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. 2021 Nov 20;41(11):1592–1599. [Article in Chinese] doi: 10.12122/j.issn.1673-4254.2021.11.01

老年阻塞性睡眠呼吸暂停与代谢综合征各组分的相关性及其对远期不良心血管事件发生风险的影响

Correlation of obstructive sleep apnea with components of metabolic syndrome and implications for long‐term adverse cardiovascular risk in elderly patients

Xiaofeng SU 1,2, Jiming HAN 2, Yinghui GAO 3, Zijun HE 2, Zhe ZHAO 1, Junling LIN 4, Jingjing GUO 5, Kaibing CHEN 6, Yan GAO 7, Lin LIU 1,*
PMCID: PMC8685693  PMID: 34916183

Abstract

Objective

To investigate the relationship between obstructive sleep apnea (OSA) and components of metabolic syndrome (MetS) in the elderly and the implications for long-term risk for major adverse cardiovascular events (MACE).

Methods

This multicenter prospective cohort study was conducted among 1157 consecutive patients with OSA [defined as an apnea-hypopnea index (AHI) ≥5 times/h recorded by overnight polysomnography] aged ≥60 years enrolled from January, 2015 to October, 2017. All the patients did not have a history of MACE at baseline and had complete documentations of MetS indicators. The baseline demographic data, clinical characteristics, biochemical markers, and sleep parameters were collected from all the patients, who were divided into 4 groups according to the quartile level of AHI and followed up for a median of 42 months for MACE and its component events (cardiovascular death, myocardial infarction, and hospitalization for unstable angina or heart failure). Multivariate linear regression and Cox proportional risk regression models were used to analyze the correlation of MetS components with major objective predictors of OSA, AHI and LSpO2 and the long- term risk of MACE.

Results

AHI and LSpO2 quartiles group showed a positive dose-response relationship with MetS components [fasting blood glucose, waist circumference, systolic blood pressure, and triglycerides] and a negative dose-response relationship with high-density lipoprotein level. MACE occurred in 119 (10.3%) patients with OSA during the follow-up. Multivariate Cox regression analysis showed that a high triglycerides, a high systolic blood pressure, and an increased waist circumference were independent risk factors for MACE and its component events (P < 0.05 or 0.01); a high HDL was a protective factor against MACE and myocardial infarction (P < 0.05 or 0.01) independent of the AHI. MetS components independent of LSpO2 showed no significant correlations with the risk of MACE or its component events.

Conclusion

The major diagnostic indexes AHI and LSPO2 in elderly patients with OSA have a dose-response relationship with MetS components, and the interaction between the components of MetS and AHI can increase the risk of MACE and its component events.

Keywords: obstructive sleep apnea, elderly, metabolic syndrome, major adverse cardiovascular events, cardiovascular diseases

阻塞性睡眠呼吸暂停（OSA）是最常见的睡眠呼吸障碍类型，经由睡眠期间的间歇性部分或完全的上气道阻塞引起的以呼吸暂停和低通气为主要临床表现的潜在致死性综合征[1]。OSA可通过各种机制影响心脏结构和功能，包括胰岛素抵抗、氧化应激、交感神经激活、内皮功能障碍和炎症增加[2]。OSA与心血管疾病之间密切相关[3]，但这种关联可能因代谢综合征（MetS）而存在不同。MetS是过度腹部肥胖、血脂异常、高血压、高血糖和胰岛素抵抗的组合，与心血管事件和死亡率的风险增加有关[4]。MetS存在于所有年龄组中，老年人的患病率最高[5]。OSA和MetS往往在临床人群中聚集[6]。一项针对横断面研究的荟萃分析显示，OSA与MetS显著相关[7]。实则，OSA和MetS之间的关系是双向的，OSA会增加MetS的发生风险，反之亦然[8]。在临床实践中，OSA中的睡眠呼吸暂停低通气指数（AHI）是用于评估OSA严重程度并进行分类和指导治疗的标志物，其与慢性间歇性缺氧引起的MetS有关。此外，睡眠期的氧饱和度下降也是OSA的另一常见病理生理现象。在流行病学研究中，OSA与MACE及其组成事件（心血管死亡、心肌梗死（MI）、需住院的心绞痛或心力衰竭）发病风险密切相关。然而，OSA与MetS的发展机制复杂，关于MetS各组分与老年OSA患者的两个主要特征性诊断指标AHI和LSpO2之间的关联及其对老年OSA人群远期MACE及其组成事件发生风险的影响仍未明确。

