多囊卵巢综合征患者糖脂代谢的临床研究
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摘要
研究背景
多囊卵巢综合征(polycystic ovary syndrome, PCOS)是育龄期女性最常见的内分泌紊乱性疾病,发生率4%～12%。PCOS临床表现多样,常见月经异常(稀发或闭经)、多毛、痤疮、肥胖、不孕等,远期并发症包括高血压、高血脂及心血管疾病、糖尿病(diabetes mellitus, DM)等。PCOS从青春期开始发病,不仅影响着机体内分泌和代谢,其肥胖和痤疮等表现更给患者带来了精神心理问题。既往的研究都表明,PCOS患者糖耐量异常(impaired glucose tolerance, IGT)和血脂紊乱发生率较高,病因尚未完全阐明,可能与肥胖、胰岛素抵抗和高雄激素血症有关。由于种族、生活方式及饮食习惯的差异,各国报道的糖耐量及血脂异常发生率不一,西方国家基本偏高,而亚洲各国则较低。越来越多的研究支持胰岛素抵抗是PCOS发病的中心环节的,其代谢异常与胰岛素抵抗有关,但也有研究认为代谢异常和肥胖、高雄激素血症的关系更密切。本研究对185例PCOS患者的临床资料进行了回顾性分析,期望进一步探讨中国PCOS患者糖耐量及血脂异常发生率及发病类型,并探讨糖耐量异常及血脂异常与胰岛素抵抗的关系,为更好地指导PCOS的治疗提供依据。
近年来随着代谢综合征(metabolic syndrome, MS)概念的提出,大部分国家均发现PCOS患者MS发生率较普通健康人群显著增加。代谢综合征以腹型肥胖为特征,伴有血糖、血脂、血压等异常,是糖尿病、动脉硬化相关疾病等的高发人群。研究发现,载脂蛋白(apolipoprotein, apo)与机体动脉粥样硬化风险关系较甘油三酯(triglyceride, TG)、总胆固醇(total cholesterol, TC)等更密切,尤其是apoB/apoA I比值在预测机体心血管疾病发病风险方面比其他任何血脂成分更可靠。本研究希望通过回顾性分析,探讨PCOS患者中MS的发生率以及apoB/apoA I比值对MS的诊断价值,为监测PCOS患者中MS的发病情况发现一个更敏感的指标。
第一章多囊卵巢综合征患者的糖脂代谢异常及其与胰岛素抵抗的关系
研究对象：
2008年11月至2012年11月因月经异常或不孕症初次就诊南方医科大学珠江医院妇产科门诊的患者；要求其就诊前3个月未服用任何影响体内激素、血糖及血脂的药物,符合2003年欧洲人类生殖和胚胎与美国生殖医学学会(ESHRE/ASRM)鹿特丹专家会议推荐的PCOS诊断标准。最后纳入具有完整资料的研究对象共185例,年龄16～41岁,平均26.82±4.30岁。
目的：
探索PCOS患者糖脂代谢异常的发生率及其与胰岛素抵抗的关系。
方法：
1.所有纳入对象均收集其病史(初潮年龄、月经史、婚育史、月经紊乱诱因等)及家族史。
2.测量身高、体重、血压、腰围、臀围,并计算体质指数(body mass index, BMI)和腰臀围比。
3.采集所有纳入对象月经周期或撤退性出血2-3天时的空腹静脉血,用免疫化学发光法(Beckman)测定雌二醇(E2)、卵泡刺激素(FSH)、黄体生成素(LH)、泌乳素(PRL)、睾酮(T)；采用日立-7600全自动分析仪分析血脂,包括总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、载脂蛋白B (apoB)和载脂蛋白AI (apoAI)。
4.于月经周期或撤退性出血的第4～5天,由有经验的B超医生行经阴道B超(无性生活史者行经肛门B超)检查。
5.口服葡萄糖耐量试验(oral glucose tolerance test, OGTT)及胰岛素释放试验(insulin release test, IRT):所有纳入对象禁食8～12h,于次日清晨空腹采血后,将83g普通葡萄糖粉(含一分子H2O)溶于250～300ml水中,5分钟内饮完。服第一口糖水开始计时,于服糖后1小时和2小时分别取血,测定各个时间点的血清葡萄糖水平(葡萄糖氧化酶法)和胰岛素水平(电化学发光法,罗氏公司提供)。根据空腹血糖(fasting plasma glucose, FPG)及空腹胰岛素(fasting insulin, FINS)数值计算稳态模式评估法-胰岛素抵抗指数(homeostasis model assessment-insulin resistance index, HOMA-IR)。
6.统计方法：采用SPSS19.0统计软件对数据进行分析,用Leneve检验方差齐性；计量资料描述用x±s表示,计数资料描述用绝对数(百分比)表示。两组间均值的比较采用独立样本t检验,率的比较用卡方检验；相关分析采用Pearson或Spearman相关分析。P<0.05为差异有统计学意义。
7.分组：
(1)根据2006年WHO糖尿病的诊断标准,将185例PCOS患者分为糖耐量正常组和糖耐量异常组,两组例数分别为148例及37例,比较两组相关因素的差异,并根据BMI和年龄分层分析糖耐量异常发病情况。
(2)根据2007年中国成人血脂异常防治指南,将185例PCOS患者分为血脂正常组和血脂异常组,两组例数分别为154例及31例,比较两组相关因素的差异,并根据BMI和年龄分层分析血脂异常的发病情况及发病类型。
(3)根据全国糖尿病协作组调查的数据,将HOMA-IR≥2.69定义为胰岛素抵抗(insulin resistance, IR),依此将185例PCOS患者分为胰岛素抵抗组和非胰岛素抵抗组,两组例数分别为50例及135例,比较两组糖耐量异常和血脂异常发生率的差异,分析糖耐量异常、血脂异常和胰岛素抵抗的相关性。
结果：
本研究对185例PCOS患者的临床资料进行了回顾性分析,结果如下：
1. PCOS患者糖耐量异常发生率为20.00%(37/185),其中糖耐量受损占17.84%(33/185),糖尿病占2.16%(4/185)。
2.糖耐量异常组年龄、BMI、腰臀围比、HOMA-IR、空腹胰岛素(FINS)、1h胰岛素(1h-INS)、2h胰岛素(2h-INS)的均值较糖耐量正常组的显著升高(P值分别为0.033、0.003、0.011、0.003、0.008、0.005和0.000),血压中的收缩压和舒张压、TC、TG、LDL-C和HDL-C的均值两组无显著差异(P值分别为0.068、0.053、0.919、0.512、0.527和0.485)。
3.根据BMI分层分析PCOS患者糖耐量异常情况,发现超重者(23≤BMI<25kg/m2)占17.30%(32/185),肥胖者(BMI≥25kg/m2)占20.54%(38/381)。PCOS患者糖耐量异常的发生率从BMI<18kg/m2层的20.83%增加到BMI≥28kg/m2层的55.56%,差异有统计学意义(χ2=16.711,P=0.002)。
4.按年龄分层分析PCOS患者糖耐量异常的情况,发现随着年龄增长,糖耐量异常的发生率从16～20岁年龄层的0.00%(0/9)增加到≥36岁年龄层的33.33%(2/6),差异有统计学意义(χ2=36.193,P=0.000)。
5.血脂异常总发生率为16.76%(31/185),其中TC升高占3.24%(6/185),TG升高占4.32%(8/185),LDL-C升高占2.16%(4/185),HDL-C降低占9.73%(18/185)。各组分按发生率由高到低分别是：HDL-C降低、TG升高、TC升高、LDL-C升高。
6.血脂异常组(31例)的BMI、腰臀比、收缩压、舒张压、空腹胰岛素、HOMA-IR的均值较血脂正常组(154例)显著升高(P值分别为0.000、0.005、0.001、0.005、0.023和0.014),而两组间年龄、空腹血糖、1h血糖、2h血糖、1h胰岛素和2h胰岛素的均值无显著差异(P值分别为0.606、0.139、0.522、0.113、0.127和0.278)。
7.按BMI分层比较血脂异常的发病情况,发现随着BMI的增长,PCOS患者血脂异常的总发生率从BMI<18kg/m2层的0.00%(0/24)增加到BMI≥28kg/m2层的33.33%(6/18),差异有统计学意义(χ2=14.072,P=0.007)。
8.按年龄分层比较血脂异常的情况,发现16～20岁年龄层及≥36岁年龄层的血脂异常发生率均较高,均为33.33%(3/9、2/6),各年龄层血脂异常发生率的差异无统计学意义(χ2=4.974,P=0.290)。
9.胰岛素抵抗的发生率为27.03%(50/185),胰岛素抵抗组的血脂异常和糖耐量异常总发生率分别为30.00%(15/50)和38.00%(19/50),非胰岛素抵抗组的则分别为11.85%(16/135)和13.33%(18/135)。胰岛素抵抗组血脂异常和糖耐量异常的总发生率较非胰岛素抵抗组的显著增加(χ2分别为8.615和13.875；P值均为0.000)。血脂异常各类型中,除了胰岛素抵抗组TG升高的发生率较非胰岛素抵抗组的显著增加外(χ2为5.335,P值为0.021),TC升高、HDL-C降低和LDL-C升高在两组发生率的差异均无统计学意义(χ2值分别为0.125、3.067和1.094；P值分别为0.724、0.080和0.296)。
10. HOMA-IR指数与BMI、腰围、空腹血糖、1h血糖、2h血糖、糖耐量异常、TG. LDL-C、血脂异常均呈正相关(相关系数r分别为0.590、0.547、0.356、0.279、0.422、0.281、0.286、0.146和0.239,P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.000、0.048和0.001),与HDL-C呈负相关(相关系数r为-0.268,P值为0.000),相关性有统计学意义(P<0.05)。HOMA-IR指数与TC的相关性无统计学意义(相关系数r为-0.022,P值为0.764)。
结论：
1.在本研究中,PCOS患者糖耐量异常发生率为20.00%,且随着BMI和年龄的增长,糖耐量异常发生率均显著增加。对临床中诊断PCOS的所有患者均应进行OGTT试验,早期对糖耐量异常患者进行干预(降低体重及利用降糖药物),可防止或延缓其向糖尿病的发展。
2. PCOS患者血脂异常发生率为16.76%,各类型按发生率由高到低分别是：HDL-C降低、TG升高、TC升高、LDL-C升高。
3.随着BMI的增长,PCOS患者血脂异常的发生率显著增加,肥胖可加重PCOS患者的脂代谢异常,控制体重是治疗PCOS患者脂代谢异常的首要目标。
4.本研究中青春期PCOS患者(16～20岁)与中年患者血脂异常发生率一样高,均为33.33%,这可能和青春期患者超重和肥胖发生率较高有关。对于临床中诊断的青春期PCOS患者,尤其是超重或肥胖者,应重视血脂异常的筛查。
5.本研究结果提示糖耐量异常和血脂异常均和胰岛素抵抗呈正相关,控制PCOS患者的胰岛素抵抗可能有助于糖脂代谢异常的纠正。
第二章apoB/apoA I比值对于多囊卵巢综合征患者发生代谢综合征的诊断价值
研究对象：
回顾性分析2008年11月至2012年11月因月经异常或不孕症初次就诊南方医科大学珠江医院妇产科门诊患者的临床资料；要求其就诊前3个月未服用任何影响体内激素、血糖及血脂的药物,符合2003年欧洲人类生殖和胚胎与美国生殖医学学会(ESHRE/ASRM)鹿特丹专家会议推荐的PCOS诊断标准。最后纳入具有完整资料的研究对象共185例,年龄16～41岁,平均26.82±4.30岁。(同第一部分)
目的：
探讨多囊卵巢综合征(PCOS)患者中代谢综合征(MS)的发生率及apoB/apoAI比值对PCOS患者发生MS的诊断价值。
方法：
1.所有纳入对象均收集病史(初潮年龄、月经史、婚育史、月经紊乱诱因等)及家族史；测量身高、体重、血压、腰围、臀围。
2.于月经周期或撤退性出血2-3天时采集空腹静脉血测定性激素及代谢指标(OGTT实验及胰岛素释放实验、血脂分析)；并于月经周期或撤退性出血4～5天时(闭经者可随机检查)行经阴道或经肛门B超检查。(同第一部分)。
3.统计学方法：采用SPSS19.0统计软件对数据进行分析,用Leneve检验方差齐性；计量资料描述用X±s表示,计数资料描述用绝对数(百分比)表示。两组间均值的比较采用独立样本t检验,多组均数的多重比较用one-way ANOVA,率的比较用卡方检验；相关分析采用Pearson或Spearman相关分析。用ROC曲线分析apoB/apoA I比值对PCOS患者发生代谢综合征的诊断价值,P<0.05有统计学意义。
4.分组：
(1)根据2005年国际糖尿病联盟(IDF)关于代谢综合征的诊断标准,将185例患者分为代谢综合征组和非代谢综合征组,两组例数分别为36例及149例,比较两组间相关指标的差异。
(2)按是否腹型肥胖和胰岛素抵抗(IR)分为四组：①非腹型肥胖非IR组：89例；②非腹型肥胖IR组：10例；③腹型肥胖非IR组：46例；④腹型肥胖IR组：40例。比较各组间apoB/apoA I均值的差异,探讨apoB/apoA I比值与PCOS各指标的相关性。
(3)根据代谢综合征异常组分的项数分为五组：①0项异常组：80例；②1项异常组：58例；③2项异常组：35例；④3项异常组：9例；⑤4项异常组：3例,比较各组间apoB/apoA I均值的差异,并利用ROC曲线分析apoB/apoAI比值对于PCOS合并代谢综合征的诊断价值。
结果：
本研究对185例PCOS患者的临床资料进行了回顾性分析,结果如下：
1. PCOS患者代谢综合征(MS)发生率为19.46%(36/185),至少有一项MS组分异常的有56.76%(105/185)。代谢综合征组的BMI、腰围、腰臀围比、收缩压、舒张压、空腹血糖、空腹胰岛素、1h血糖、1h胰岛素、2h血糖、2h胰岛素、HOMA-IR、TG、LDL-C、apoB及apoB/apoA I的均值较非代谢综合征组的显著升高(P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.000、0.012、0.014、0.000、0.040、0.000、0.000、0.010、0.000和0.000),HDL-C、 apoA I显著降低(P值分别为0.000和0.000),两组间的年龄、TC均值的差异没有统计学意义(P值分别为0.398和0.393)。
2. apoB/apoA I比值与BMI、腰围、腰臀围比、血压、HOMA-IR、TC、TG、 LDL-C呈正相关(相关系数r分别为0.469、0.415、0.411、0.317、0.219、0.285和0.292,P值均为0.000),与HDL-C呈负相关(相关系数r为-0.465,P值为0.000),均具有统计学意义(P<0.05),与年龄及卵巢平均体积的相关性无统计学意义(相关系数r分别为0.010和-0.062,P值分别为0.889和0.398)。
