insulin resistance (standardized factor loading = 0.93, p < 0.001), obesity (loading = 0.92, p < 0.001), and the lipid profile (loading = 0.72, p < 0.001). Furthermore, insulin resistance was correlated with obesity and lipid profile (r = 0.86, p < 0.001; r = 0.68, p < 0.001, respectively). Obesity and lipid profile were also highly correlated in OSAS (r = 0.66, p < 0.001). In non-OSAS, MS was strongly associated with insulin resistance, obesity, and lipid profile (loading = 0.95, p < 0.001; loading = 0.74, p < 0.001; loading = 0.68, p < 0.001, respectively). Insulin resistance was most strongly associated with fasting insulin (loading = 0.65, p < 0.001). Lipid profile was most strongly associated with TG (loading = 0.88, p < 0.001). Obesity was most strongly associated with BMI (loading = 0.80, p < 0.001). CONCLUSIONS: OSAS is more prone to show clustering of metabolic components compared with non-OSAS. In particular, insulin resistance, obesity, and the lipid profile were independently and strongly correlated with MS in OSAS.

Development and validation of a simple-to-use clinical nomogram for predicting obstructive sleep apnea.

BACKGROUND: The high cost and low availability of polysomnography (PSG) limits the timely diagnosis of OSA. Herein, we developed and validated a simple-to-use nomogram for predicting OSA. METHODS: We collected and analyzed the cross-sectional data of 4162 participants with suspected OSA, seen at our sleep center between 2007 and 2016. Demographic, biochemical and anthropometric data, as well as sleep parameters were obtained. A least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data dimensionality, select factors, and construct the nomogram. The performance of the nomogram was assessed using calibration and discrimination. Internal validation was also performed. RESULTS: The LASSO regression analysis identified age, sex, body mass index, neck circumference, waist circumference, glucose, insulin, and apolipoprotein B as significant predictive factors of OSA. Our nomogram model showed good discrimination and calibration in terms of predicting OSA, and had a C-index value of 0.839 according to the internal validation. Discrimination and calibration in the validation group was also good (C-index = 0.820). The nomogram identified individuals at risk for OSA with an area under the curve (AUC) of 0.84 [95% confidence interval (CI), 0.83-0.86]. CONCLUSIONS: Our simple-to-use nomogram is not intended to replace standard PSG, but will help physicians better make decisions on PSG arrangement for the patients referred to sleep center.

Distinct severity stages of obstructive sleep apnoea are correlated with unique dyslipidaemia: large-scale observational study.

BACKGROUND: Dyslipidaemia is an intermediary exacerbation factor for various diseases but the impact of obstructive sleep apnoea (OSA) on dyslipidaemia remains unclear. METHODS: A total of 3582 subjects with suspected OSA consecutively admitted to our hospital sleep centre were screened and 2983 (2422 with OSA) were included in the Shanghai Sleep Health Study. OSA severity was quantified using the apnoea-hypopnea index (AHI), the oxygen desaturation index and the arousal index. Biochemical indicators and anthropometric data were also collected. The relationship between OSA severity and the risk of dyslipidaemia was evaluated via ordinal logistic regression, restricted cubic spline (RCS) analysis and multivariate linear regressions. RESULTS: The RCS mapped a nonlinear dose-effect relationship between the risk of dyslipidaemia and OSA severity, and yielded knots of the AHI (9.4, 28.2, 54.4 and 80.2). After integrating the clinical definition and RCS-selected knots, all subjects were regrouped into four AHI severity stages. Following segmented multivariate linear modelling of each stage, distinguishable sets of OSA risk factors were quantified: low-density lipoprotein cholesterol (LDL-C), apolipoprotein E and high-density lipoprotein cholesterol (HDL-C); body mass index and/or waist to hip ratio; and HDL-C, LDL-C and triglycerides were specifically associated with stage I, stages II and III, and stages II-IV with different OSA indices. CONCLUSIONS: Our study revealed the multistage and non-monotonic relationships between OSA and dyslipidaemia and quantified the relationships between OSA severity indexes and distinct risk factors for specific OSA severity stages. Our study suggests that a new interpretive and predictive strategy for dynamic assessment of the risk progression over the clinical course of OSA should be adopted.

Elevated low-density lipoprotein cholesterol is independently associated with obstructive sleep apnea: evidence from a large-scale cross-sectional study.

