Objective To clarify that the vascular endothelial cell injury caused by obstructive sleep apnoea hypopnea syndrome (OSAHS) is partly mediated by miRNA-92a. Methods Serum miRNA-92a level was measured in patients who underwent polysomnography between January 2018 and December 2018. The correlation between miRNA-92a and OSAHS was analyzed. Meanwhile, endothelial cells were cultured in vitro, and morphological changes and JC-1 staining results of endothelial cells were observed after OSAHS serum stimulation, so as to further clarify the injury of endothelial cells. The changes of miRNA-92a target gene were detected by reverse transcription-polymerase chain reaction (RT-PCR) and Western blot to further clarify the mechanism of endothelial cell injury. Results Seventy-two patients received polysomnography, including 22 cases in the non-OSAHS group, 18 in the mild OSAHS group, 10 in the moderate OSAHS group, and 22 in the severe OSAHS group. Serum miRNA-92a level was significantly increased in the OSAHS patients, and it also increased with the aggravation of OSAHS severity. OSAHS serum significantly damaged endothelial cells. Endothelial cells were swollen, disordered arrangement, and unclear boundaries. JC-1 staining showed that green fluorescence was significantly enhanced compared with the control group. RT-PCR and Western blot showed that the expressions of Krüppel-like factor-2 (KLF-2), Krüppel-like factor-4 (KLF-4) and endothelial nitric oxide synthase (eNOS) were significantly decreased under OSAHS serum stimulation. Conclusion Serum miRNA-92a of OSAHS patients is significantly increased, and reduces the expression of target genes KLF-2, KLF-4 and eNOS, affects the mitochondrial function of endothelial cells, and injures endothelial cells.
Objective To investigate the differences in clinical characteristics and polysomnographic characteristics between the elderly obstructive sleep apnea-hypopnea syndrome ( OSAHS) patients and the young and middle-aged OSAHS patients. Methods The clinical manifestations and the polysomnographic characteristics of 37 elderly OSAHS patients and 294 young and middle-aged patients were analyzed. The differences in polysomnographic indicators between two groups were compared according to the body mass index.Results The nocturia frequency in the elderly OSAHS patients was higher( P =0. 01) ,however, the othert clinical manifestations between the elderly group and the young and middle-aged group were not different significantly. The elderly group had a lower body mass index ( P =0. 018) , a smaller neck circumference ( P =0. 003) , and a larger chance of diabetes ( P = 0. 001) and hypertension( P lt; 0. 001) .The phase Ⅰ and phase Ⅱ sleep of the elderly group took a longer duration ( P lt; 0. 001) and a larger proportion( P lt;0. 001) . The sleep apnea-hypopnea index between two groups did not show any significant difference( P =0. 082) . The lowest night oxyhemoglobin saturation of the elderly group was higher than that of the young and middle-aged group( P =0. 009) , but such difference disappeared after adjustment by weight ( P =0. 114) . Conclusions The major clinical manifestations of the elderly OSAHS patients are similar to the young and middle-aged patients. The elderly patients are thinner than the young and middle-aged patients, but have more complications and a higher frequency of nocturia. The night oxyhemoglobin saturation is lower in young and middle-aged patients which is associated with higher body mass index.
Sleep apnea causes cardiac arrest, sleep rhythm disorders, nocturnal hypoxia and abnormal blood pressure fluctuations in patients, which eventually lead to nocturnal target organ damage in hypertensive patients. The incidence of obstructive sleep apnea hypopnea syndrome (OSAHS) is extremely high, which seriously affects the physical and mental health of patients. This study attempts to extract features associated with OSAHS from 24-hour ambulatory blood pressure data and identify OSAHS by machine learning models for the differential diagnosis of this disease. The study data were obtained from ambulatory blood pressure examination data of 339 patients collected in outpatient clinics of the Chinese PLA General Hospital from December 2018 to December 2019, including 115 patients with OSAHS diagnosed by polysomnography (PSG) and 224 patients with non-OSAHS. Based on the characteristics of clinical changes of blood pressure in OSAHS patients, feature extraction rules were defined and algorithms were developed to extract features, while logistic regression and lightGBM models were then used to classify and predict the disease. The results showed that the identification accuracy of the lightGBM model trained in this study was 80.0%, precision was 82.9%, recall was 72.5%, and the area under the working characteristic curve (AUC) of the subjects was 0.906. The defined ambulatory blood pressure features could be effectively used for identifying OSAHS. This study provides a new idea and method for OSAHS screening.
Objective To investigate the prevalence of obstructive sleep apnea hypopnea syndrome ( OSAHS) in patients with idiopathic pulmonary fibrosis ( IPF) and its clinical significance. Methods Sleep quality and breathing disorders were measured by polysomnography and the relationship with lung function was analyzed in 20 IPF patients. Results Thirteen of 20 subjects ( 65% ) had OSAHS as defined by an AHI ≥5 events per hour. Three subjects ( 15% ) had mild OSAHS ( AHI,5 to 20 events per hour) , and 10 subjects ( 50% ) had moderate-to-severe OSAHS ( AHI≥20 events per hour) . The sleep architecture in these patients showed a reduction in sleep efficiency, rapid eye movement ( REM) sleep and slow wave sleep, and a marked sleep fragmentation due to an increased arousal index. The AHI was negatively correlated with FVC% pred ( r =-0.672, P=0.001) and FEV1% pred ( r =-0.659, P=0.002) , and positively correlated with body mass index ( BMI) ( r=0.791, Plt;0.0001) . Conclusions OSAHS is a common comorbidity in IPF. Early treatment of OSAHS may improve quality of life and the prognosis of patients with IPF.