3.按是否腹型肥胖和胰岛素抵抗(IR)分组,经过Levene检验显示apoB/apoA I比值方差齐性(F=0.544,P=-0.653),各组apoB/apoA I均数的多重比较用one-way ANOVA (LSD法),结果显示1组和3组、1组和4组、2组和3组、2组和4组的apoB/apoA I均值差异均具有统计学意义(P值分别为0.000、0.000、0.049和0.015),1组和2组、3组和4组的apoB/apoA I均值差异则无统计学意义(P值分别为0.918和0.428)。
4.根据代谢综合征异常组分项数分组,经过Levene检验显示apoB/apoA I比值方差齐性(F=1.545,P=0.191),各组apoB/apoA I均数的多重比较用one-way ANOVA (LSD法),结果显示0项异常组和2项异常组、0项异常组和3项异常组、0项异常组和4项异常组、1项异常组和2项异常组、1项异常组和3项异常组、1项异常组和4项异常组、2项异常组和3项异常组、2项异常组和4项异常组、3项异常组和4项异常组的apoB/apoA I均值差异均具有统计学意义(P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.009、0.000和0.007)；0项异常组和1项异常组的apoB/apoA I均值差异则无统计学意义(P值为0.250)。
5.在PCOS患者中,当截断值为0.66时,apoB/apoA I对代谢综合征的诊断价值最大：ROC曲线下面积为0.885,敏感度和特异性分别为0.917和0.700。
结论：
1.本研究中,PCOS患者代谢综合征发生率为19.46%,且有超过一半的患者至少有一项代谢综合征组分异常,将来可能发展为代谢综合征。代谢综合征是糖尿病及心血管疾病的高发人群,因此,重视PCOS患者代谢异常的筛查并及时进行干预,对于减少PCOS患者出现远期并发症有重要意义。
2. apoB/apoAⅠ比值均值随着代谢综合征异常组分项数的增多而增加,与其关系密切。
3. apoB/apoAⅠ比值对代谢综合征有较好的诊断价值。对于临床中未达到代谢综合征的诊断标准而apoB/apoAⅠ比值超过0.66的PCOS患者,应警惕代谢综合征的发生,宜及时采取相应的干预措施。
Background and Objective:Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age, whose incidence is4%-12%. The clinical manifestations of PCOS are various, for example abnormal menstruation (oligomenorrhea or amenorrhea), hirsutism, acne, obesity, infertility and so on. Long term complications include hypertension, hyperlipidemia, diabetes and cardiovascular disease. PCOS starts from adolescence, not only affects the body endocrine and metabolism, but also brought psychological problems to the patients. Previous studies have shown that the incidence of dyslipidemia and impaired glucose tolerance (IGT) is higher in patients with PCOS than normal people. The cause has not yet fully elucidated, and may be associated with obesity, insulin resistance and hyperandrogenism. Because of the differences in race, life style and dietary habit, the incidence of IGT and dyslipidemia is varied in different countries. Basically, western countries'is higher while Asian countries'is lower. A growing number of studies support that insulin resistance is the key pathogenesis of PCOS, metabolic abnormalities are associated with it. But there are also studies consider that metabolic abnormalities have a more close relationship with obesity or hyperandrogenism. In this study, we further explore the incidence and type of dyslipidemia and abnormal glucose tolerance in Chinese PCOS patients through, and the related factors of glucose and dyslipidemia, hoping to provide better guidance for the treatment of PCOS.
In recent years, metabolic syndrome (MS) is getting more and more concerning. Most countries have found that the incidence of MS in PCOS patients increased significantly than normal healthy people. MS is characterized by the central obesity, along with abnormal blood glucose, blood lipid and blood pressure. People diagnosed with this syndrome are at a high risk of getting diabetes, atherosclerosis related diseases. Some studys have found that apolipoprotein (apo) has a closer relation with atherosclerosis disease than triglyceride(TG) or total cholesterol (TC), especially the apoB/apoA I ratio is better than any other lipid components in the prediction of cardiovascular disease. This study aims to explore the incidence of MS and the value of apoB/apoA I ratio in diagnosting MS in PCOS patients.
Chapter I The glucose and lipid metabolism in patients with polycystic ovary syndrome and their relationship with insulin resistance
Objects:185patients were included in this study, who visited the outpatient of obstetrics and gynecology department in Zhujiang Hospital of Southern Medical University for the first time in November2008to November2012, and had not taking any drugs that affected the hormones, plasma glucose and lipid in the recent3monthes before the diagnosis, and conformed to the2003Rotterdam diagnostic criteria of PCOS.
Objectives:to explore the incidence of abnormal glucose and lipid metabolism in PCOS patients and their relationships with insulin resistance.
Methods:
1. All included patients were gathered the medical history (menarche age, menstrual history, past marital and fertile history, incentives of menstrual disorders, etc.), and family history.
2. Measured the height, weight, blood pressure, waist circumference, hip circumference, and calculated the BMI (body mass index, BMI) and waist-to-hip ratio.
3. Fasting venous blood was collected on the second or third day of menstrual cycle or withdrawal bleeding, being used to detect the concentration of estradiol (E2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), testosterone (T) and blood lipid, including total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), apolipoprotein B (apoB) and apolipoprotein A I (apoA I).
4. B-ultrasonic examination was performed on the fourth or fifth day of the menstrual cycle or withdrawal bleeding by specific ultrasound doctors.
5. Oral glucose tolerance test (OGTT) and insulin release test (IRT):every included object fasted for8-12hours, and fasting blood was collected in the next morning. Then solubled83g normal glucose powder (containing a H2O molecule) in250-300ml water and drinked it off in5minutes. Timing started when the first bite of sugar water was taked. Blood samples were taken on the first hour and the second hour after taking the sugar water. The serum glucose and insulin levels were detected in all the blood samples. The homeostasis model assessment-insulin resistance (HOMA-IR) index was calculated using the values of fasting glucose (FPG) and fasting insulin (FINS).
6. Statistical methods:SPSS19.0statistical software was used to analyze the datas. The homogeneity of variance was tested with Leneve. The measurement data was described with x±s, and the enumeration data was described with absolute terms (percentage). Comparison between two groups was done with independent sample T-test and chi-square test. Correlation analysis was done with Pearson or Spearman. Difference was statistically significant with P<0.050.
7. Groups:
(1) According to the WHO diagnostic criteria for diabetes in2006,185patients with PCOS were divided into normal glucose tolerance group (NGT) and the abnormal glucose tolerance group (AGT). Cases of the two groups were148and37respectively. The differences of related factors between the two groups were compared, and stratified analysis of the incidences of abnormal glucose tolerance according to BMI and age were also done.