因此，本研究，基于多中心研究样本分析OSA和MetS各组分之间的相关性，基于前瞻性随访结局探讨OSA的两个主要临床诊断指标和MetS各组分对远期心血管事件发生风险的影响。

1. 资料和方法

1.1. 研究对象

本研究为多中心前瞻性队列研究，中位随访时间42（41，53）月。2015年1月~2017年10月在解放军总医院、北京大学国际医院、北京大学人民医院、北京朝阳医院、解放军第九六零医院和甘肃中医药大学附属医院住院部或门诊连续纳入经多导睡眠监测（PSG）首次确诊为OSA的老年患者1290例进行随访，年龄60~96岁，中位年龄66（62，71）岁，其中≥70岁的患者占总人数的30.94%（358例），伴有基础疾病的患者是593例（51.25%）。纳入标准：年龄≥60岁；住院部或门诊睡眠中心进行整夜PSG（住院部患者在入院后1周内临床稳定后行PSG），符合OSA诊断，诊断标准参考《成人阻塞性睡眠呼吸暂停多学科诊疗指南》[8]。排除标准：先前合并心血管疾病疾病（MI、需住院的心绞痛或心力衰竭）；之前接受过常规CPAP（持续呼吸道正压通气）治疗（>3个月）或从随访开始至今持续进行CPAP干预的OSA患者；恶性肿瘤患者；失访人群。最终纳入符合研究标准的老年OSA患者1157例。本研究已获得解放军总医院伦理委员会批准（S2020-397-02），所有参与本研究的患者均签署知情同意书。

1.2. 方法

1.2.1. 基线数据收集

从6家医院睡眠中心的临床数据管理系统中提取了以下基线资料，人口学变量：年龄、性别、体质量指数（BMI）、血压、空腹血糖（FPG）、腰围及自我报告的吸烟和饮酒情况等；生化指标：甘油三酯（TG）、高密度脂蛋白（HDL）等；睡眠参数指标：AHI、氧减指数（ODI）、平均氧饱和度（MSpO2）和最低氧饱和度（LSpO2）等；临床病史：在诊断OSA前6个月内从医院数据管理系统中确定基线合并症（颈动脉粥样硬化、高脂血症、心房颤动、高血压、慢性阻塞性肺病（COPD）、冠心病（CHD）和糖尿病史等。当前吸烟定义为每天至少一支，当前饮酒定义为每周饮酒一次，持续至少半年。测量SBP和舒张压（DBP）3次，高血压定义为至少两次连续测量SBP/DBP的平均值≥140/90 mmHg或使用抗高血压药物[9]。使用中国成人高脂血症管理指南定义高脂血症[10]。房颤根据ESC2016指南[11]定义。颈动脉粥样硬化、CHD和COPD是通过相关诊断临床记录确定的，表明该疾病的存在。

1.2.2. 睡眠监测

如前所述[12]，所有研究对象均采用便携PSG仪（澳大利亚Compumedics分析系统）记录睡眠参数。监测时间均>7 h，监测参数包括脑电图、眼电图、心电图、体位、口鼻气流、胸腹式呼吸、夜间打鼾、脉氧饱和度，同时记录患者的AHI、ODI、MSpO2、LSpO2等。每家医院入选患者的PSG结果均由2名睡眠技术人员手动校对，最终诊断结果由一名高级睡眠医师进行审查。睡眠测试分析根据2017年美国睡眠医学会指南进行评分[13]。OSA定义为AHI≥5次/h。AHI即睡眠期间每小时发生呼吸暂停和低通气事件次数之和。呼吸暂停定义为气流持续停止超过10 s，而低通气定义为气流减少50%且持续时间至少10 s。ODI定义为氧饱和度下降≥4%。轻度OSA为AHI 5~14次/h，中度OSA为AHI15~29次/h，重度OSA为AHI≥30次/h[14]。

