Sanders Mark H, Givelber Rachel
Division of Pulmonary, Allergy and Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Sleep Med. 2003 Jul;4(4):349-50. doi: 10.1016/s1389-9457(03)00118-7.
OBJECTIVE(S): (a) To determine if self-reported diabetes mellitus is independently associated with sleep-disordered breathing (SDB); (b) to determine if diabetes mellitus is specifically associated with central sleep apnea including periodic breathing (Cheyne-Stokes breathing pattern) during sleep.
The study population reflected participants in the on-going Sleep Heart Health Study (SHHS). Analyses were conducted utilizing data obtained from 4872 SHHS participants without prevalent cardiovascular disease (CVD) and 1002 participants with self-reported CVD, defined as hospitalization for non-fatal coronary heart disease, congestive heart failure, myocardial infarction, coronary artery bypass graft, and stroke.
SHHS methodologies have been previously reported and include performance of overnight, in-home polysomnography (PSG), which recorded variables reflecting sleep architecture and breathing, permitting identification of obstructive and central apneas, hypopneas, periodic breathing and oxyhemoglobin saturation (SpO(2)). Anthropomorphic metrics as well as systemic blood pressure measurements were obtained at the time of PSG. Other health data were available from questionnaires and the data sets of the parent cohorts from whom SHHS participants were recruited. The investigators assessed and compared breathing parameters, sleep architecture and CVD variables in diabetic and non-diabetic participants. The relationships between diabetes and the various study parameters, independent of potential confounders, were examined by multivariable modeling. Linear regression modeling was employed to examine the relationship between continuously distributed variables such as respiratory disturbance index log (RDI). The relationships between diabetes and dichotomous outcome variables such as central apnea index (CAI), obstructive apnea index (OAI), periodic breathing and the percentage of time spent at various levels below SpO(2) 90% were examined by the logistic regression model. Age, gender, race, BMI and neck circumference were forced into all multivariable analyses since these factors are associated with both diabetes mellitus and SDB.
The investigators reported that the prevalence of CVD risk factors including increased BMI, waist circumference, neck circumference, triglycerides, reduced HDL cholesterol and hypertension was greater in diabetic than non-diabetic participants. Native Americans represented a disproportionately high percentage of the diabetic population. Unadjusted data obtained from participants without prevalent CVD indicated that the mean RDI was higher in the diabetic participants. Moreover, there was a greater percentage of diabetic participants in the higher RDI categories (e.g. 23.8% of the 470 diabetics and 15.6% of the 4402 non-diabetics had RDI>15, P<0.001). Similarly, the unadjusted data indicated that a significantly greater proportion of the diabetic participants spent >5% and >10% of sleep time below SpO(2) 90%, compared with the non-diabetic participants. The unadjusted data from participants without prevalent CVD indicated that the diabetic and non-diabetic participants did not differ with regard to distribution by category of OAI severity (e.g. > or =2 events/h, > or =3 events/h, or > or =4 events/h). On the other hand, although the prevalence of central apneas was low, a significantly greater proportion of diabetic participants were in the CAI categories (> or =2 events/h and > or =3 events/h) than non-diabetic subjects. There was no difference between diabetic and non-diabetic individuals with regard to CAI prevalence in the > or =4 events/h category. Of note, a greater percentage of diabetic patients exhibited periodic breathing (3.8% vs. 1.8%, diabetic and non-diabetic participants, respectively, P=0.002). Repeating the above analyses with inclusion of the participants with prevalent CVD did not change these relationships, and in fact, the differences between diabetic and non-diabetic participants with respect to central events and periodic breathing became more evident (the data forre evident (the data for this were not provided in the paper). Linear regression analyses demonstrated that BMI, age and male gender were independently related to increased RDI among participants without prevalent CVD. Furthermore, after adjusting for age, gender, race, BMI and neck circumference, there was no difference in geometric mean RDI between the diabetic and non-diabetic participants. The adjusted odds of having RDI> or =15 and the adjusted odds for spending> or =5% or > or =10% of sleep time with SpO(2) <90% did not differ between the diabetic and non-diabetic individuals. The investigators also examined sleep architecture in the study cohort. There were no differences between the diabetic and non-diabetic groups with regard to the adjusted proportion of time spent in non-REM sleep stages, although the mean percent time spent in REM sleep was 1.1% less in the diabetic individuals. The findings were the same with or without inclusion of participants with known CVD. Even after adjustment for potential confounders, in a sample without or with prevalent CVD, diabetic participants had increased adjusted odds for periodic breathing odds ratio (1.8, 95% confidence interval (CI) with a range of 1.02--3.15 in diabetic participants without prevalent CVD vs. 1.74, 95% CI with a range of 1.16--2.62 in diabetic participants with prevalent CVD). There was a suggestion of increased odds for CAI in diabetic subjects when analyzing populations with and without prevalent CVD.