(2) According to a dyslipidemia prevention guideline for Chinese adults in2007,185patients with PCOS were divided into normal blood lipids group and dyslipidemia group. Cases of the two groups were154and31respectively. The differences of related factors between the two groups were compared, and stratified analysis of the incidences of dyslipidemia according to BMI and age were also done.
(3) According to the data of the national diabetes cooperation investigation, insulin resistance was defined as the HOMA-IR greater than or equal to2.69.185PCOS patients were divided into non-insulin resistant group and insulin resistant group. Cases of the two groups were135and50respectively. The incidences of dyslipidemia and abnormal glucose tolerance of the two groups were compared, and the correlations of dyslipidemia and abnormal glucose tolerance with insulin resistance were also analyzed.
Results:
1. In this study, we found that80.00%(148/185) of all the185PCOS patients had normal glucose tolerance (NGT), while20%of them had IGT and DM:IGT17.84%(33/185) and DM2.16%(4/185).
2. The mean values of age, BMI, waist hip ratio, HOMA IR, fasting insulin (FINS),2h-INS were higher in abnormal glucose tolerance(AGT) group (37cases) than in NGT group (148cases), the difference was statistically significant (P<0.05); the mean values of LH, T, systolic pressure, diastolic blood pressure and blood lipid levels had no obvious difference.
3. Stratified analysis of abnormal glucose tolerance (AGT) according to BMI were performed and we found that overweight people (23≤BMI<25kg/m2) accounted for17.30%(32/185) in all the patients, while overweight people (BMI>25kg/m2) accounted for20.54%(38/381). Along with the increase of BMI, the incidence of increased significantly, from20.83%in the BMI<18kg/m2layer to55.56%in the BMI≥28kg/m2layer.
4. Stratified analysis of abnormal glucose tolerance (AGT) according to age were also performed and we found that And we found that, as the growth of the age, the incidence of AGT increased significantly, form0.00%in the16～20years-old layer to33.33%in the≥36years-old layer.
5. In this study, the total incidence of dyslipidemia was16.76%(31/185), in which the TC abnormality was3.24%(6/185), TG abnormality was4.32%(8/185), LDL-C abnormal accounted for2.16%(4/185), HDL-C accounted for9.73%(18/185). The incidences from high to low were:low HDL-C, high TG, high TC, and high LDL-C.
6. The mean values of BMI, waist-to-hip ratio, systolic blood pressure, diastolic blood pressure, fasting insulin, HOMA-IR and apoB/apoA I in dyslipidemia group (31cases) were significantly elevated than that in the nomal blood lipid group, while the mean values of age, LH, T, fasting plasma glucose, fasting insulin,2h-glucose and2h-insulin had no obvious difference between the two groups.
7. Stratified analysis of dyslipidemia according to BMI were performed, and we found that along with the increase of BMI, the incidence of dyslipidemia PCOS patients increased significantly, from0.00%in the BMI<18kg/m2layer to33.33%in the BMI≥28kg/m2layer.
8. Stratified analysis of dyslipidemia according to age was also performed, and we found that the incidence of dyslipidemia in the16-20years-old layer was the same with that in the>36years-old layer (33.33%).
9. The incidence of insulin resistance was27.03%(50/185), the incidences of dyslipidemia and abnormal glucose tolerance of the insulin resistant group were30.00%(15/50) and38.00%(19/50) respectively, while those of the non-insulin resistant group were11.85%(16/135) and13.33%(18/135) respectively. The total incidence of dyslipidemia and abnormal glucose tolerance of the insulin resistant group increased significantly than the non-insulin resistant group (chi-square values were8.615and8.615respectively; P values all were0.000). The incidence of higher TG in the insulin resistant group increased significantly than that in the non-insulin resistant group (chi-square value was5.335, P value was0.021), while the differences of incidences of higher TC, lower HDL-C and higher LDL-C between the two groups had no statistical significance (chi-square values were0.125,3.067and0.125respectively; P values were0.724,0.080and0.296respectively).
10. HOMA-IR index had a positive correlation with BMI, waist circumference, fasting plasma glucose,1h-glucose,2h-glucose, TG, LDL-C, abnormal glucose tolerance and dyslipidemia (correlation coefficients r values were0.590,0.547,0.356,0.279,0.422,0.281,0.286,0.146and0.239respectively, and P values were0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000and0.001respectively), while a negative correlation with HDL-C (correlation coefficient r values were0.268, and P value was0.000). The correlation with TC had no statistical significance (correlation coefficient r value was0.022, and P value was0.764).
Conclusion:
1. In this study, the incidence of abnormal glucose tolerance patients with PCOS was20.00%, and increased significantly as BMI and age rose. All the PCOS patients in the clinical should have an OGTT experiment, and early intervention should carry out in patients with abnormal glucose tolerance (for example, weight loss or using hypoglycemic drugs) to prevent or delay the development of diabetes.
2. The incidence of dyslipidemia was16.76%, the incidence of each type from high to low were:lower HDL-C, higher TG, higher TC, and higher LDL-C.
3. The incidence of dyslipidemia in PCOS patients increased significantly along with the rise of BMI. Obesity might worsen the lipid metabolism in PCOS patients, and weight control was he primary goal of the treatment of dyslipidemia in PCOS patients.
4. In our study, the incidence of dyslipidemia in adolescent PCOS patients was the same with that of the middle-aged patients, all were33.33%. That may be related to high incidence of overweight and obesity in adolescent patients. Attentions should be pay to screening of dyslipidemia in adolescent PCOS patients, especially overweight or obese patients.
5. Our study found out that insulin resistance had a positive correlation with abnormal glucose tolerance and dyslipidemia. Improvement of insulin resistance may be helpful in correcting the abnormal glucose and lipid metabolism in PCOS patients.
Chapter II Diagnostic value of apoB/apoA I ratio for metabolic syndrome in patients with polycystic ovary syndrome
Objects:185patients were included in this study, who visited the outpatient of obstetrics and gynecology department in Zhujiang Hospital of Southern Medical University for the first time in November2008to November2012, and had not taking any drugs that affected the hormones, plasma glucose and lipid in the recent3monthes before the diagnosis, and conformed to the2003Rotterdam diagnostic criteria of PCOS.(The same with the first chapter)
Objectives:to explore the incidence of metabolic syndrome (MS) and the diagnostic value of apoB/apoAⅠ ratio for metabolic syndrome in patients with polycystic ovary syndrome (PCOS).
Methods:
1. All included patients were gathered the medical history (menarche age, menstrual history, past marital and fertile history, incentives of menstrual disorders, etc.), and family history. Measured the height, weight, blood pressure, waist circumference, hip circumference, and calculated the BMI (body mass index, BMI) and waist-to-hip ratio.
2. Fasting venous blood was collected on the second or third day of menstrual cycle or withdrawal bleeding, being used to detect the concentration of sex hormones and metabolism indexes.
3. B-ultrasonic examination was performed on the fourth or fifth day of the menstrual cycle or withdrawal bleeding by specific ultrasound doctors.
4. Statistical methods:SPSS19.0statistical software was used to analyze the datas. The homogeneity of variance was tested with Leneve. The measurement data was described with x±s, and the enumeration data was described with absolute terms (percentage). Comparison between two groups was done with independent sample T-test and chi-square test, and multiple comparisons with one-way ANOVA. Correlation analysis was done with Pearson or Spearman. Using ROC curve analyzed the diagnostic value of apoB/apoAⅠ ratio for metabolic syndrome. Difference was statistically significant with P<0.050.
5. Groups:
(1) According to the international diabetes federation (IDF) diagnostic criteria of for metabolic syndrome in2005,185patients were divided into the metabolic syndrome and non-metabolic syndrome group. Cases of the two groups were148and37respectively. The differences of related factors between the two groups were compared.
(2) According to whether abdominal obesity and insulin resistance (IR) or not,185patients were divided into four groups:l=not abdominal obesity not IR group,2=not abdominal obesity and IR group,3=abdominal obesity not IR group,4=abdominal obesity IR group. Cases of the four groups were89,10,46and40respectively. The mean values of apoB/apoA I ratio were compared among the for groups, and the correlation between the apoB/apoA I ratio and some indexes of PCOS was exploded.
(3) According to the numbers of abnormal metabolic syndrome components,185patients were divided into five groups:0group,1group,2group,3group,4group and5group. Cases of the five groups were80,58,35,9and3respectively. The mean values of apoB/apoA I ratio were compared among the for groups, and the diagnostic value of apoB/apoA I ratio for metabolic syndrome was exploded by using ROC curve.
Results:
1. In this study, we found that the morbidity of MS was19.46%in all the185PCOS patients, and56.76%of them had at least one abnormal components of MS. The mean values of BMI, waist circumference, waist-to-hip ratio, systolic blood pressure and diastolic blood pressure, fasting glucose, fasting insulin,1h glucose,1h insulin,2h glucose,2h insulin, HOMA-IR, TG, LDL-C, apoB and apoB/apoA I of MS group were significantly higher than those of the non-MS group (P values were0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.012,0.014,0.000,0.040,0.000,0.000,0.010,0.000and0.000respectively); while HDL-C and apoA I decreased significantly (P values were0.000and0.000respectively). The mean values of age and TC between the two groups had no statistical significance (P values were0.398and0.393respectively).
2. ApoB/apoA I ratio was positively correlated with BMI, waist circumference, waist-to-hip ratio, blood pressure, fasting glucose, HOMA IR, TG and LDL-C (correlation coefficients r values were0.469,0.415,0.411,0.317,0.219,0.285and0.292respectively, and P values all were0.000), and negatively correlated with HDL-C (correlation coefficients r values was-0.465, and P values was0.000), all statistically significant (P<0.05). But the correlation of age and ovarian volume had no statistical significance (correlation coefficients r values were0.010and-0.062respectively, and P values were0.889and0.398respectively).
3. All patients were divided into four groups according to whether they had abdominal obesity and IR. Levene test showed that the homogeneity of variances of had no statistical significance (F=0.544, P=0.544), and we found that the differences of averages of apoB/apoA I ratio between group1and3, group1and4, group2and4were all statistically significant (P values were0.000,0.000,0.049and0.015), while the differences of averages between group1and2, group3and4had no statistical significance (P values were0.918and0.428respectively).
4. According to the numbers of abnormal metabolic syndrome components,185patients were divided into five groups, Levene test showed that the homogeneity of variances of apoB/apoA I ratio had no statistical significance (F=0.544, P=0.544), multiple comparisons among five groups were done with one-way ANOVA. We found that the differences of averages of apoB/apoA I ratio between group0and2, group0and3, group0and4, group1and2, group1and3, group2and3, group2and4, group3and4were all statistically significant (P values were0.000,0.000,0.000,0.000,0.000,0.000,0.009,0.000and0.007respectively), while the differences of averages between group0and1had no statistical significance (P values was0.250).
