高血压是我国重点防治的心血管疾病, 血压的控制率备受关注。在一些血压控制不良的患者中睡眠呼吸暂停是导致顽固性高血压的重要原因。以睡眠过程中反复、频繁出现呼吸暂停和低通气为特点的睡眠呼吸暂停低通气综合征( sleep apneahypopnea syndrome, SAHS) 自20 世纪80 年代以来也受到广泛关注, 临床和基础研究取得了迅速发展。目前, 多项临床、流行病学和基础研究证实SAHS可以导致和/ 或加重高血压, 与高血压的发生发展密切相关。
ObjectiveTo systematically review the prevalence of obstructive sleep apnea syndrome (OSAS) in China. MethodsPubMed, EMbase, The Cochrane Library, CBM, CNKI, WanFang Data, and VIP databases were electronically searched to collect cross-sectional studies of the prevalence of OSAS in China from inception to October 30th, 2020. Two reviewers independently screened literature, extracted data and evaluated the risk of bias of included studies. Meta-analysis was then performed using Stata 16.0 software. ResultsA total of 27 studies were included, with a total sample size of 97 746 cases and 10 853 confirmed OSAS patients. Meta-analysis results showed that the prevalence of OSAS in China was 11% (95%CI 5% to 17%), of which females was 12% (95%CI 5% to 19%) and males was 12% (95%CI 5% to 20%). OSAS cases grouped by regions were as follows: Central China 4% (95%CI 2.7% to 4.5%), South China 5% (95%CI 2.7% to 6.7%), North China 7% (95%CI 4.6% to 9.3%), Northeast China 22% (95%CI 17.7% to 61.2%), Southwest China 4% (95%CI 3.2% to 5%), Northwest China 16% (95%CI 14.5% to 17.7%), and East China 17% (95%CI 2.8% to 30.6%). OSAS patients grouped by ages were as follows: 4% (95%CI 3% to 5%) for ≤14 years old, 5% (95%CI 2% to 7%) for 15-44 years old, 13% (95%CI 6% to 20%) for 45-59 years old, 16% (95%CI 6% to 25%) for 60-74 years old, 13% (95%CI 4% to 23%) for 75-89 years old, and 11% (95%CI 2% to 21%) for ≥ 90 years old. A subgroup analysis based on the year of publication found that the prevalence of OSAS fluctuated between 6% and 9% from 2005 to 2020, and the prevalence was the highest from 2000 to 2005 accouted with 21% (95%CI 0.8% to 40.5%). ConclusionsThe prevalence of OSAS in China is relatively high, and there are differences in the prevalence among individuals of different ages and regions. The 60-year-old groups in addition to the Northeast and East China regions have a high incidence. The prevalence of OSAS is substantially consistent between males and females. Due to the limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusions.
Objective To investigate the correlation between serum level of visfatin and obesity in patients with obstructive sleep apnea hypopnea syndrome ( OSAHS) . Methods Forty-seven patients with OSAHS and 20 healthy controls were recruited in this study. Polysomnography was performed in all subjects to detect apnea-hypopnea index ( AHI) . The serumlevels of cisfatin, C-reactive protein ( CRP) , TNF-α, and IL-6 were measured by enzyme linked immunosorbent assay. The body mass inex ( BMI) was calculated.The level of cisfatin was compared between the OSAHS patients with different severity and the controls, and its relationship with the levels of AHI, BMI, CRP, TNF-α, and IL-6 was analyzed. Results The serumlevel of visfatin in the OSAHS patients was higher significantly than that in the controls ( P lt;0. 01) and increased by the severity of OSAHS. There were positive correlations between the serum level of visfatin and AHI,BMI, CRP, TNF-α, IL-6 in the OSAHS patients ( P lt;0. 05) . Conclusion The expression of visfatin may play an important role in the pathogenesis of OSAHS.
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 changes and clinical relationship of plasma adrenomedullin( ADM) , atrial natriuretic polypeptide( ANP) , and heart rate variability( HRV) in patients with obstructive sleep apnea-hypopnea syndrome ( OSAHS) . Methods Seventy-five inpatients with OSAHS were enrolled in this study. According to the apnea hypopnea index ( AHI) by polysomnography, the subjects were divided into a mild group, a moderate group, and a severe group. Meanwhile, HRV was screened bydynamic electrocardiogram in sleep laboratory. HRV parameters were obtained including LF ( low frequency power) , HF( high frequency power) , pNN50( percentage of NN50 in the total number of N-N intervals) ,SDNN( standard deviation of the N-N intervals) , rMSSD( square root of the mean squared differences of successive N-N intervals ) . Plasma levels of ADM/ANP were measured by radioimmunoassay. Results The levels of SDNN ( P lt;0. 05) , rMSSD, pNN50, LF ( P lt; 0. 05) and HF were gradually reduced, and the levels of ADM ( P lt;0. 05) and ANP ( P lt; 0. 05) were increased with increasing severity of OSAHS. Linear correlation analysis demonstrated that SDNN was negatively correlated with ADM( r = - 0. 423, P lt;0. 05)and ANP( r = - 0. 452, P lt; 0. 05) , and LF was also negatively correlated with ADM( r = - 0. 348, P lt;0. 05) . Conclusion Lower HRV is associated with more sever OSAHS, and it may be modulated neurohumorally by ADM and ANP.
目的:探讨早产儿呼吸暂停相关高危因素,指导临床防治工作。方法:对90例早产儿呼吸暂停进行回顾性分析。结果:胎龄越小,体重越低的早产儿,原发性呼吸暂停发生率越高,随着胎龄增加继发性呼吸暂停发生率亦增加,继发性呼吸暂停与缺氧、低体温、酸中毒、脑损伤、感染等因素有关,生后2～5d为发病高峰期。结论:呼吸暂停与胎龄、体重、缺氧、低体温、低血糖、酸中毒、感染、颅脑损伤等多因素有关。对有相关高危因素早产儿应足够重视,减少呼吸暂停发生。
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.
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.