1.2.3. MetS的定义

MetS的定义是根据NCEPATP Ⅲ标准（亚洲人的腰围标准修订版）[15]存在以下5个临床特征中的至少3个：男性WC≥90 cm，女性WC≥80 cm；TG≥1.70 mmol/L；男性HDL < 1.03 mmol/L，女性 < 1.30 mmol/L；SBP≥130 mmHg或DBP≥85 mmHg或正在服用降压药；空腹血糖≥5.6 mmol/L或正在服用抗糖尿病药物。

1.2.4. 随访

研究开始前对6家医院的负责人、调查员及数据质量审核人员进行统一培训，包括随访方案、基线数据的录入标准及审核标准、微信数据管理平台的使用等。我们从PSG评估的诊断时间到2020年12月，对1157例OSA患者进行了随访，中位随访42（41，53）个月，随访结局包括MACE及其组成事件（心血管死亡、MI、需住院的不稳定型心绞痛或心力衰竭）。每3个月进行一次随访（至少3月，最长不超过6月）。受试者的随访结局由两名调查员通过电话随访、微信追踪随访、上门随访和住院部或门诊病历系统查询，调查员每六个月对患者的PSG结果不知情。所有临床事件均由原始文件确认，并由临床事件委员会裁决。所有患者在42个月的中位随访期内，均根据其疾病状况接受标准医疗护理。

1.3. 统计学方法

采用SPSS 23.0软件件（version 23.0, SPSS Inc., Chicago, Illinois, USA）进行数据分析，分类变量采用百分比（%）表示，组间比较采用χ2检验。正态分布的连续型变量以Mean±SD表示，组间比较采用t检验；不符合正态分布用中位数（四分位间距）[M（Q）]表示，组间比较采用Kruskal-Wallis H非参数检验；MetS各组分与OSA两个主要特征的相关性采用多元线性回归分析；Cox比例风险回归模型用于评估OSA的主要特征和MetS各组分对于老年OSA患者MACE及其组成事件发生风险的影响。所有统计均采用双侧检验，P < 0.05为差异有统计学意义。所有实验都是独立重复3次。

2. 结果

2.1. 患者的基线特征

共入选1157例年龄≥60岁的老年OSA患者，中位年龄66（62，71）岁，其中男性704例，女性453例，男女比例1.55∶1。MetS总患病率为60.76%（703例），MetS各组分（FG、WC、SBP、TG、HDL）中，超过诊断标准异常值的发生人数占比分别为[55.32%（640例）、36.73%（425例）、66.98%（775例）、49.87%（577例）和62.23%（720例）]。根据基线AHI的四分位数将所有老年OSA患者分为四组，Quartile 1 [AHI≤14.95次/h] 289例，中位AHI 9.30（6.70，11.90）次/h；Quartile 2 [14.95 < AHI≤27.20次/h] 285例，中位AHI 20.80（17.90，23.75）次/h；Quartile 3 [27.20 < AHI≤45.40次/h] 292例，中位AHI 26.30（24.34，29.01）次/h；Quartile 4[AHI>45.40次/h] 289例，中位AHI 28.34（25.95，31.14）次/h。研究人群4组的组间颈围、舒张压、吸烟、饮酒、COPD、高脂血症、房颤及高血压史无统计学差异（P>0.05），其余组间的基线人口学数据、临床特征、生化指标、睡眠参数均有统计学差异（P < 0.05，P < 0.01，表 1）。

1.