5. Using the receiver operating characteristics (ROC) curve to analysis the diagnostic value of apoB/apoA I ratio for MS in PCOS patients, we found that when the cutoff value of apoB/apoA I was0.66, the area under the ROC curve was the biggest (0.885), with a sensitivity of0.917and specificity of0.700.
Conclusion:
1. In this study, the incidence of metabolic syndrome in PCOS patients was 19.46%, and more than half of the patients had at least one abnormal components of the metabolic syndrome, who were likely to develop metabolic syndrome in the future. Patients diagnosed with metabolic syndrome were at a higher risk of developing diabetes and cardiovascular disease. Therefore, it has important significance to attach great importance in screening of metabolic abnormalities in patients with PCOS and carrying out timely intervention soon afterwards.
2. The average of apoB/apoA I ratio rose as the number of abnormal metabolic syndrome components increased, that means it had a close relationship with metabolic syndrome.
3. ApoB/apoA I ratio had a good diagnostic value for metabolic syndrome. Those PCOS patients, who did not meet the diagnostic criteria for metabolic syndrome but the apoB/apoA I ratio was more than0.66, should be alert to the occurrence of the metabolic syndrome, and should take appropriate intervention measures in a timely manner.
多囊卵巢综合征(polycystic ovary syndrome, PCOS)是育龄期女性最常见的内分泌紊乱性疾病,发生率4%～12%。PCOS临床表现多样,常见月经异常(稀发或闭经)、多毛、痤疮、肥胖、不孕等,远期并发症包括高血压、高血脂及心血管疾病、糖尿病(diabetes mellitus, DM)等。PCOS从青春期开始发病,不仅影响着机体内分泌和代谢,其肥胖和痤疮等表现更给患者带来了精神心理问题。既往的研究都表明,PCOS患者糖耐量异常(impaired glucose tolerance, IGT)和血脂紊乱发生率较高,病因尚未完全阐明,可能与肥胖、胰岛素抵抗和高雄激素血症有关。由于种族、生活方式及饮食习惯的差异,各国报道的糖耐量及血脂异常发生率不一,西方国家基本偏高,而亚洲各国则较低。越来越多的研究支持胰岛素抵抗是PCOS发病的中心环节的,其代谢异常与胰岛素抵抗有关,但也有研究认为代谢异常和肥胖、高雄激素血症的关系更密切。本研究对185例PCOS患者的临床资料进行了回顾性分析,期望进一步探讨中国PCOS患者糖耐量及血脂异常发生率及发病类型,并探讨糖耐量异常及血脂异常与胰岛素抵抗的关系,为更好地指导PCOS的治疗提供依据。
近年来随着代谢综合征(metabolic syndrome, MS)概念的提出,大部分国家均发现PCOS患者MS发生率较普通健康人群显著增加。代谢综合征以腹型肥胖为特征,伴有血糖、血脂、血压等异常,是糖尿病、动脉硬化相关疾病等的高发人群。研究发现,载脂蛋白(apolipoprotein, apo)与机体动脉粥样硬化风险关系较甘油三酯(triglyceride, TG)、总胆固醇(total cholesterol, TC)等更密切,尤其是apoB/apoA I比值在预测机体心血管疾病发病风险方面比其他任何血脂成分更可靠。本研究希望通过回顾性分析,探讨PCOS患者中MS的发生率以及apoB/apoA I比值对MS的诊断价值,为监测PCOS患者中MS的发病情况发现一个更敏感的指标。
第一章多囊卵巢综合征患者的糖脂代谢异常及其与胰岛素抵抗的关系
研究对象：
2008年11月至2012年11月因月经异常或不孕症初次就诊南方医科大学珠江医院妇产科门诊的患者；要求其就诊前3个月未服用任何影响体内激素、血糖及血脂的药物,符合2003年欧洲人类生殖和胚胎与美国生殖医学学会(ESHRE/ASRM)鹿特丹专家会议推荐的PCOS诊断标准。最后纳入具有完整资料的研究对象共185例,年龄16～41岁,平均26.82±4.30岁。
目的：
探索PCOS患者糖脂代谢异常的发生率及其与胰岛素抵抗的关系。
方法：
1.所有纳入对象均收集其病史(初潮年龄、月经史、婚育史、月经紊乱诱因等)及家族史。
2.测量身高、体重、血压、腰围、臀围,并计算体质指数(body mass index, BMI)和腰臀围比。
3.采集所有纳入对象月经周期或撤退性出血2-3天时的空腹静脉血,用免疫化学发光法(Beckman)测定雌二醇(E2)、卵泡刺激素(FSH)、黄体生成素(LH)、泌乳素(PRL)、睾酮(T)；采用日立-7600全自动分析仪分析血脂,包括总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、载脂蛋白B (apoB)和载脂蛋白AI (apoAI)。
4.于月经周期或撤退性出血的第4～5天,由有经验的B超医生行经阴道B超(无性生活史者行经肛门B超)检查。
5.口服葡萄糖耐量试验(oral glucose tolerance test, OGTT)及胰岛素释放试验(insulin release test, IRT):所有纳入对象禁食8～12h,于次日清晨空腹采血后,将83g普通葡萄糖粉(含一分子H2O)溶于250～300ml水中,5分钟内饮完。服第一口糖水开始计时,于服糖后1小时和2小时分别取血,测定各个时间点的血清葡萄糖水平(葡萄糖氧化酶法)和胰岛素水平(电化学发光法,罗氏公司提供)。根据空腹血糖(fasting plasma glucose, FPG)及空腹胰岛素(fasting insulin, FINS)数值计算稳态模式评估法-胰岛素抵抗指数(homeostasis model assessment-insulin resistance index, HOMA-IR)。
6.统计方法：采用SPSS19.0统计软件对数据进行分析,用Leneve检验方差齐性；计量资料描述用x±s表示,计数资料描述用绝对数(百分比)表示。两组间均值的比较采用独立样本t检验,率的比较用卡方检验；相关分析采用Pearson或Spearman相关分析。P<0.05为差异有统计学意义。
7.分组：
(1)根据2006年WHO糖尿病的诊断标准,将185例PCOS患者分为糖耐量正常组和糖耐量异常组,两组例数分别为148例及37例,比较两组相关因素的差异,并根据BMI和年龄分层分析糖耐量异常发病情况。
(2)根据2007年中国成人血脂异常防治指南,将185例PCOS患者分为血脂正常组和血脂异常组,两组例数分别为154例及31例,比较两组相关因素的差异,并根据BMI和年龄分层分析血脂异常的发病情况及发病类型。
(3)根据全国糖尿病协作组调查的数据,将HOMA-IR≥2.69定义为胰岛素抵抗(insulin resistance, IR),依此将185例PCOS患者分为胰岛素抵抗组和非胰岛素抵抗组,两组例数分别为50例及135例,比较两组糖耐量异常和血脂异常发生率的差异,分析糖耐量异常、血脂异常和胰岛素抵抗的相关性。
结果：
本研究对185例PCOS患者的临床资料进行了回顾性分析,结果如下：
1. PCOS患者糖耐量异常发生率为20.00%(37/185),其中糖耐量受损占17.84%(33/185),糖尿病占2.16%(4/185)。
2.糖耐量异常组年龄、BMI、腰臀围比、HOMA-IR、空腹胰岛素(FINS)、1h胰岛素(1h-INS)、2h胰岛素(2h-INS)的均值较糖耐量正常组的显著升高(P值分别为0.033、0.003、0.011、0.003、0.008、0.005和0.000),血压中的收缩压和舒张压、TC、TG、LDL-C和HDL-C的均值两组无显著差异(P值分别为0.068、0.053、0.919、0.512、0.527和0.485)。
3.根据BMI分层分析PCOS患者糖耐量异常情况,发现超重者(23≤BMI<25kg/m2)占17.30%(32/185),肥胖者(BMI≥25kg/m2)占20.54%(38/381)。PCOS患者糖耐量异常的发生率从BMI<18kg/m2层的20.83%增加到BMI≥28kg/m2层的55.56%,差异有统计学意义(χ2=16.711,P=0.002)。
4.按年龄分层分析PCOS患者糖耐量异常的情况,发现随着年龄增长,糖耐量异常的发生率从16～20岁年龄层的0.00%(0/9)增加到≥36岁年龄层的33.33%(2/6),差异有统计学意义(χ2=36.193,P=0.000)。
5.血脂异常总发生率为16.76%(31/185),其中TC升高占3.24%(6/185),TG升高占4.32%(8/185),LDL-C升高占2.16%(4/185),HDL-C降低占9.73%(18/185)。各组分按发生率由高到低分别是：HDL-C降低、TG升高、TC升高、LDL-C升高。
6.血脂异常组(31例)的BMI、腰臀比、收缩压、舒张压、空腹胰岛素、HOMA-IR的均值较血脂正常组(154例)显著升高(P值分别为0.000、0.005、0.001、0.005、0.023和0.014),而两组间年龄、空腹血糖、1h血糖、2h血糖、1h胰岛素和2h胰岛素的均值无显著差异(P值分别为0.606、0.139、0.522、0.113、0.127和0.278)。
7.按BMI分层比较血脂异常的发病情况,发现随着BMI的增长,PCOS患者血脂异常的总发生率从BMI<18kg/m2层的0.00%(0/24)增加到BMI≥28kg/m2层的33.33%(6/18),差异有统计学意义(χ2=14.072,P=0.007)。
8.按年龄分层比较血脂异常的情况,发现16～20岁年龄层及≥36岁年龄层的血脂异常发生率均较高,均为33.33%(3/9、2/6),各年龄层血脂异常发生率的差异无统计学意义(χ2=4.974,P=0.290)。
9.胰岛素抵抗的发生率为27.03%(50/185),胰岛素抵抗组的血脂异常和糖耐量异常总发生率分别为30.00%(15/50)和38.00%(19/50),非胰岛素抵抗组的则分别为11.85%(16/135)和13.33%(18/135)。胰岛素抵抗组血脂异常和糖耐量异常的总发生率较非胰岛素抵抗组的显著增加(χ2分别为8.615和13.875；P值均为0.000)。血脂异常各类型中,除了胰岛素抵抗组TG升高的发生率较非胰岛素抵抗组的显著增加外(χ2为5.335,P值为0.021),TC升高、HDL-C降低和LDL-C升高在两组发生率的差异均无统计学意义(χ2值分别为0.125、3.067和1.094；P值分别为0.724、0.080和0.296)。
10. HOMA-IR指数与BMI、腰围、空腹血糖、1h血糖、2h血糖、糖耐量异常、TG. LDL-C、血脂异常均呈正相关(相关系数r分别为0.590、0.547、0.356、0.279、0.422、0.281、0.286、0.146和0.239,P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.000、0.048和0.001),与HDL-C呈负相关(相关系数r为-0.268,P值为0.000),相关性有统计学意义(P<0.05)。HOMA-IR指数与TC的相关性无统计学意义(相关系数r为-0.022,P值为0.764)。
结论：
1.在本研究中,PCOS患者糖耐量异常发生率为20.00%,且随着BMI和年龄的增长,糖耐量异常发生率均显著增加。对临床中诊断PCOS的所有患者均应进行OGTT试验,早期对糖耐量异常患者进行干预(降低体重及利用降糖药物),可防止或延缓其向糖尿病的发展。
2. PCOS患者血脂异常发生率为16.76%,各类型按发生率由高到低分别是：HDL-C降低、TG升高、TC升高、LDL-C升高。
3.随着BMI的增长,PCOS患者血脂异常的发生率显著增加,肥胖可加重PCOS患者的脂代谢异常,控制体重是治疗PCOS患者脂代谢异常的首要目标。
4.本研究中青春期PCOS患者(16～20岁)与中年患者血脂异常发生率一样高,均为33.33%,这可能和青春期患者超重和肥胖发生率较高有关。对于临床中诊断的青春期PCOS患者,尤其是超重或肥胖者,应重视血脂异常的筛查。
5.本研究结果提示糖耐量异常和血脂异常均和胰岛素抵抗呈正相关,控制PCOS患者的胰岛素抵抗可能有助于糖脂代谢异常的纠正。
第二章apoB/apoA I比值对于多囊卵巢综合征患者发生代谢综合征的诊断价值
研究对象：
回顾性分析2008年11月至2012年11月因月经异常或不孕症初次就诊南方医科大学珠江医院妇产科门诊患者的临床资料；要求其就诊前3个月未服用任何影响体内激素、血糖及血脂的药物,符合2003年欧洲人类生殖和胚胎与美国生殖医学学会(ESHRE/ASRM)鹿特丹专家会议推荐的PCOS诊断标准。最后纳入具有完整资料的研究对象共185例,年龄16～41岁,平均26.82±4.30岁。(同第一部分)
目的：
探讨多囊卵巢综合征(PCOS)患者中代谢综合征(MS)的发生率及apoB/apoAI比值对PCOS患者发生MS的诊断价值。
