Association of Hypertriglyceridemic Waist Phenotype with Obstructive Sleep Apnea: A Cross-Sectional Study

The long-term impact of hypertriglyceridemia-waist phenotype on major adverse cardiovascular events in elderly patients with OSA

INTRODUCTION

The hypertriglyceridemia-waist (HTGW) phenotype is a prevalent risk factor for cardiovascular diseases and obstructive sleep apnea (OSA). However, the impactof the HTGW phenotype on the simultaneous occurrence of OSA and cardiovascular diseases remains unexplored. This study aimed to determine whether the HTGW phenotype elevates the incidence of major adverse cardiovascular events (MACE) in patients with OSA, such as hospitalization for unstable angina and heart failure, myocardial infarction, and cardiovascular death, in patients with OSA.

METHODS

A total of 1,290 patients with OSA were recruited from six hospitals for follow-up. According to the Chinese population criteria recommended by the International Diabetes Federation, the patients were divided into four groups: normal triglyceride waist circumference (NTNW) phenotype, pure high triglyceride (HTNW) phenotype, pure high waist circumference (NTGW) phenotype, and HTGW phenotype. The prognosis for MACE was evaluated using Cox proportional hazards analysis. The prognosis of MACE was evaluated using Cox proportional hazards analysis.

RESULTS

207 (17.9%) developed an HTGW phenotype. After a median of 42 months of follow-up, 119 (10.3%) experienced MACE. Cox proportional hazards analysis revealed that patients exhibiting the HTGW phenotype had a 1.963-fold higher risk of developing MACE than patients with the NTNW phenotype (P = 0.012). These results remained significant after adjusting for confounders, and a 2.186-fold increased risk of MACE was found in patients with NTGW phenotype (P = 0.012). Subgroup analyses revealed an increased risk of MACE in OSA patients with HTGW phenotype and NTGW phenotype that were older than or equal to 70 years, male, and had moderate-to-severe OSA (all P-values < 0.05).

CONCLUSION

The HTGW and NTGW phenotypes significantly increase MACE risk among elderly patients with OSA.

The use of the sleep apnea-specific hypoxic burden to predict obstructive sleep apnea hypopnea syndrome: Evidence from a large cross-sectional study

OBJECTIVES

Obstructive sleep apnea hypopnea syndrome (OSA) is an independent risk factor for neurocognitive and behavioral problems and cardiovascular and metabolic morbidities, ultimately increasing mortality. However, OSA diagnosis is time-consuming, labor-intensive, and expensive. We evaluated the predictive utility of the sleep apnea-specific hypoxic burden (SASHB) in terms of OSA and the severity thereof in Han Chinese individuals.

METHODS

From January 2019 to July 2022, subjects with suspected OSA were recruited in the sleep center of the Shanghai Sixth People's Hospital during sleep evaluation via standard polysomnography. Basic anthropometric measurements and polysomnographic indicators were collected; SASHB was calculated based on the SpO2 trends of apnea or hypopnea events. Models predictive of OSA were established via logistic regression in the experimental group and verified in an independent group by drawing receiver operating characteristic (ROC) curves.

RESULTS

A total of 2303 subjects with suspected OSA (1200 in the experimental group and 1103 in the validation group) were included. SASHB was positively correlated with the apnea-hyponea index (AHI) in all subjects (r = 0.823, P < 0.001). SASHB distinguished OSA from non-OSA subjects in both the experimental group {area under the curve (AUC) 0.948 [0.934∼0.962]} and the validation group (AUC 0.931 [0.913∼0.949]). SASHB predicted OSA severity well, better than did the neck, waist, or hip circumference; the lowest or mean oxygen saturation; and the Epworth sleepiness scale score.

CONCLUSION

SASHB predicted OSA both accurately and efficiently in a Chinese Han population. Further studies are warranted to verify our findings in community samples.

The Diagnostic Value of Gut Microbiota Analysis for Post-Stroke Sleep Disorders

BACKGROUND

Gut microbiota have been associated with many psychiatric disorders. However, the changes in the composition of gut microbiota in patients with post-stroke sleep disorders (PSSDs) remain unclear. Here, we determined the gut microbial signature of PSSD patients.

METHODS

Fecal samples of 205 patients with ischemic stroke were collected within 24 h of admission and were further analyzed using 16 s RNA gene sequencing followed by bioinformatic analysis. The diversity, community composition, and differential microbes of gut microbiota were assessed. The outcome of sleep disorders was determined by the Pittsburgh Sleep Quality Index (PSQI) at 3 months after admission. The diagnostic performance of microbial characteristics in predicting PSSDs was assessed by receiver operating characteristic (ROC) curves.

RESULTS

Our results showed that the composition and structure of microbiota in patients with PSSDs were different from those without sleep disorders (PSNSDs). Moreover, the linear discriminant analysis effect size (LEfSe) showed significant differences in gut-associated bacteria, such as species of Streptococcus, Granulicatella, Dielma, Blautia, Paeniclostridium, and Sutterella. We further managed to identify the optimal microbiota signature and revealed that the predictive model with eight operational-taxonomic-unit-based biomarkers achieved a high accuracy in PSSD prediction (AUC = 0.768). Blautia and Streptococcus were considered to be the key microbiome signatures for patients with PSSD.

CONCLUSIONS

These findings indicated that a specific gut microbial signature was an important predictor of PSSDs, which highlighted the potential of microbiota as a promising biomarker for detecting PSSD patients.

Association Between Triglyceride Glucose Index-Waist Circumference and Risk of First Myocardial Infarction in Chinese Hypertensive Patients with Obstructive Sleep Apnoea: An Observational Cohort Study

PURPOSE

This study aimed to investigate the association between triglyceride glucose index-waist circumference (TyG-WC) and the risk of first myocardial infarction (MI) in Chinese hypertensive patients with obstructive sleep apnoea (OSA).

METHODS

This study was an observational cohort study. A total of 2224 Chinese hypertensive patients with OSA without a history of MI were included in this study. Hazard ratio (HR) and 95% confidence interval (CI) were estimated using multivariable Cox proportion hazard models. A generalized additive model was used to identify nonlinear relationships. Additionally, we performed hierarchical analysis and test for interaction.

RESULTS

During a median follow-up of 7.15 years, 85 incidents of MI developed. Overall, there was a positive association between TyG-WC and the risk of first MI. In the multivariable-adjusted model, the risk of MI increased with quartiles of the TyG-WC, the HR in quartile 4 versus quartile 1 was 4.29. A generalized additive model and a smooth curve fitting showed that there existed a similar J-shaped association between TyG-WC and the risk of first MI, with an inflection point at about 785.

CONCLUSION

Elevated levels of the baseline TyG-WC are associated with an increased risk of first MI. This finding indicates that the TyG-WC might be useful to identify the high risk of first MI in Chinese hypertensive patients with OSA.