患者的临床特征

Clinical characteristics of the patients

Variables Quartile 1 (n=289) Quartile 2 (n=287) Quartile 3 (n=292) Quartile 4 (n=289) Statistics P
BMI: Body mass index; NC: neck circumference; WC: Waist circumference; WHR: Waist/hip ratio; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; AHI: The apnea-hypopnea index; ODI: The oxygen desaturation index; MSpO2: The mean pulse oxygen saturation; LSpO2: The lowest pulse oxygen saturation; T90: Percentage of the times for SaO2 < 90% in total monitoring time during overnight sleep; TST: Total sleep time; TSA90: The duration of time with SaO2 < 90%; OSA: Obstructive sleep apnea; LAT: The longest apnea time; MAT: The mean apnea time; FPG: Fasting plasma glucose; TG: Triglyceride; CHD: Coronary heart disease; COPD: Chronic obstructive pulmonary disease.
Demographics
  Age[year, M(Q1, Q3)] 67.0(63.0, 72.0) 65.0(62.0, 72.0) 66.0(62.0, 71.0) 65.0(61.0, 70.0) 18.551 < 0.001
  Male[n(%)] 158(54.67) 161(56.10) 195(66.78) 190(65.74) 14.569 0.02
  BMI[kg/m2, M(Q1, Q3)] 25.25(22.66, 27.47) 25.51(23.44, 27.69) 26.30(24.34, 29.01) 28.34(25.95, 31.14) 121.235 < 0.001
  WC[cm, M(Q1, Q3)] 88.0(80.0, 95.0) 89.0(78.0, 98.0) 90.0(80.0, 10.0) 98.0(87.0, 107.0) 68.371 < 0.001
  NC[cm, M(Q1, Q3)] 37.50(35.0, 40.0) 38.0(35.50, 40.0) 38.0(36.0, 40.0) 38.0(35.0, 40.0) 1.407 0.704
  WHR[%, M(Q1, Q3)] 0.80(0.70, 0.85) 0.70(0.70, 0.80) 0.80(0.70, 0.90) 0.90(0.80, 1.10) 28.791 < 0.001
  SBP[mmHg, M(Q1, Q3)] 128.0(120.0, 135.0) 129.0(120.0, 138.0) 130.0(120.0, 140.0) 130.0(123.0, 139.0) 9.858 0.020
  DBP[mmHg, M(Q1, Q3)] 76.0(70.0, 80.0) 75.0(70.0, 81.0) 76.0(70.0, 83.25) 75.0(70.0, 80.0) 4.082 0.253
  Smoking[n(%)] 57(19.79) 57(19.86) 75(25.68) 67(23.18) 4.097 0.251
  Drinking[n(%)] 26(9.03) 29(10.10) 36(12.33) 25(8.65) 2.641 0.45
  TG[mmol/L, M(Q1, Q3)] 1.20(0.91, 1.76) 1.31(0.99, 1.76) 1.23(0.89, 1.71) 1.42(1.01, 1.94) 13.912 0.003
  FPG[mmol/L, M(Q1, Q3)] 5.55(4.96, 6.21) 5.63(5.04, 6.34) 5.72(5.03, 6.57) 5.70(5.12, 6.43) 8.313 0.040
  HDL[mmol/L, M(Q1, Q3)] 1.13(0.95, 1.43) 1.18(0.96, 1.44) 1.08(0.88, 1.37) 1.10(0.90, 1.35) 10.124 0.018
Sleep parameters
  AHI[events/h, M(Q1, Q3)] 9.30(6.70, 11.90) 20.80(17.90, 23.75) 34.40(30.65, 39.73) 59.10(51.80, 69.90) 1083.750 < 0.001
  TST[h, M(Q1, Q3)] 7.05(6.23, 7.31) 7.10(6.32, 7.59) 6.96(5.89, 7.36) 7.18(6.30, 7.75) 16.183 0.01
  ODI[events/h, M(Q1, Q3)] 8.20(4.60, 12.0) 15.60(11.15, 21.85) 28.50(22.0, 36.50) 52.0(42.60, 62.90) 717.264 < 0.01
  TSA90[min, M(Q1, Q3)] 3.41(0.70, 34.02) 8.30(1.90, 29.90) 17.02(4.27, 51.78) 68.0(19.0, 150.50) 185.857 < 0.001
  MSpO2[%, M(Q1, Q3)] 94.0(92.0, 95.0) 94.0(92.0, 95.0) 94.0(92.0, 95.0) 92.0(90.0, 94.0) 86.579 < 0.001
  LSpO2[%, M(Q1, Q3)] 84.0(80.0, 87.0) 82.0(77.0, 86.0) 79.0(72.0, 84.0) 72.0(63.0, 79.0) 227.547 < 0.001
  MAT[s, M(Q1, Q3)] 21.35(17.40, 24.33) 21.20(18.0, 24.84) 22.91(20.21, 26.0) 23.81(20.98, 29.0) 72.369 < 0.001
  LAT[s, M(Q1, Q3)] 30.40(14.0, 44.0) 40.50(28.0, 56.0) 56.0(41.50, 76.30) 67.0(47.0, 88.0) 288.518 < 0.001
  T90[%, M(Q1, Q3)] 0.01(0.0, 0.08) 0.02(0.0, 0.07) 0.05(0.01, 0.13) 0.17(0.05, 0.39) 182.448 < 0.001
Medical history
  COPD[n(%)] 24(8.30) 17(5.92) 22(7.53) 17(5.88) 1.958 0.581
  CHD[n(%)] 51(17.65) 71(24.74) 77(26.37) 66(22.84) 7.057 0.070
  Carotid atherosclerosis[n(%)] 93(32.18) 63(21.95) 78(26.71) 62(21.45) 11.379 0.010
  Hyperlipidemia[n(%)] 92(31.83) 76(26.48) 78(26.71) 79(27.34) 2.729 0.435
  Hypertension[n(%)] 179(61.94) 173(60.28) 180(61.64) 210(72.66) 12.390 0.06
  Diabetes[n(%)] 57(19.72) 63(21.95) 83(28.42) 83(28.72) 9.698 0.021
  Atrial fibrillation[n(%)] 18(6.23) 17(5.92) 40(13.70) 22(7.61) 17.933 0.06
  MetS[n(%)] 175(60.55) 164(57.54) 183(62.67) 181(62.63) 2.451 0.484
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2.2. MetS的各组分与OSA主要诊断指标的相关性