方法：
1.所有纳入对象均收集病史(初潮年龄、月经史、婚育史、月经紊乱诱因等)及家族史；测量身高、体重、血压、腰围、臀围。
2.于月经周期或撤退性出血2-3天时采集空腹静脉血测定性激素及代谢指标(OGTT实验及胰岛素释放实验、血脂分析)；并于月经周期或撤退性出血4～5天时(闭经者可随机检查)行经阴道或经肛门B超检查。(同第一部分)。
3.统计学方法：采用SPSS19.0统计软件对数据进行分析,用Leneve检验方差齐性；计量资料描述用X±s表示,计数资料描述用绝对数(百分比)表示。两组间均值的比较采用独立样本t检验,多组均数的多重比较用one-way ANOVA,率的比较用卡方检验；相关分析采用Pearson或Spearman相关分析。用ROC曲线分析apoB/apoA I比值对PCOS患者发生代谢综合征的诊断价值,P<0.05有统计学意义。
4.分组：
(1)根据2005年国际糖尿病联盟(IDF)关于代谢综合征的诊断标准,将185例患者分为代谢综合征组和非代谢综合征组,两组例数分别为36例及149例,比较两组间相关指标的差异。
(2)按是否腹型肥胖和胰岛素抵抗(IR)分为四组：①非腹型肥胖非IR组：89例；②非腹型肥胖IR组：10例；③腹型肥胖非IR组：46例；④腹型肥胖IR组：40例。比较各组间apoB/apoA I均值的差异,探讨apoB/apoA I比值与PCOS各指标的相关性。
(3)根据代谢综合征异常组分的项数分为五组：①0项异常组：80例；②1项异常组：58例；③2项异常组：35例；④3项异常组：9例；⑤4项异常组：3例,比较各组间apoB/apoA I均值的差异,并利用ROC曲线分析apoB/apoAI比值对于PCOS合并代谢综合征的诊断价值。
结果：
本研究对185例PCOS患者的临床资料进行了回顾性分析,结果如下：
1. PCOS患者代谢综合征(MS)发生率为19.46%(36/185),至少有一项MS组分异常的有56.76%(105/185)。代谢综合征组的BMI、腰围、腰臀围比、收缩压、舒张压、空腹血糖、空腹胰岛素、1h血糖、1h胰岛素、2h血糖、2h胰岛素、HOMA-IR、TG、LDL-C、apoB及apoB/apoA I的均值较非代谢综合征组的显著升高(P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.000、0.012、0.014、0.000、0.040、0.000、0.000、0.010、0.000和0.000),HDL-C、 apoA I显著降低(P值分别为0.000和0.000),两组间的年龄、TC均值的差异没有统计学意义(P值分别为0.398和0.393)。
2. apoB/apoA I比值与BMI、腰围、腰臀围比、血压、HOMA-IR、TC、TG、 LDL-C呈正相关(相关系数r分别为0.469、0.415、0.411、0.317、0.219、0.285和0.292,P值均为0.000),与HDL-C呈负相关(相关系数r为-0.465,P值为0.000),均具有统计学意义(P<0.05),与年龄及卵巢平均体积的相关性无统计学意义(相关系数r分别为0.010和-0.062,P值分别为0.889和0.398)。
3.按是否腹型肥胖和胰岛素抵抗(IR)分组,经过Levene检验显示apoB/apoA I比值方差齐性(F=0.544,P=-0.653),各组apoB/apoA I均数的多重比较用one-way ANOVA (LSD法),结果显示1组和3组、1组和4组、2组和3组、2组和4组的apoB/apoA I均值差异均具有统计学意义(P值分别为0.000、0.000、0.049和0.015),1组和2组、3组和4组的apoB/apoA I均值差异则无统计学意义(P值分别为0.918和0.428)。
4.根据代谢综合征异常组分项数分组,经过Levene检验显示apoB/apoA I比值方差齐性(F=1.545,P=0.191),各组apoB/apoA I均数的多重比较用one-way ANOVA (LSD法),结果显示0项异常组和2项异常组、0项异常组和3项异常组、0项异常组和4项异常组、1项异常组和2项异常组、1项异常组和3项异常组、1项异常组和4项异常组、2项异常组和3项异常组、2项异常组和4项异常组、3项异常组和4项异常组的apoB/apoA I均值差异均具有统计学意义(P值分别为0.000、0.000、0.000、0.000、0.000、0.000、0.009、0.000和0.007)；0项异常组和1项异常组的apoB/apoA I均值差异则无统计学意义(P值为0.250)。
5.在PCOS患者中,当截断值为0.66时,apoB/apoA I对代谢综合征的诊断价值最大：ROC曲线下面积为0.885,敏感度和特异性分别为0.917和0.700。
结论：
1.本研究中,PCOS患者代谢综合征发生率为19.46%,且有超过一半的患者至少有一项代谢综合征组分异常,将来可能发展为代谢综合征。代谢综合征是糖尿病及心血管疾病的高发人群,因此,重视PCOS患者代谢异常的筛查并及时进行干预,对于减少PCOS患者出现远期并发症有重要意义。
2. apoB/apoAⅠ比值均值随着代谢综合征异常组分项数的增多而增加,与其关系密切。
3. apoB/apoAⅠ比值对代谢综合征有较好的诊断价值。对于临床中未达到代谢综合征的诊断标准而apoB/apoAⅠ比值超过0.66的PCOS患者,应警惕代谢综合征的发生,宜及时采取相应的干预措施。
Background and Objective:Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age, whose incidence is4%-12%. The clinical manifestations of PCOS are various, for example abnormal menstruation (oligomenorrhea or amenorrhea), hirsutism, acne, obesity, infertility and so on. Long term complications include hypertension, hyperlipidemia, diabetes and cardiovascular disease. PCOS starts from adolescence, not only affects the body endocrine and metabolism, but also brought psychological problems to the patients. Previous studies have shown that the incidence of dyslipidemia and impaired glucose tolerance (IGT) is higher in patients with PCOS than normal people. The cause has not yet fully elucidated, and may be associated with obesity, insulin resistance and hyperandrogenism. Because of the differences in race, life style and dietary habit, the incidence of IGT and dyslipidemia is varied in different countries. Basically, western countries'is higher while Asian countries'is lower. A growing number of studies support that insulin resistance is the key pathogenesis of PCOS, metabolic abnormalities are associated with it. But there are also studies consider that metabolic abnormalities have a more close relationship with obesity or hyperandrogenism. In this study, we further explore the incidence and type of dyslipidemia and abnormal glucose tolerance in Chinese PCOS patients through, and the related factors of glucose and dyslipidemia, hoping to provide better guidance for the treatment of PCOS.
In recent years, metabolic syndrome (MS) is getting more and more concerning. Most countries have found that the incidence of MS in PCOS patients increased significantly than normal healthy people. MS is characterized by the central obesity, along with abnormal blood glucose, blood lipid and blood pressure. People diagnosed with this syndrome are at a high risk of getting diabetes, atherosclerosis related diseases. Some studys have found that apolipoprotein (apo) has a closer relation with atherosclerosis disease than triglyceride(TG) or total cholesterol (TC), especially the apoB/apoA I ratio is better than any other lipid components in the prediction of cardiovascular disease. This study aims to explore the incidence of MS and the value of apoB/apoA I ratio in diagnosting MS in PCOS patients.
Chapter I The glucose and lipid metabolism in patients with polycystic ovary syndrome and their relationship with insulin resistance
Objects:185patients were included in this study, who visited the outpatient of obstetrics and gynecology department in Zhujiang Hospital of Southern Medical University for the first time in November2008to November2012, and had not taking any drugs that affected the hormones, plasma glucose and lipid in the recent3monthes before the diagnosis, and conformed to the2003Rotterdam diagnostic criteria of PCOS.
Objectives:to explore the incidence of abnormal glucose and lipid metabolism in PCOS patients and their relationships with insulin resistance.
Methods:
1. All included patients were gathered the medical history (menarche age, menstrual history, past marital and fertile history, incentives of menstrual disorders, etc.), and family history.
2. Measured the height, weight, blood pressure, waist circumference, hip circumference, and calculated the BMI (body mass index, BMI) and waist-to-hip ratio.
3. Fasting venous blood was collected on the second or third day of menstrual cycle or withdrawal bleeding, being used to detect the concentration of estradiol (E2), follicle-stimulating hormone (FSH), luteinizing hormone (LH), prolactin (PRL), testosterone (T) and blood lipid, including total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), apolipoprotein B (apoB) and apolipoprotein A I (apoA I).
4. B-ultrasonic examination was performed on the fourth or fifth day of the menstrual cycle or withdrawal bleeding by specific ultrasound doctors.
