This study seeks to explore the early signs of cognitive impairment in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). According to polysomnography, twenty patients diagnosed with OSAHS and twenty normal controls underwent event-related potential (ERP) examination including mismatch negativity (MMN) and P300. Compared with normal controls, OSAHS patients showed significantly prolonged latency of MMN and P300 at Cz. After controlling age and body mass index (BMI), MMN latency positively correlated with apnea hypopnea index (AHI), oxygen reduction index, stage N1 sleep and arousal index, while MMN latency negatively correlated with stage N3 sleep and mean blood oxygen saturation; and P300 latency positively related to AHI and oxygen reduction index; no relationships were found among MMN latency, MMN amplitude, P300 latency and P300 amplitude. These results suggest that the brain function of automatic processing and controlled processing aere impaired in OSAHS patients, and these dysfunction are correlated with nocturnal repeatedly hypoxemia and sleep structure disturbance.
Objective To investigate the risk factors of chronic obstructive pulmonary disease (COPD) combined with obstructive sleep apnea (OSA) and its relationship with apnea-hypopnea index (AHI). Methods Clinical data of 216 COPD patients with OSA were retrospectively chosen in the period from January 2016 to December 2019 in our hospital. All patients were divided into different groups according to with or without OSA and the clinical features of patients with and without OSA were compared. Multivariate analysis was used to analyze the influencing factors of COPD with OSA and the correlation between AHI and COPD with OSA was also evaluated. Results ① The age, body mass index (BMI), neck circumference, smoking index, forced expiratory volume in 1 second (FEV1), FEV1% predicted (FEV1pred), the ratio of FEV1 to the forced vital capacity of the lungs (FEV1/FVC), COPD assessment test (CAT) score, Epworth sleepiness scale (ESS) score, Charlson comorbidity index (CCI) score, sleep apnea clinical score (SACS) score and proportion of patients with essential hypertension in OSA group were significantly higher than non-OSA group (P<0.05). The course of disease and the proportion of severe COPD and GOLD grade 4 in OSA group were significantly less than non-OSA group (P<0.05). ② AHI was positively correlated with age, BMI, neck circumference, smoking index, FEV1%pred, FEV1%pred<50%, CAT score, ESS score, CCI score and SACS score (P<0.05); and negatively correlated with FEV1%pred<50% (P<0.05). ③ Multivariate analysis showed that BMI, FEV1%pred<50%, CAT score and ESS score were the independent factors of COPD patients with OSA (P<0.05). ④ The proportion of AHI<5 times/h in GOLD grade 4 was significantly higher than GOLD grade 1-3 (P<0.05). The proportion of AHI> 30 times/h in GOLD grade 4 was significantly lower than GOLD grade 1-3 (P<0.05). Conclusion The incidence of COPD with OSA was independently correlated with BMI, FEV1%pred, CAT score and ESS score; patients with severe COPD possess lower OSA risk.
Objective To study the correlation between smoking and obstructive sleep apnea (OSA). Methods A total of 454 patients from October 2015 to July 2021 were retrospectively collected for nocturnal polysomnography monitoring (no less than 7 hours). The patients were divided into an OSA group (n=405) and a control group (n=49, patients with primary snoring) according to the results of polysomnography monitoring. According to the apnea hypopnea index (AHI) and the lowest oxygen saturation during sleep, the severity of OSA was classified into a mild to moderate group (5 times/h ≤ AHI<30 times/h) and a severe group (AHI ≥30 times/h). The patients were inquired about their smoking history, then the patients diagnosed with OSA were further divided into a smoking group, a smoking cessation group, and a non-smoking group based on their smoking history. Results The smoking rate of the patients in the OSA group was higher than that in the control group (50.9% vs. 32.7%, P<0.05), while the smoking rate in the severe OSA group was higher than that in the mild to moderate group (55.7% vs. 39.8%, P<0.05). Smoking was positively correlated with AHI, cumulative percentages of time spent at oxygen saturation below 90% (Ts90%), and total apnea time (r value was 0.196, 0.197, 0.163, P<0.05), while negatively correlated with the lowest and average SpO2 during sleep (r value was –0.202, –0.214, P<0.05). The logistic regression analysis with severe OSA as the outcome variable showed that smoking (OR=1.781) and obesity (OR=1.930) were independent risk factors of severe OSA (P<0.05). The comparison between groups of the OSA patients with different smoking states showed that the proportion of severe OSA, AHI, Ts90%, and total apnea time (77.8%, 53.55 times/h, 18.35%, and 111.70 minutes, respectively) of the smoking group were higher than those of the non-smoking group (62.8%, 40.20 times/h, 8.40%, and 76.20 minutes, respectively, P<0.05). The lowest SpO2 and average SpO2 during sleep (69.50%, 93.00%, respectively) of the smoking group were lower than those of the non-smoking group (75.00%, 94.00%, respectively, both P<0.05). The average SpO2 of the smoking cessation group was higher than that of the smoking group (94.00% vs. 93.00%, P<0.05), and the Ts90% of the smoking cessation group was lower than that of the smoking group (6.75% vs. 18.35%, P<0.05). Conclusions Smoking significantly affects the degree of sleep-disordered breathing and may be an independent risk factor for severe OSA. Smoking can exacerbate the severity of OSA and the degree of hypoxia, while smoking cessation can improve the degree of hypoxia in OSA patients.
Sleep disorder is related to many comorbidities, such as diabetes, obesity, cardiovascular diseases, and hypertension. Because of its increasing prevalence rate, it has become a global problem that seriously threatens people’s health. Various forms of sleep disorder can cause increased insulin resistance and/or decreased sensitivity, thus affecting the occurrence, development and prognosis of diabetes. However, sleep health has not been paid attention to in recent years. Therefore, this article summarizes the findings of the correlation between sleep disorder and diabetes mellitus in recent years, by elaborating the relationship between various types of sleep disorder (including sleep apnea syndrome) and diabetes mellitus, as well as their mechanisms and intervention measures, in order to enhance the attention of clinical workers to sleep health, and to provide basis for reducing the risk of diabetes.
Habitual snoring can occur in both children and adults. If it is physiological snoring, it usually does not require special intervention. If it is pathological snoring, such as snoring caused by central diseases and obstructive diseases, it needs to be treated as soon as possible. Habitual snoring has more harm to children, such as causing sleep structure disorders, slow growth and development. During the snoring process, children’s sleep fragmentation and hypoxia state lead to changes in the transmission of neurochemicals in the brain’s precortex, causing adverse effects on brain function and inducing attention deficit hyperactivity disorder. This article reviews relevant research in recent years to further elucidate the relationship between children’s habitual snoring and attention deficit hyperactivity disorder, and provide a basis for future clinical research and intervention.