将OSA两个主要诊断指标AHI和LSpO2通过四分位数水平进行分组，分别比较其与MetS各组分之间的相关性。AHII和LSpO2四分位组均与MetS各组分（FG、WC、SBP、TG）存在正剂量效应关系，与HDL水平呈负剂量反应关系（图 1）。多元线性回归分析显示，校正潜在混杂因素后，WC（β=0.345, P < 0.001），SBP（β=0.102, P=0.021），TG（β=1.421, P=0.040）是影响OSA严重程度诊断指标AHI的独立风险因素，HDL（β=-4.066, P= 0.004）为保护性因素。而MetS各组分中，仅WC（β= 0.229, P < 0.001）是影响OSA严重程度的另一评判指标LSpO2的独立危险因素（表 2）。

1.

1

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AHI和LSpO2四分位数的Mets组分水平趋势

The tendency of MetS biomarker levels acrossAHI and LSpO2 quartiles. *P < 0.05.

2.

AHI和LSpO2的逐步多元线性回归模型

Stepwise multivariate linear regression model forAHI and LSpO2

Predictors AHI LSpO2
B SE(B) P VIF B SE(B) P VIF
Model 1 was adjusted by age, sex for WC, TG, HDL, SBP, and FG; Model 2 was adjusted by age, sex, BMI, WHR, carotid atherosclerosi, CHD or diabetes treatment history and SBPfor WC, TG, HDL, SBP, and FG.
Model 1
  SBP 0.103 0.067 0.019 1.03 0.032 0.039 0.178 1.03
  WC 0.346 0.256 0.000 1.027 0.162 0.228 0.000 1.027
  TG 1.453 0.061 0.035 1.04 0.635 0.050 0.084 1.040
  HDL -4.089 -0.082 0.004 1.035 0.487 -0.019 0.521 1.035
  FPG 0.578 0.039 0.166 1.015 0.133 0.017 0.550 1.015
Model 2
  SBP 0.102 0.066 0.021 1.032 0.034 0.042 0.151 1.032
  WC 0.345 0.256 0.000 1.028 0.163 0.229 0.000 1.028
  TG 1.421 0.059 0.040 1.049 0.565 0.045 0.126 1.049
  HDL -4.066 -0.082 0.004 1.036 0.536 -0.021 0.480 1.036
  FPG 0.582 0.04 0.163 1.016 0.143 0.019 0.520 1.016
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2.3. OSA、MetS各组分与MACE及其组分的Cox回归分析