5. Oral glucose tolerance test (OGTT) and insulin release test (IRT):every included object fasted for8-12hours, and fasting blood was collected in the next morning. Then solubled83g normal glucose powder (containing a H2O molecule) in250-300ml water and drinked it off in5minutes. Timing started when the first bite of sugar water was taked. Blood samples were taken on the first hour and the second hour after taking the sugar water. The serum glucose and insulin levels were detected in all the blood samples. The homeostasis model assessment-insulin resistance (HOMA-IR) index was calculated using the values of fasting glucose (FPG) and fasting insulin (FINS).
6. Statistical methods:SPSS19.0statistical software was used to analyze the datas. The homogeneity of variance was tested with Leneve. The measurement data was described with x±s, and the enumeration data was described with absolute terms (percentage). Comparison between two groups was done with independent sample T-test and chi-square test. Correlation analysis was done with Pearson or Spearman. Difference was statistically significant with P<0.050.
7. Groups:
(1) According to the WHO diagnostic criteria for diabetes in2006,185patients with PCOS were divided into normal glucose tolerance group (NGT) and the abnormal glucose tolerance group (AGT). Cases of the two groups were148and37respectively. The differences of related factors between the two groups were compared, and stratified analysis of the incidences of abnormal glucose tolerance according to BMI and age were also done.
(2) According to a dyslipidemia prevention guideline for Chinese adults in2007,185patients with PCOS were divided into normal blood lipids group and dyslipidemia group. Cases of the two groups were154and31respectively. The differences of related factors between the two groups were compared, and stratified analysis of the incidences of dyslipidemia according to BMI and age were also done.
(3) According to the data of the national diabetes cooperation investigation, insulin resistance was defined as the HOMA-IR greater than or equal to2.69.185PCOS patients were divided into non-insulin resistant group and insulin resistant group. Cases of the two groups were135and50respectively. The incidences of dyslipidemia and abnormal glucose tolerance of the two groups were compared, and the correlations of dyslipidemia and abnormal glucose tolerance with insulin resistance were also analyzed.
Results:
1. In this study, we found that80.00%(148/185) of all the185PCOS patients had normal glucose tolerance (NGT), while20%of them had IGT and DM:IGT17.84%(33/185) and DM2.16%(4/185).
2. The mean values of age, BMI, waist hip ratio, HOMA IR, fasting insulin (FINS),2h-INS were higher in abnormal glucose tolerance(AGT) group (37cases) than in NGT group (148cases), the difference was statistically significant (P<0.05); the mean values of LH, T, systolic pressure, diastolic blood pressure and blood lipid levels had no obvious difference.
3. Stratified analysis of abnormal glucose tolerance (AGT) according to BMI were performed and we found that overweight people (23≤BMI<25kg/m2) accounted for17.30%(32/185) in all the patients, while overweight people (BMI>25kg/m2) accounted for20.54%(38/381). Along with the increase of BMI, the incidence of increased significantly, from20.83%in the BMI<18kg/m2layer to55.56%in the BMI≥28kg/m2layer.
4. Stratified analysis of abnormal glucose tolerance (AGT) according to age were also performed and we found that And we found that, as the growth of the age, the incidence of AGT increased significantly, form0.00%in the16～20years-old layer to33.33%in the≥36years-old layer.
5. In this study, the total incidence of dyslipidemia was16.76%(31/185), in which the TC abnormality was3.24%(6/185), TG abnormality was4.32%(8/185), LDL-C abnormal accounted for2.16%(4/185), HDL-C accounted for9.73%(18/185). The incidences from high to low were:low HDL-C, high TG, high TC, and high LDL-C.
6. The mean values of BMI, waist-to-hip ratio, systolic blood pressure, diastolic blood pressure, fasting insulin, HOMA-IR and apoB/apoA I in dyslipidemia group (31cases) were significantly elevated than that in the nomal blood lipid group, while the mean values of age, LH, T, fasting plasma glucose, fasting insulin,2h-glucose and2h-insulin had no obvious difference between the two groups.
7. Stratified analysis of dyslipidemia according to BMI were performed, and we found that along with the increase of BMI, the incidence of dyslipidemia PCOS patients increased significantly, from0.00%in the BMI<18kg/m2layer to33.33%in the BMI≥28kg/m2layer.
8. Stratified analysis of dyslipidemia according to age was also performed, and we found that the incidence of dyslipidemia in the16-20years-old layer was the same with that in the>36years-old layer (33.33%).
9. The incidence of insulin resistance was27.03%(50/185), the incidences of dyslipidemia and abnormal glucose tolerance of the insulin resistant group were30.00%(15/50) and38.00%(19/50) respectively, while those of the non-insulin resistant group were11.85%(16/135) and13.33%(18/135) respectively. The total incidence of dyslipidemia and abnormal glucose tolerance of the insulin resistant group increased significantly than the non-insulin resistant group (chi-square values were8.615and8.615respectively; P values all were0.000). The incidence of higher TG in the insulin resistant group increased significantly than that in the non-insulin resistant group (chi-square value was5.335, P value was0.021), while the differences of incidences of higher TC, lower HDL-C and higher LDL-C between the two groups had no statistical significance (chi-square values were0.125,3.067and0.125respectively; P values were0.724,0.080and0.296respectively).
10. HOMA-IR index had a positive correlation with BMI, waist circumference, fasting plasma glucose,1h-glucose,2h-glucose, TG, LDL-C, abnormal glucose tolerance and dyslipidemia (correlation coefficients r values were0.590,0.547,0.356,0.279,0.422,0.281,0.286,0.146and0.239respectively, and P values were0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000and0.001respectively), while a negative correlation with HDL-C (correlation coefficient r values were0.268, and P value was0.000). The correlation with TC had no statistical significance (correlation coefficient r value was0.022, and P value was0.764).
Conclusion:
1. In this study, the incidence of abnormal glucose tolerance patients with PCOS was20.00%, and increased significantly as BMI and age rose. All the PCOS patients in the clinical should have an OGTT experiment, and early intervention should carry out in patients with abnormal glucose tolerance (for example, weight loss or using hypoglycemic drugs) to prevent or delay the development of diabetes.
2. The incidence of dyslipidemia was16.76%, the incidence of each type from high to low were:lower HDL-C, higher TG, higher TC, and higher LDL-C.
3. The incidence of dyslipidemia in PCOS patients increased significantly along with the rise of BMI. Obesity might worsen the lipid metabolism in PCOS patients, and weight control was he primary goal of the treatment of dyslipidemia in PCOS patients.
4. In our study, the incidence of dyslipidemia in adolescent PCOS patients was the same with that of the middle-aged patients, all were33.33%. That may be related to high incidence of overweight and obesity in adolescent patients. Attentions should be pay to screening of dyslipidemia in adolescent PCOS patients, especially overweight or obese patients.
5. Our study found out that insulin resistance had a positive correlation with abnormal glucose tolerance and dyslipidemia. Improvement of insulin resistance may be helpful in correcting the abnormal glucose and lipid metabolism in PCOS patients.
Chapter II Diagnostic value of apoB/apoA I ratio for metabolic syndrome in patients with polycystic ovary syndrome
Objects:185patients were included in this study, who visited the outpatient of obstetrics and gynecology department in Zhujiang Hospital of Southern Medical University for the first time in November2008to November2012, and had not taking any drugs that affected the hormones, plasma glucose and lipid in the recent3monthes before the diagnosis, and conformed to the2003Rotterdam diagnostic criteria of PCOS.(The same with the first chapter)
Objectives:to explore the incidence of metabolic syndrome (MS) and the diagnostic value of apoB/apoAⅠ ratio for metabolic syndrome in patients with polycystic ovary syndrome (PCOS).
Methods:
1. All included patients were gathered the medical history (menarche age, menstrual history, past marital and fertile history, incentives of menstrual disorders, etc.), and family history. Measured the height, weight, blood pressure, waist circumference, hip circumference, and calculated the BMI (body mass index, BMI) and waist-to-hip ratio.
2. Fasting venous blood was collected on the second or third day of menstrual cycle or withdrawal bleeding, being used to detect the concentration of sex hormones and metabolism indexes.
3. B-ultrasonic examination was performed on the fourth or fifth day of the menstrual cycle or withdrawal bleeding by specific ultrasound doctors.
4. Statistical methods:SPSS19.0statistical software was used to analyze the datas. The homogeneity of variance was tested with Leneve. The measurement data was described with x±s, and the enumeration data was described with absolute terms (percentage). Comparison between two groups was done with independent sample T-test and chi-square test, and multiple comparisons with one-way ANOVA. Correlation analysis was done with Pearson or Spearman. Using ROC curve analyzed the diagnostic value of apoB/apoAⅠ ratio for metabolic syndrome. Difference was statistically significant with P<0.050.
5. Groups:
(1) According to the international diabetes federation (IDF) diagnostic criteria of for metabolic syndrome in2005,185patients were divided into the metabolic syndrome and non-metabolic syndrome group. Cases of the two groups were148and37respectively. The differences of related factors between the two groups were compared.
(2) According to whether abdominal obesity and insulin resistance (IR) or not,185patients were divided into four groups:l=not abdominal obesity not IR group,2=not abdominal obesity and IR group,3=abdominal obesity not IR group,4=abdominal obesity IR group. Cases of the four groups were89,10,46and40respectively. The mean values of apoB/apoA I ratio were compared among the for groups, and the correlation between the apoB/apoA I ratio and some indexes of PCOS was exploded.
(3) According to the numbers of abnormal metabolic syndrome components,185patients were divided into five groups:0group,1group,2group,3group,4group and5group. Cases of the five groups were80,58,35,9and3respectively. The mean values of apoB/apoA I ratio were compared among the for groups, and the diagnostic value of apoB/apoA I ratio for metabolic syndrome was exploded by using ROC curve.
Results:
1. In this study, we found that the morbidity of MS was19.46%in all the185PCOS patients, and56.76%of them had at least one abnormal components of MS. The mean values of BMI, waist circumference, waist-to-hip ratio, systolic blood pressure and diastolic blood pressure, fasting glucose, fasting insulin,1h glucose,1h insulin,2h glucose,2h insulin, HOMA-IR, TG, LDL-C, apoB and apoB/apoA I of MS group were significantly higher than those of the non-MS group (P values were0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.012,0.014,0.000,0.040,0.000,0.000,0.010,0.000and0.000respectively); while HDL-C and apoA I decreased significantly (P values were0.000and0.000respectively). The mean values of age and TC between the two groups had no statistical significance (P values were0.398and0.393respectively).
2. ApoB/apoA I ratio was positively correlated with BMI, waist circumference, waist-to-hip ratio, blood pressure, fasting glucose, HOMA IR, TG and LDL-C (correlation coefficients r values were0.469,0.415,0.411,0.317,0.219,0.285and0.292respectively, and P values all were0.000), and negatively correlated with HDL-C (correlation coefficients r values was-0.465, and P values was0.000), all statistically significant (P<0.05). But the correlation of age and ovarian volume had no statistical significance (correlation coefficients r values were0.010and-0.062respectively, and P values were0.889and0.398respectively).