BACKGROUND: Lipid metabolism disorder is recognized to be associated with obstructive sleep apnea (OSA); however, inconsistent results have been reported. The aim of this study was to evaluate the association between lipid profile and OSA with adjustments for multiple confounding factors. METHODS: In total, 2983 subjects were recruited from the Shanghai Sleep Health Study (SSHS) during 2007-2013. Data for overnight polysomnography (PSG) parameters, serum lipids, fasting blood glucose, insulin levels, and anthropometric measurements were collected. Multivariable logistic regression analyses were used to determine the correlation between lipid profile and OSA with adjustments for confounders including lipids, age, gender, Epworth sleepiness scale, body mass index, waist/hip ratio, glucose, insulin resistance, hypertension, and smoking. RESULTS: The prevalence of hyper total cholesterol (TC), hyper triglycerides, hypo high-density lipoprotein cholesterol, hyper low-density lipoprotein cholesterol (LDL-C), hyper apolipoprotein (apo) A-I, and hyper apoB differed significantly between the non-OSA and OSA patients. Without considering the interaction across different lipids, TC, LDL-C, and apoB were independently associated with OSA in primary multivariable logistic regression analyses; the odds ratios (ORs) and 95 % confidence intervals (CIs) were 1.262 (1.109-1.438), 1.432 (1.233-1.664), and 5.582 (2.643-11.787), respectively. However, only LDL-C (OR = 1.430, 95 % CI = 1.221-1.675) was found to be an independent risk factor for OSA in further multivariable logistic regression analyses. CONCLUSIONS: We demonstrated that patients with OSA had a higher percentage of dyslipidemia than subjects without OSA. Of the various components in serum lipid, only LDL-C was independently associated with OSA.

Differences in Physiologic Endotypes Between Nonpositional and Positional OSA: Results From the Shanghai Sleep Health Study Cohort.

BACKGROUND: Positional OSA (POSA) is a recognized subtype of OSA that exhibits distinct endotypic characteristics when compared with nonpositional OSA (NPOSA). The basis for the disparity in endotypes between these subtypes remains poorly understood. RESEARCH QUESTION: (1) Do individuals with NPOSA and POSA have different underlying OSA endotypes? (2) Which endotypic characteristics are critical in determining NPOSA and POSA severity? STUDY DESIGN AND METHODS: Within the Shanghai Sleep Health Study cohort, individuals with OSA were recruited and classified as having POSA or NPOSA. Endotypes were calculated using polysomnography. RESULTS: Endotype analysis was conducted in 1,036 individuals with OSA. Compared with individuals with NPOSA, those with POSA had lower loop gain calculated during all sleep stages and all sleep positions (0.55; interquartile range [IQR], 0.46-0.66 vs 0.68, IQR, 0.52-0.90; P < .001), lower arousal threshold calculated during all sleep stages and all sleep positions (ArTHAll) (138.67; IQR, 118.94-180.87 percentage of the eupneic ventilation [%Veupnea] vs 189.00; IQR, 129.71-257.76 %Veupnea; P < .001), lower pharyngeal collapsibility calculated during all sleep stages and all sleep positions (VpassiveAll) (91.85; IQR, 83.13-95.15 %Veupnea vs 76.38; IQR, 23.77-92.08 %Veupnea; P < .001), and higher muscle compensation calculated during all sleep stages and all sleep positions (6.50; IQR, -6.77 to 16.39 %Veupnea vs 3.65; IQR, -10.47 to 12.14 %Veupnea; P = .003). Logistic regression analyses indicated that higher VpassiveAll was associated with increased odds of POSA vs NPOSA. In NPOSA, fully adjusted linear regression analyses indicated that VpassiveAll (ß = -0.55; 95% CI, -0.68 to -0.42; P < .001) and lower loop gain calculated during all sleep stages and all sleep positions (ß = 0.19; 95% CI, 0.08-0.30; P < .001) were significant independent predictors of the apnea hypopnea index, with VpassiveAll being the most critical factor. In contrast, in POSA, collapsibility appeared to be less influential (ß = -0.09; 95% CI, -0.21 to 0.03; P = .138). Nonanatomic endotypic characteristics (LGAll: ß = 0.29; 95% CI, 0.18-0.41; P < .001; arousal threshold in all sleep stages and all sleep positions: ß = 0.15; 95% CI, 0.01-0.28; P = .031; muscle compensation in all sleep stages and all sleep positions: ß = -0.21; 95% CI, -0.29 to -0.12; P < .001) were significant in determining the severity of POSA, with loop gain being the most crucial factor. INTERPRETATION: This study highlights the differences in endotypes between NPOSA and POSA. In Chinese individuals, anatomic factors were more significant in determining the severity of NPOSA, whereas nonanatomic traits were more likely to determine the severity of POSA. Future research should focus on developing personalized management strategies for individuals with NPOSA and POSA based on their endotypes. TRIAL REGISTRATION: Chinese Clinical Trial Registry; No.: ChiCTR1900025714; URL: https://www.chictr.org.cn/indexEN.html.

Global burden of thyroid cancer from 1990 to 2021: a systematic analysis from the Global Burden of Disease Study 2021.