以老年OSA患者的MACE及其组分（心血管死亡、MI、需住院的心绞痛或心力衰竭）的各自发生状况分别作为因变量，赋值1=发生，0=未发生，t=生存期。以MetS的各组分（TG、WC、HDL、SBP和FG）和OSA的两个临床诊断指标AHI和LSpO2为自变量，调节其它潜在风险因素，建立Cox回归模型。模型1为未调整模型，模型2针对年龄、性别、BMI、腰臀比、收缩压和临床病史等进行调整；模型3在模型2的基础上，进一步调整了评判OSA严重程度的两个临床指标AHI和LSpO2。Model 2中，MetS组分中高TG（HR=1.74, 95% CI: 1.22- 2.48, P < 0.01）是MACE的独立危险因素；WC增加（HR=1.13, 95% CI: 1.01-1.03, P < 0.05）和高TG（HR= 2.23, 95% CI: 1.45-3.43, P < 0.001）是需住院的不稳定心绞痛或心力衰竭的独立危险因素；高HDL是MACE、MI和需住院的不稳定心绞痛或心力衰竭的保护因素（P < 0.05，P < 0.01）。Model 3在Model 2的基础上进一步调整AHI和LSpO2，高TG仍是MACE和需住院的不稳定心绞痛或心力衰竭的独立危险因素（P < 0.05，P < 0.01），高HDL是MACE和MI的保护性因素（P < 0.05，P < 0.01），SBP增加是心血管死亡的独立风险因素（P < 0.05），WC增加是心血管死亡和需住院的不稳定心绞痛或心力衰竭的独立危险因素（P < 0.05），且独立于AHI; 相比之下，LSpO2未表现出与MACE及其组成事件发生风险的相关性（表 3）。

3.

不良心血管事件发生风险的Cox回归模型

Cox regression model for the risk of MACE

MACE(n=119)
HR(95% CI)		 Cardiovascular death(n=25)
HR(95% CI)		 MI(n=38)
HR(95% CI)		 Hospitalization for unstable angina or heart failure(n=75)
HR(95% CI)
Model 1 was adjusted for the MetS group; Model 2 was adjusted by age, sex, BMI, carotid atherosclerosi, CHD or diabetes treatment history, SBP and WHR, and sleep parameters of T90, ODI, TSA90, LAT, MAT or MSpO2 for WC, TG, HDL, SBP, and FPG; Model 3 was adjusted using the variables listed above in model 1 forAHI and LSpO2. *P < 0.05. **P < 0.01. ***P < 0.001.
Model 1
  SBP 1.01(0.98, 1.01) 0.99(0.93, 1.02) 0.97(0.95, 1.01) 1.01(0.98, 1.03)
  WC 1.08(0.96, 1.02) 1.00(0.98, 1.03) 1.06(0.96, 1.07) 1.01(0.99, 1.03)
  HDL 0.73(0.55, 0.97)* 0.81(0.49, 1.42) 0.52(0.28, 0.95)* 0.61(0.40, 0.94)*
  TG 1.48(1.07, 2.05)* 1.35(0.62, 2.93) 1.29(0.71, 2.35) 1.77(1.18, 2.64)**
  FPG 1.06(0.89, 1.15) 0.72(0.49, 1.05) 0.92(0.71, 1.20) 1.11(0.94, 1.28)
Model 2
  SBP 0.99(0.97, 1.00) 0.97(0.933, 1.004) 0.98(0.947, 1.01) 0.99(0.97, 1.01)
  WC 1.01(0.99, 1.02) 1.01(0.98, 1.03) 1.01(0.991, 1.03) 1.13(1.01, 1.03)*
  HDL 0.69(0.53, 0.91)** 0.79(0.451, 1.383) 0.50(0.272, 0.91)* 0.56(0.37, 0.89)*
  TG 1.74(1.22, 2.48)** 1.30(0.554, 3.071) 1.56(0.799, 3.06) 2.23(1.45, 3.43)***
  FPG 1.01(0.88, 1.15) 0.71(0.482, 1.051) 0.90(0.683, 1.18) 1.10(0.94, 1.29)
Model 3
  SBP 0.98(0.97, 1.01) 1.11(1.01, 1.03)* 0.98(0.951, 1.01) 0.99(0.98, 1.01)
  WC 1.03(0.98, 1.02) 1.08(1.03, 1.14)* 1.01(0.96, 1.05) 1.036(1.02, 1.07)*
  HDL 0.74(0.56, 0.98)** 0.97(0.59, 1.59) 0.57(0.305, 1.05)* 0.68(0.45, 1.01)
  TG 1.69(1.19, 2.43)** 0.92(0.37, 2.27) 1.52(0.72, 3.23) 1.85(1.17, 2.94)*
  FPG 1.00(0.88, 1.15) 0.72(0.49, 1.06) 0.87(0.67, 1.14) 1.07(0.92, 1.25)
  AHI 1.02(1.01, 1.03)** 1.26(1.10, 1.44)* 1.04(0.95, 1.14) 1.09(1.01, 1.17)*
  LSpO2 1.01(0.98, 1.02) 0.93(0.95, 1.04) 1.04(0.99, 1.08) 1.02(0.99, 1.04)
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3. 讨论