3. All patients were divided into four groups according to whether they had abdominal obesity and IR. Levene test showed that the homogeneity of variances of had no statistical significance (F=0.544, P=0.544), and we found that the differences of averages of apoB/apoA I ratio between group1and3, group1and4, group2and4were all statistically significant (P values were0.000,0.000,0.049and0.015), while the differences of averages between group1and2, group3and4had no statistical significance (P values were0.918and0.428respectively).
4. According to the numbers of abnormal metabolic syndrome components,185patients were divided into five groups, Levene test showed that the homogeneity of variances of apoB/apoA I ratio had no statistical significance (F=0.544, P=0.544), multiple comparisons among five groups were done with one-way ANOVA. We found that the differences of averages of apoB/apoA I ratio between group0and2, group0and3, group0and4, group1and2, group1and3, group2and3, group2and4, group3and4were all statistically significant (P values were0.000,0.000,0.000,0.000,0.000,0.000,0.009,0.000and0.007respectively), while the differences of averages between group0and1had no statistical significance (P values was0.250).
5. Using the receiver operating characteristics (ROC) curve to analysis the diagnostic value of apoB/apoA I ratio for MS in PCOS patients, we found that when the cutoff value of apoB/apoA I was0.66, the area under the ROC curve was the biggest (0.885), with a sensitivity of0.917and specificity of0.700.
Conclusion:
1. In this study, the incidence of metabolic syndrome in PCOS patients was 19.46%, and more than half of the patients had at least one abnormal components of the metabolic syndrome, who were likely to develop metabolic syndrome in the future. Patients diagnosed with metabolic syndrome were at a higher risk of developing diabetes and cardiovascular disease. Therefore, it has important significance to attach great importance in screening of metabolic abnormalities in patients with PCOS and carrying out timely intervention soon afterwards.
2. The average of apoB/apoA I ratio rose as the number of abnormal metabolic syndrome components increased, that means it had a close relationship with metabolic syndrome.
3. ApoB/apoA I ratio had a good diagnostic value for metabolic syndrome. Those PCOS patients, who did not meet the diagnostic criteria for metabolic syndrome but the apoB/apoA I ratio was more than0.66, should be alert to the occurrence of the metabolic syndrome, and should take appropriate intervention measures in a timely manner.
引文
[1]Kedikova SE, Sirakov MM, Boyadzhieva MV. Leptin levels and adipose tissue percentage in adolescents with polycystic ovary syndrome. Gynecol Endocrinol,2013.
[2]Krepula K, Bidzinska-Speichert B, Lenarcik A, et al. Psychiatric disorders related to polycystic ovary syndrome. Endokrynol Pol,2012,63:488-491.
[3]Milsom SR, Nair SM, Ogilvie CM, et al. Polycystic Ovary Syndrome and Depression in New Zealand Adolescents. J Pediatr Adolesc Gynecol,2013.
[4]Vrbikova J, Fanta M, Cibula D, et al. Impaired glucose metabolism in women with polycystic ovary syndrome. Gynecol Obstet Invest,2009,68(3):186-190.
[5]Celik C, Abali R, Bastu E, et al. Assessment of impaired glucose tolerance prevalence with hemoglobin Alc and oral glucose tolerance test in 252 Turkish women with polycystic ovary syndrome:a prospective, controlled study. Hum Reprod,2013,28(4):1062-1068.
[6]倪仁敏,钟俊敏,陈晓莉,等.多囊卵巢综合征患者糖代谢异常发生率及其特点.中华糖尿病杂志,2009,1(6)：417-421.
[7]Zhang J, Fan P, Liu H, et al. Apolipoprotein A-I and B levels, dyslipidemia and metabolic syndrome in south-west Chinese women with PCOS. Hum Reprod,2012,27(8):2484-2493.
[8]Wild RA. Dyslipidemia in PCOS. Steroids,2012,77(4):295-299.
[9]Valkenburg O, Steegers-Theunissen RP, Smedts HP, et al. A more atherogenic serum lipoprotein profile is present in women with polycystic ovary syndrome:a case-control study. J Clin Endocrinol Metab, 2008,93(2):470-476.
[10]Macut D, Panidis D, Glisic B, et al. Lipid and lipoprotein profile in women with polycystic ovary syndrome. Can J Physiol Pharmacol, 2008,86(4):199-204.
[11]Bhathena RK. Insulin resistance and the long-term consequences of polycystic ovary syndrome. J Obstet Gynaecol,2011,31(2):105-110.
[12]Lee H, Oh JY, Sung YA, et al. The prevalence and risk factors for glucose intolerance in young Korean women with polycystic ovary syndrome. Endocrine,2009,36(2):326-332.
[13]Liang SJ, Liou TH, Lin HW, et al. Obesity is the predominant predictor of impaired glucose tolerance and metabolic disturbance in polycystic ovary syndrome. Acta Obstet Gynecol Scand,2012,91 (10):1167-1172.
[14]Wongwananuruk T, Rattanachaiyanont M, Indhavivadhana S, et al. Prevalence and clinical predictors of insulin resistance in reproductive-aged thai women with polycystic ovary syndrome. Int J Endocrinol,2012,2012:529184.
[15]Rocha MP, Marcondes JA, Barcellos CR, et al. Dyslipidemia in women with polycystic ovary syndrome:incidence, pattern and predictors. Gynecol Endocrinol,2011,27(10):814-819.
[16]Tehrani FR, Simbar M, Tohidi M, et al. The prevalence of polycystic ovary syndrome in a community sample of Iranian population:Iranian PCOS prevalence study. Reprod Biol Endocrinol,2011,9:39.
[17]Wild RA, Carmina E, Diamanti-Kandarakis E, et al. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome:a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab,2010,95(5):2038-2049.
[18]Cheung LP, Ma RC, Lam PM, et al. Cardiovascular risks and metabolic syndrome in Hong Kong Chinese women with polycystic ovary syndrome. Hum Reprod,2008,23(6):1431-1438.
[19]Dong Z, Chen X, Li L, et al. Free testosterone level correlated with the metabolic abnormalities dependent on central obesity in women with polycystic ovary syndrome. Exp Clin Endocrinol Diabetes, 2012,120(6):355-360.
[20]Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod, 2004,19(1):41-47.
[21]Lean ME, Han TS, Morrison CE. Waist circumference as a measure for indicating need for weight management. BMJ,1995,311 (6998):158-161.
[22]杨文英.联合测量腰臀围比值(或腰围)和血压可预测代谢综合征.中华内分泌代谢杂志,2005,21：227-229.
[23]洪宇,刘雯,赵晓苗,等.多囊卵巢综合征患者的血脂代谢异常及与胰岛素抵抗的关系分析.实用妇产科杂志,2012,28(3)：230-233.
[24]Essah PA, Nestler JE, Carmina E. Differences in dyslipidemia between American and Italian women with polycystic ovary syndrome. J Endocrinol Invest,2008,31(1):35-41.
[25]Hu W, Hu WH, Qiao J, et al. [Characteristics of abnormal glucose tolerance in patients with polycystic ovary syndrome]. Zhonghua Yi Xue Za Zhi, 2009,89(29):2053-2055.
[26]Wei HJ, Young R, Kuo IL, et al. Prevalence of insulin resistance and determination of risk factors for glucose intolerance in polycystic ovary syndrome:a cross-sectional study of Chinese infertility patients. Fertil Steril, 2009,91(5):1864-1868.
[27]Bhartacharya SM. Polycystic ovary syndrome and abnormalities in glucose tolerance. Int J Gynaecol Obstet,2009,105(1):29-31.
[28]Kauffman RP, Baker TE, Graves-Evenson K, et al. Lipoprotein profiles in Mexican American and non-Hispanic white women with polycystic ovary syndrome. Fertil Steril,2011,96(6):1503-1507.
[29]Alberti KG, Zimmet P, Shaw J. The metabolic syndrome--a new worldwide definition. Lancet,2005,366(9491):1059-1062.
[30]Apridonidze T, Essah PA, Iuorno MJ, et al. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab,2005,90:1929-1935.
[31]Hudecova M, Holte J, Olovsson M, et al. Prevalence of the metabolic syndrome in women with a previous diagnosis of polycystic ovary syndrome: long-term follow-up. Fertility and Sterility,2011,96:1271-1274.
[32]Ni RM, Mo Y, Chen X, et al. Low prevalence of the metabolic syndrome but high occurrence of various metabolic disorders in Chinese women with polycystic ovary syndrome. Eur J Endocrinol,2009,161:411-418.
[33]晏群.多囊卵巢综合征患者代谢综合征患病风险研究.中华内分泌代谢 杂志,2010,26.
[34]Sierra-Johnson J, Somers VK, Kuniyoshi FH, et al. Comparison of apolipoprotein-B/apolipoprotein-AI in subjects with versus without the metabolic syndrome. Am J Cardiol,2006,98:1369-1373.
[35]Pitsavos C, Panagiotakos DB, Skoumas J, et al. Risk stratification of apolipoprotein B, apolipoprotein Al, and apolipoprotein B/AI ratio on the prevalence of the metabolic syndrome:the ATTICA study. Angiology, 2008,59:335-341.
[36]Yin Q, Chen X, Li L, et al. Apolipoprotein B/apolipoprotein A1 ratio is a good predictive marker of metabolic syndrome and pre-metabolic syndrome in Chinese adolescent women with polycystic ovary syndrome. J Obstet Gynaecol Res,2013,39:203-209.
[37]Dejager S, Pichard C, Giral P, et al. Smaller LDL particle size in women with polycystic ovary syndrome compared to controls. Clin Endocrinol (Oxf), 2001,54:455-462.
[38]McQueen MJ, Hawken S, Wang X, et al. Lipids, lipoproteins, and apolipoproteins as risk markers of myocardial infarction in 52 countries (the INTERHEART study):a case-control study. Lancet,2008,372:224-233.
[39]Walldius G, Jungner I, Aastveit AH, et al. The apoB/apoA-I ratio is better than the cholesterol ratios to estimate the balance between plasma proatherogenic and antiatherogenic lipoproteins and to predict coronary risk. Clin Chem Lab Med,2004,42:1355-1363.
[40]Kalra A, Nair S, Rai L. Association of obesity and insulin resistance with dyslipidemia in Indian women with polycystic ovarian syndrome. Indian J Med Sci,2006,60:447-453.
[41]Ying X, Qian Y, Jiang Y, et al. Association of the apolipoprotein B/apolipoprotein A-I ratio and low-density lipoprotein cholesterol with insulin resistance in a Chinese population with abdominal obesity. Acta Diabetol, 2012,49:465-472.
[1]Tehrani FR, Simbar M, Tohidi M, et al. The prevalence of polycystic ovary syndrome in a community sample of Iranian population:Iranian PCOS prevalence study. Reprod Biol Endocrinol,2011,9:39.