目的 总结多导睡眠监测的监测方法及护理要点。 方法 2010年3月－2011年3月采用美国伟康多导睡眠呼吸监测仪对睡眠中心78例患者进行不少于7 h的整夜连续监测和护理。 结果 76例患者顺利完成监测，确诊阻塞性睡眠呼吸暂停低通气综合征73例（重度17例，中度31例，轻度25例），单纯鼾症3例。1例因环境陌生、导联多无法入睡而监测失败，另1例因鼻气流导管脱落而监测失败。 结论 对症有效的护理方法是多导睡眠监测得以顺利完成的根本保证。
Objective To investigate the correlation between obstructive sleep apnea hypopnea syndrome (OSAHS) and biochemical indexes in children. Methods Seventy-eight children with OSAHS in our hospital from January 2015 to February 2017 were recruited as an observation group, and 100 normal children who underwent physical examination were selected as a control group in the same period. The mean values and positive rates of biochemical markers were compared between two groups including alanine aminotransferase (ALT), blood urea nitrogen (BUN), total cholesterol (TC), triglyceride (TG), creatine kinase isoenzyme (CK-MB), cardiac troponin I (cTnI), fasting blood glucose (FPG) level. Results The mean values of biochemical indexes showed significant differences between the observation group and the control group except BUN and FPG [ALT, (52.1±26.2) U/L vs. (41.3±18.5) U/L; TC, (4.9±0.9) mmol/L vs. (4.3±0.8) mmol/L; TG, (1.4±0.7) mmol/L vs. (1.0±0.4) mmol/L; CK-MB, (24.3±9.5) U/L vs. (11.2±8.2) U/L; cTnI, (1.4±0.7) μg/L vs. (1.0±0.6) μg/L] (all P<0.05). The positive rates also showed significant differences between the observation group and the control group except BUN and FPG [ALT (48.7%vs. 14.0%), TC (24.4% vs. 8.0%), TG (23.1% vs. 8.0%), CK-MB (41.0% vs. 11.0%), cTnI (34.6% vs. 7.0%) (all P<0.05). Conclusions The cardiac function and liver function are significantly impaired in children with OSAHS, showing the disorder of lipid metabolism to some extent. These abnormal indexes may be the occurrence and development of OSAHS. More attention should be paid to the detection of biochemical indexes in children with OSAHS.
ObjectiveTo analyse the hundred top-cited articles in obstructive sleep apnea hypopnea syndrome (OSAHS), and summarize the development trend of OSAHS research.MethodsWe searched the Web of Science core collection for all published articles on OSAHS or sleep disorders from January 1st, 1992 to May 23th, 2018. The hundred top-cited articles with the most frequent citation were selected. The publication time, country of origin, journal, institution, professional field of corresponding author, funding type, publication type, etc. were analyzed.ResultsThe hundred top-cited articles were published between 1992 and 2013, with 300～5 980 citations and a total of 65 719 citations. The main types of articles were clinical studies (73 articles), reviews (20 articles), guidelines (4 articles) and basic research (3 articles). Fourteen authors published more than one first-author paper, and fifteen authors published more than one articles as corresponding authors. These authors were distributed across 22 subject areas. The most cited country was the United States (60 articles), and the most cited institution was the University of Wisconsin (10 articles). The hundred top-cited articles were published in 31 journals, most of which were cited less than 1 000 times, and a few articles were cited more than 2 000 times.ConclusionsOSAHS has attracted much attention in respiratory medicine, neurology, epidemiology and other fields, and many articles about clinical research types of OSAHS have been cited. In addition, most of the highly cited articles in the OSAHS field come from the developed countries; our country needs to devote more resources to OSAHS research.
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.
Objective To prospectively verify the accuracy and reliability of the diagnostic model of obstructive sleep apnea (OSA), including the probability model and disease severity model, and to explore a simple and cost-effective method for screening of OSA. Methods A total of 996 patients who underwent polysomnography in Zigong Fourth People’s Hospital(590 cases) and West China Hospital of Sichuan University(406 cases) were consecutively and prospectively included as the research subjects. Firstly, the OSA diagnostic model was used for the diagnostic test; then polysomnography was performed; Finally, taking polysomnography as the gold standard, the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio and area under the ROC curve of OSA diagnostic model were calculated, and the reliability analysis of the model’s results was carried out. Results The sensitivity, specificity and accuracy of the OSA diagnostic model were 76.38%(595/779), 83.41%(181/217) and 77.91%(776/996) respectively, the positive predictive value is 94.29%, negative predictive value is 45.49%, positive likelihood ratio is 4.604, negative likelihood ratio is 0.283; and the area under the ROC curve was 0.866. The reliability analysis of OSA diagnostic model showed that there was no significant difference in the bias comparison of AHI; the intra-class correlation coefficient(ICC) between AHI in the OSA diagnostic model and AHI in polysomnography was 0.659, with a relatively strong consistency degree; the intra-class correlation coefficient between the lowest SpO2 in the OSA diagnostic model and the lowest SpO2 in polysomnography was 0.563, with a moderate consistency degree. Conclusions The OSA diagnostic model can better predict the probability of illness and assess the severity of the disease, which is helpful for the early detection, diagnosis and treatment of OSA. The OSA diagnostic model is suitable for popularization and application in primary hospitals and when polysomnography is not available in time.