我们的研究显示，MetS总患病率为60.76%（703例），MetS各组分（FG、WC、SBP、TG、HDL）中，超过诊断标准异常值的发生人数占比分别为[55.32%（640例）、36.73%（425例）、66.98%（775例）、49.87%（577例）和62.23%（720例）]。OSA严重程度的主要判别指标AHI和LSpO2均与MetS组分中的（FG、WC、SBP、TG）存在正剂量效应关系，与HDL呈负剂量反应关系。多元线性回归分析显示，WC、TG是影响OSA严重程度的主要评判指标AHI的独立危险因素，HDL为保护性因素。而MetS各组分中，仅WC是影响OSA严重程度的另一评判指标LSpO2的独立危险因素。中位随访时间42个月内，10.3% 的OSA患者发生了MACE。多因素Cox回归分析结果显示，高TG仍是MACE和需住院的不稳定心绞痛或心力衰竭的独立危险因素，高HDL是MACE和MI的保护性因素，SBP增加是心血管死亡的独立风险因素，WC增加是心血管死亡和需住院的不稳定心绞痛或心力衰竭的独立危险因素，且独立于AHI；相比之下，LSpO2未表现出与MACE及其组成事件发生风险的相关性。

一项荟萃分析显示，OSA患者的MetS风险的增加[16]。OSA与MetS的诊断参数SBP、TG的增高及HDL水平的降低有关[17]。Roche等[18]的研究发现，在青少年人群中，超过AHI阈值的OSA患者其MetS风险的综合评分更高。本研究基于以上研究基础，在老年OSA人群中发现AHI和LSpO2四分位水平与MetS各组分（FG、WC、SBP、TG）存在正剂量效应关系，与HDL水平呈负剂量反应关系。WC、SBP、TG是影响OSA严重程度指标AHI的独立危险因素，HDL为其保护性因素；WC是影响OSA严重程度的另一评判指标LSpO2的独立危险因素，提示在老年人群中，应尤其重视WC、SBP及TG水平的控制，出现异常值应给予及时治疗，同时也应关注有夜间血氧饱和下降表现且存在腹型肥胖的老年OSA患者。