The authors concluded that diabetes mellitus is associated with sleep apnea but that this association is largely explained by risk factors in common for both disorders, most notably obesity. After adjusting for confounding factors there was no difference between diabetic and non-diabetic participants with regard to obstructive events. However, even after adjusting for potential confounders, there was a greater prevalence of periodic breathing in diabetic subjects. Although not reaching statistical significance, there was a suggestion of an increased prevalence of central events in the diabetic population, particularly when the sample included participants with known CVD. The investigators believed it unlikely that the findings were attributable to underlying congestive heart failure in as much as the diabetic subjects without prevalent CVD exhibited increased prevalence of periodic breathing and possibly increased central events. The authors proposed that diabetes mellitus might be a cause of SDB, mediated through autonomic neuropathy that may alter ventilatory control mechanisms. In this context, the authors commented that autonomic neuropathy may cause perturbations in ventilatory control by altering chemoreceptor gain or altering cardiovascular function (although the authors discounted underlying congestive heart failure as an explanation for the higher prevalence of periodic breathing in diabetic participants). To reinforce their conclusions, the authors cited the literature indicating increased prevalence of sleep apnea in diabetic patients with autonomic dysfunction, as well as the association between Shy--Drager syndrome, in which autonomic insufficiency is a constitutive element, and central sleep apnea.
(a) 确定自我报告的糖尿病是否与睡眠呼吸紊乱(SDB)独立相关;(b) 确定糖尿病是否与包括睡眠期间周期性呼吸(陈-施呼吸模式)在内的中枢性睡眠呼吸暂停有特定关联。
研究人群反映了正在进行的睡眠心脏健康研究(SHHS)中的参与者。分析使用了从4872名无心血管疾病(CVD)的SHHS参与者和1002名自我报告有CVD的参与者那里获得的数据,CVD定义为因非致命性冠心病、充血性心力衰竭、心肌梗死、冠状动脉搭桥术和中风而住院。