Thyroid cancer (TC) is a significant global healthcare burden. However, the lack of comprehensive data has impeded our understanding of its global impact. We aimed to examine the burden of TC and its trends at the global, regional, and national levels using data stratified by sociodemographic index (SDI), sex, and age. Data on TC, including incidence, mortality, and disability-adjusted life-years (DALYs) from 1990 to 2021, were obtained from the Global Burden of Disease Study 2021. Estimated annual percentage changes (EAPCs) were calculated to assess the incidence rate, mortality, and DALYs trends. The incidence, mortality, and DALYs of TC in 2021 were 249,538 (95% uncertainty interval: 223,290-274,638), 44,799 (39,925-48,541), and 646,741 (599,119-717,357), respectively. The age-standardized incidence rate (ASIR) in 2021 was 2.914 (2.607-3.213), with an EAPC of 1.25 (1.14-1.37) compared to 1990. In 2021, the age-standardized death rate (ASDR) was 0.53 (0.47-0.575) and age-standardized DALYs rate was 14.571 (12.783-16.115). Compared with 1990, the EAPCs of ASDR and age-standardized DALYs rate showed decreasing trends, at - 0.24 (- 0.27 to - 0.21) and - 0.14 (- 0.17 to - 0.11), respectively. Low SDI regions showed the highest ASDR and age-standardized DALYs rate, at 0.642 (0.516-0.799) and 17.976 (14.18-23.06), respectively. Low-middle SDI regions had the highest EAPCs for ASDR and age-standardized DALYs rate, at 0.74 (0.71-0.78) and 0.67 (0.63-0.7), respectively. Females exhibited decreasing trend in ASDR and age-standardized DALYs rate, with EAPCs of - 0.58 (- 0.61 to - 0.55) and - 0.45 (- 0.47 to - 0.42), respectively. In contrast, males showed an increasing trend in ASDR and age-standardized DALYs rate, with EAPCs of 0.41 (0.35-0.46) for both. In high-income regions, most countries with decreased annual changes in deaths experience increasing age-related deaths. Over the past few decades, a notable increase in TC incidence and decreased mortality has been observed globally. Regions characterized by lower SDI, male sex, and an aging population exhibited no improvement in TC mortality. Effective resource allocation, meticulous control of risk factors, and tailored interventions are crucial for addressing these issues.

Global burden of head and neck cancers from 1990 to 2019.

Head and neck cancer (HNC) exerts a significant healthcare burden worldwide. Insufficient data impedes a comprehensive understanding of its global impact. Through analysis of the 2019 Global Burden of Disease (GBD) database, our secondary investigation unveiled a surging global incidence of HNC, yet a decline in associated mortality and disability-adjusted life years (DALYs) owing to enhanced prognosis. Particularly noteworthy is the higher incidence of escalation among females compared to males. Effective resource allocation, meticulous control of risk factors, and tailored interventions are imperative to curtail mortality rates among young individuals afflicted with HNC in underprivileged regions, as well as in elderly individuals grappling with thyroid cancer.

Effects of the combination of novel eye mask sleep position therapy device and oral appliance on positional OSA: A multi-arm, parallel-group randomized controlled trial.

OBJECTIVES: We explored whether a new combination of eye mask sleep position therapy (SPT) and oral appliance therapy (OAT) was more effective at treating positional obstructive sleep apnea (POSA) than was the use of either device alone. METHODS: In this randomized controlled trial, 60 POSA subjects diagnosed by standard polysomnography (PSG) were divided into three groups (ratio 1:1:1): SPT, OAT, and SPT combined with OAT (SOT). Participants underwent hospital-based follow-ups during months 1 and 6 after beginning treatment. The primary outcome was the decline in the apnea hypopnea index (AHI) at month 6. The secondary outcomes were changes in oxygen-derived parameters and the curative effect at month 6. RESULTS: After 6 months of treatment, PSG showed that SPT, OAT, and SOT all improved the AHI and oxygen-derived parameters. The AHI decline was significantly better in the SOT group than in the OAT or SPT group (71.58% [50.56-84.84%] for SOT, 44.42% [21.23-67.52%] for OAT, and 33.24% [19.03-54.62%] for SPT at 6 months) (P = 0.018 and P < 0.001 for the comparisons of SOT with OAT and SOT with SPT, respectively). In terms of oxygen-derived parameters, only the sleep apnea-specific hypoxic burden (SASHB) improved more in the SOT group (76.89% [57.43-85.91%]) than in the other groups (44.73% [32.38-72.69%] for OAT and 41.82% [15.40-65.24%] for SPT, P = 0.002 and P < 0.001 for the comparisons of SOT with OAT and SOT with SPT, respectively). The efficacies of SPT, OAT, and SOT were 36.84%, 50%, and 80% at 6 months; the SOT group evidenced the highest value (rate ratio [95% confidence interval] 1.78 (1.05-3.03), P = 0.048 and 2.17 (1.16-4.07), P = 0.010, for the comparisons of SOT with OAT and SOT with SPT, respectively). CONCLUSION: The combination of SPT and OAT was better than either treatment alone and may represent a good option for the treatment of POSA. TRIAL REGISTRATION: Chinese Clinical Trial Registry; URL: http://www.chictr.org.cn/showproj.aspx?proj=42,852; No. ChiCTR1900025584.