睡眠期间的呼吸障碍与睡眠碎片化和间歇性缺氧相关，导致交感神经过度活跃和氧自由基的过度产生，该炎症级联反应与多种心脏代谢疾病的发生有关[19]。相比于非OSA患者，OSA患者患有MetS的可能性高出9.1倍；相反，MetS患者通常患有OSA[20]。OSA和MetS的重叠将导致患者的心血管风险增加，而心血管疾病的发生基础与自主神经功能障碍有关，包括交感神经的过度激活和压力反射的抑制，MetS可进一步刺激OSA患者交感神经的过度激活并降低压力反射的敏感性[21]。Cepeda等[22]的研究发现，与没有或轻度OSA的MetS患者相比，MetS和中度至重度OSA的共存患者交感迷走神经的失衡表现为运动后的心率恢复延迟，心血管疾病风险也更高，但该研究主要针对青中年患者，且研究设计类型为横断面分析，无法探讨OSA和MetS共存与心血管疾病风险的远期因果关系。我们的研究发现，高TG是MACE和需住院的不稳定心绞痛或心力衰竭的独立危险因素，高HDL是MACE和MI的保护性因素，SBP增加是心血管死亡的独立风险因素，WC增加是心血管死亡和需住院的不稳定心绞痛或心力衰竭的独立危险因素，且独立于AHI。此外，OSA是为最常见的睡眠呼吸障碍类型，AHI和LSpO2是判别OSA严重程度的主要临床指标[23-25]，我们的研究进一步发现，AHI与合并MetS组分老年人群的远期MACE及其组成事件中的心血管死亡和需住院的不稳定心绞痛和心力衰竭的发生风险有关，但与MI发生风险无关；相比之下，LSpO2对MACE及其所有组成事件的发生风险均未表现出相关性。分析其可能原因如下：（1）老年OSA患者的临床表现不一，多为症状重但临床表现轻，且除病因因素之外，老年OSA患者夜间睡眠习惯的差异对MetS的发生发展也可能产生不同的影响[26]，因而虽LSpO2衡量的夜间睡眠血氧饱和度综合水平作为评判OSA严重程度的有效指标之一，但在老年人群中，可能并未能监测出其夜间脉氧饱和度下降的真实情况，尤其是一夜的睡眠监测[27]；（2）老年人对间歇性缺氧具有适度耐受性[28]。本研究入组的老年OSA患者中，60~65岁的人群占比49.18%（569例），而这部分老年人相比于高龄老年人其机体代偿机制良好，且Mohananey等[29]的研究发现，老年OSA患者可通过缺血预处理代偿长期慢性间歇性缺氧而诱导的心肌缺血性损伤。因此，在老年人群中，未来需要更多的前瞻性队列研究进一步验证MetS各组分及OSA主要判别指标与远期MACE及其组成事件发生风险的相关性。

本研究存在一定局限性：（1）在结果分析中我们尽可能校正了较多的混杂因素，但不能排除其它潜在指标如降脂药、降压药物对于分析结局的影响[30]，因本研究纳入分析的部分研究对象自诉未坚持进行规律的药物治疗因而我们在混杂因素校正中未进行纳入；（2）本研究选取的是同一时间段的全样本，但最终纳入的研究样本中患有OSA的老年男性占比相对较高。而男性和女性的MetS特征可能有所不同；（3）所有纳入的研究对象的OSA确诊均通过统一标准的整夜PSG（>7 h），但一次监测可能不足以反映患者真实的睡眠状况；其次，便携PSG仪操作的复杂性、呼吸睡眠事件手动分析的标准性、需要严格的睡眠检测环境（医院睡眠中心）以及患者耐受度较低等因素均可能使结果产生一定的潜在偏倚。然而，这些局限并没有否定我们研究的价值。

综上所述，老年OSA患者的主要特征指标AHI和LSPO2与MetS各组分存在剂量效应关系，MetS中的部分组分与AHI可能相互作用增加MACE及其组成事件的发生风险；而MetS中的部分组分与LSPO2指标相互作用并未能增加老年OSA患者的MACE及其组成事件的风险。MetS的各诊断组分和老年OSA患者的特征性指标与心血管疾病的发生发展是一个极其复杂的病理过程，未来仍需大规模、多中心、前瞻性队列研究进行验证。

Biography

苏小凤，在读硕士研究生，E-mail: 1160359283@qq.com

Funding Statement

军队保健专项科研课题（19BJZ34）；解放军总医院军事医学青年项目（QNC19054）；国家老年疾病临床研究中心2018开放课题（NCRCG-PLAGH-2018008）；解放军总医院第二医学中心专项科研课题（ZXD2008）

Contributor Information

苏 小凤 (Xiaofeng SU), Email: 1160359283@qq.com.

刘 霖 (Lin LIU), Email: liulin715@qq.com.

References

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