SHHS的方法先前已报告,包括在家中进行的夜间多导睡眠图(PSG)检查,记录反映睡眠结构和呼吸的变量,以识别阻塞性和中枢性呼吸暂停、呼吸不足、周期性呼吸和氧合血红蛋白饱和度(SpO₂)。在进行PSG检查时获取人体测量指标以及系统血压测量值。其他健康数据可从问卷以及招募SHHS参与者的母队列的数据集中获得。研究人员评估并比较了糖尿病和非糖尿病参与者的呼吸参数、睡眠结构和CVD变量。通过多变量建模研究了糖尿病与各种研究参数之间独立于潜在混杂因素的关系。采用线性回归建模来研究连续分布变量如呼吸紊乱指数对数(RDI)之间的关系。通过逻辑回归模型研究糖尿病与二分结局变量如中枢性呼吸暂停指数(CAI)、阻塞性呼吸暂停指数(OAI)、周期性呼吸以及SpO₂低于90%的不同水平下所花费时间的百分比之间的关系。年龄、性别、种族、BMI和颈围被纳入所有多变量分析,因为这些因素与糖尿病和SDB均相关。
研究人员报告称,糖尿病参与者中包括BMI增加、腰围、颈围、甘油三酯升高、高密度脂蛋白胆固醇降低和高血压在内的CVD危险因素的患病率高于非糖尿病参与者。美洲原住民在糖尿病患者中所占比例过高。从无CVD的参与者获得的未调整数据表明,糖尿病参与者的平均RDI更高。此外,在较高RDI类别中糖尿病参与者的比例更高(例如,470名糖尿病患者中有23.8%,4402名非糖尿病患者中有15.6%的RDI>15,P<0.001)。同样,未调整数据表明,与非糖尿病参与者相比,糖尿病参与者中有明显更高比例的人在睡眠期间SpO₂低于90%的时间超过5%和10%。从无CVD的参与者获得的未调整数据表明,糖尿病和非糖尿病参与者在OAI严重程度类别分布方面没有差异(例如,≥2次事件/小时、≥3次事件/小时或≥4次事件/小时)。另一方面,尽管中枢性呼吸暂停的患病率较低,但糖尿病参与者中处于CAI类别(≥2次事件/小时和≥3次事件/小时)的比例明显高于非糖尿病受试者。在≥4次事件/小时类别中,糖尿病和非糖尿病个体的CAI患病率没有差异。值得注意的是,糖尿病患者中表现出周期性呼吸的比例更高(分别为糖尿病和非糖尿病参与者的3.8%和1.8%,P = 0.002)。纳入有CVD的参与者重复上述分析并未改变这些关系。事实上,糖尿病和非糖尿病参与者在中枢性事件和周期性呼吸方面的差异变得更加明显(论文中未提供此方面的数据)。线性回归分析表明,在无CVD的参与者中,BMI、年龄和男性性别与RDI增加独立相关。此外,在调整年龄、性别、种族、BMI和颈围后,糖尿病和非糖尿病参与者的几何平均RDI没有差异。糖尿病和非糖尿病个体在RDI≥15以及睡眠期间SpO₂<90%的时间≥5%或≥10%的调整后比值没有差异。研究人员还检查了研究队列中的睡眠结构。糖尿病和非糖尿病组在非快速眼动睡眠阶段所花费时间的调整比例方面没有差异,尽管糖尿病个体在快速眼动睡眠中花费的平均时间百分比少1.1%。无论是否纳入已知有CVD的参与者,结果都是相同的。即使在调整潜在混杂因素后,在无或有CVD的样本中,糖尿病参与者周期性呼吸的调整后比值增加(无CVD的糖尿病参与者的比值比为1.8,95%置信区间(CI)范围为1.02 - 3.15;有CVD 的糖尿病参与者的比值比为1.74,95%CI范围为1.16 - 2.62)。在分析有和无CVD的人群时,糖尿病受试者中CAI的比值有增加的趋势。
作者得出结论,糖尿病与睡眠呼吸暂停相关,但这种关联在很大程度上由两种疾病共有的危险因素所解释,最显著的是肥胖。在调整混杂因素后,糖尿病和非糖尿病参与者在阻塞性事件方面没有差异。然而,即使在调整潜在混杂因素后,糖尿病受试者中周期性呼吸的患病率更高。尽管未达到统计学意义,但糖尿病患者中枢性事件的患病率有增加的趋势,特别是当样本包括已知有CVD的参与者时。研究人员认为,这些发现不太可能归因于潜在的充血性心力衰竭,因为无CVD的糖尿病受试者表现出周期性呼吸患病率增加,并且可能中枢性事件也增加。作者提出,糖尿病可能是SDB的一个原因,通过自主神经病变介导,自主神经病变可能改变通气控制机制。在此背景下,作者评论说,自主神经病变可能通过改变化学感受器增益或改变心血管功能而导致通气控制紊乱(尽管作者排除了潜在的充血性心力衰竭作为糖尿病参与者中周期性呼吸患病率较高的解释)。为了强化他们的结论,作者引用文献表明自主神经功能障碍的糖尿病患者中睡眠呼吸暂停的患病率增加,以及以自主神经功能不全为主要特征的Shy - Drager综合征与中枢性睡眠呼吸暂停之间的关联。