[2]Wild RA, Carmina E, Diamanti-Kandarakis E, et al. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome:a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab,2010,95(5):2038-2049.
[3]Zhang J, Fan P, Liu H, et al. Apolipoprotein A-I and B levels, dyslipidemia and metabolic syndrome in south-west Chinese women with PCOS. Hum Reprod,2012,27(8):2484-2493.
[4]Wild RA. Dyslipidemia in PCOS. Steroids,2012,77(4):295-299.
[5]Valkenburg O, Steegers-Theunissen RP, Smedts HP, et al. A more atherogenic serum lipoprotein profile is present in women with polycystic ovary syndrome:a case-control study. J Clin Endocrinol Metab,2008,93(2): 470-476.
[6]Macut D, Panidis D, Glisic B, et al. Lipid and lipoprotein profile in women with polycystic ovary syndrome. Can J Physiol Pharmacol,2008,86(4): 199-204.
[7]Andrikoula M, McDowell IF. The contribution of ApoB and ApoA I measurements to cardiovascular risk assessment. Diabetes Obes Metab, 2008,10(4):271-278.
[8]Prassl R, Laggner P. Molecular structure of low density lipoprotein:current status and future challenges. Eur Biophys J,2009,38(2):145-158.
[9]Sniderman AD, Furberg CD, Keech A, et al. Apolipoproteins versus lipids as indices of coronary risk and as targets for statin treatment. Lancet, 2003,361 (9359):777-780.
[10]Doi SA, Abbas JM, Parkinson L, et al. LDL species heterogeneity in the atherogenic dyslipidemia of polycystic ovary syndrome. Am J Clin Pathol, 2008,129(5):802-810.
[11]Karasek D, Vaverkova H, Halenka M, et al. Total adiponectin levels in dyslipidemic individuals:relationship to metabolic parameters and intima-media thickness. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub,2011,155(1):55-62.
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[13]Ni RM, Mo Y, Chen X, et al. Low prevalence of the metabolic syndrome but high occurrence of various metabolic disorders in Chinese women with polycystic ovary syndrome. Eur J Endocrinol,2009,161 (3):411-418.
[14]Cheung LP, Ma RC, Lam PM, et al. Cardiovascular risks and metabolic syndrome in Hong Kong Chinese women with polycystic ovary syndrome. Hum Reprod,2008,23(6):1431-1438.
[15]Bhattacharya SM. Metabolic syndrome in females with polycystic ovary syndrome and International Diabetes Federation criteria. J Obstet Gynaecol Res,2008,34(1):62-66.
[16]Soares EM, Azevedo GD, Gadelha RG, et al. Prevalence of the metabolic syndrome and its components in Brazilian women with polycystic ovary syndrome. Fertil Steril,2008,89(3):649-655.
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[18]McQueen MJ, Hawken S, Wang X, et al. Lipids, lipoproteins, and apolipoproteins as risk markers of myocardial infarction in 52 countries (the INTERHEART study):a case-control study. Lancet,2008,372(9634):224-233.
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[21]Pitsavos C, Panagiotakos DB, Skoumas J, et al. Risk stratification of apolipoprotein B, apolipoprotein A1, and apolipoprotein B/AI ratio on the prevalence of the metabolic syndrome:the ATTICA study. Angiology, 2008,59(3):335-341.
[22]Yin Q, Chen X, Li L, et al. Apolipoprotein B/apolipoprotein A1 ratio is a good predictive marker of metabolic syndrome and pre-metabolic syndrome in Chinese adolescent women with polycystic ovary syndrome. J Obstet Gynaecol Res,2013,39(1):203-209.
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[24]Kastelein JJ, der Steeg WA v, Holme I, et al. Lipids, apolipoproteins, and their ratios in relation to cardiovascular events with statin treatment. Circulation, 2008,117(23):3002-3009.
[2]Krepula K, Bidzinska-Speichert B, Lenarcik A, et al. Psychiatric disorders related to polycystic ovary syndrome. Endokrynol Pol,2012,63:488-491.
[3]Milsom SR, Nair SM, Ogilvie CM, et al. Polycystic Ovary Syndrome and Depression in New Zealand Adolescents. J Pediatr Adolesc Gynecol,2013.
[4]Vrbikova J, Fanta M, Cibula D, et al. Impaired glucose metabolism in women with polycystic ovary syndrome. Gynecol Obstet Invest,2009,68(3):186-190.
[5]Celik C, Abali R, Bastu E, et al. Assessment of impaired glucose tolerance prevalence with hemoglobin Alc and oral glucose tolerance test in 252 Turkish women with polycystic ovary syndrome:a prospective, controlled study. Hum Reprod,2013,28(4):1062-1068.
[6]倪仁敏,钟俊敏,陈晓莉,等.多囊卵巢综合征患者糖代谢异常发生率及其特点.中华糖尿病杂志,2009,1(6)：417-421.
[7]Zhang J, Fan P, Liu H, et al. Apolipoprotein A-I and B levels, dyslipidemia and metabolic syndrome in south-west Chinese women with PCOS. Hum Reprod,2012,27(8):2484-2493.
[8]Wild RA. Dyslipidemia in PCOS. Steroids,2012,77(4):295-299.
[9]Valkenburg O, Steegers-Theunissen RP, Smedts HP, et al. A more atherogenic serum lipoprotein profile is present in women with polycystic ovary syndrome:a case-control study. J Clin Endocrinol Metab, 2008,93(2):470-476.
[10]Macut D, Panidis D, Glisic B, et al. Lipid and lipoprotein profile in women with polycystic ovary syndrome. Can J Physiol Pharmacol, 2008,86(4):199-204.
[11]Bhathena RK. Insulin resistance and the long-term consequences of polycystic ovary syndrome. J Obstet Gynaecol,2011,31(2):105-110.
[12]Lee H, Oh JY, Sung YA, et al. The prevalence and risk factors for glucose intolerance in young Korean women with polycystic ovary syndrome. Endocrine,2009,36(2):326-332.
[13]Liang SJ, Liou TH, Lin HW, et al. Obesity is the predominant predictor of impaired glucose tolerance and metabolic disturbance in polycystic ovary syndrome. Acta Obstet Gynecol Scand,2012,91 (10):1167-1172.
[14]Wongwananuruk T, Rattanachaiyanont M, Indhavivadhana S, et al. Prevalence and clinical predictors of insulin resistance in reproductive-aged thai women with polycystic ovary syndrome. Int J Endocrinol,2012,2012:529184.
[15]Rocha MP, Marcondes JA, Barcellos CR, et al. Dyslipidemia in women with polycystic ovary syndrome:incidence, pattern and predictors. Gynecol Endocrinol,2011,27(10):814-819.
[16]Tehrani FR, Simbar M, Tohidi M, et al. The prevalence of polycystic ovary syndrome in a community sample of Iranian population:Iranian PCOS prevalence study. Reprod Biol Endocrinol,2011,9:39.
[17]Wild RA, Carmina E, Diamanti-Kandarakis E, et al. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome:a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab,2010,95(5):2038-2049.
[18]Cheung LP, Ma RC, Lam PM, et al. Cardiovascular risks and metabolic syndrome in Hong Kong Chinese women with polycystic ovary syndrome. Hum Reprod,2008,23(6):1431-1438.
[19]Dong Z, Chen X, Li L, et al. Free testosterone level correlated with the metabolic abnormalities dependent on central obesity in women with polycystic ovary syndrome. Exp Clin Endocrinol Diabetes, 2012,120(6):355-360.
[20]Revised 2003 consensus on diagnostic criteria and long-term health risks related to polycystic ovary syndrome (PCOS). Hum Reprod, 2004,19(1):41-47.
[21]Lean ME, Han TS, Morrison CE. Waist circumference as a measure for indicating need for weight management. BMJ,1995,311 (6998):158-161.
[22]杨文英.联合测量腰臀围比值(或腰围)和血压可预测代谢综合征.中华内分泌代谢杂志,2005,21：227-229.
[23]洪宇,刘雯,赵晓苗,等.多囊卵巢综合征患者的血脂代谢异常及与胰岛素抵抗的关系分析.实用妇产科杂志,2012,28(3)：230-233.
[24]Essah PA, Nestler JE, Carmina E. Differences in dyslipidemia between American and Italian women with polycystic ovary syndrome. J Endocrinol Invest,2008,31(1):35-41.
[25]Hu W, Hu WH, Qiao J, et al. [Characteristics of abnormal glucose tolerance in patients with polycystic ovary syndrome]. Zhonghua Yi Xue Za Zhi, 2009,89(29):2053-2055.
[26]Wei HJ, Young R, Kuo IL, et al. Prevalence of insulin resistance and determination of risk factors for glucose intolerance in polycystic ovary syndrome:a cross-sectional study of Chinese infertility patients. Fertil Steril, 2009,91(5):1864-1868.
[27]Bhartacharya SM. Polycystic ovary syndrome and abnormalities in glucose tolerance. Int J Gynaecol Obstet,2009,105(1):29-31.
[28]Kauffman RP, Baker TE, Graves-Evenson K, et al. Lipoprotein profiles in Mexican American and non-Hispanic white women with polycystic ovary syndrome. Fertil Steril,2011,96(6):1503-1507.
[29]Alberti KG, Zimmet P, Shaw J. The metabolic syndrome--a new worldwide definition. Lancet,2005,366(9491):1059-1062.
[30]Apridonidze T, Essah PA, Iuorno MJ, et al. Prevalence and characteristics of the metabolic syndrome in women with polycystic ovary syndrome. J Clin Endocrinol Metab,2005,90:1929-1935.
[31]Hudecova M, Holte J, Olovsson M, et al. Prevalence of the metabolic syndrome in women with a previous diagnosis of polycystic ovary syndrome: long-term follow-up. Fertility and Sterility,2011,96:1271-1274.
[32]Ni RM, Mo Y, Chen X, et al. Low prevalence of the metabolic syndrome but high occurrence of various metabolic disorders in Chinese women with polycystic ovary syndrome. Eur J Endocrinol,2009,161:411-418.
[33]晏群.多囊卵巢综合征患者代谢综合征患病风险研究.中华内分泌代谢 杂志,2010,26.
[34]Sierra-Johnson J, Somers VK, Kuniyoshi FH, et al. Comparison of apolipoprotein-B/apolipoprotein-AI in subjects with versus without the metabolic syndrome. Am J Cardiol,2006,98:1369-1373.
[35]Pitsavos C, Panagiotakos DB, Skoumas J, et al. Risk stratification of apolipoprotein B, apolipoprotein Al, and apolipoprotein B/AI ratio on the prevalence of the metabolic syndrome:the ATTICA study. Angiology, 2008,59:335-341.
[36]Yin Q, Chen X, Li L, et al. Apolipoprotein B/apolipoprotein A1 ratio is a good predictive marker of metabolic syndrome and pre-metabolic syndrome in Chinese adolescent women with polycystic ovary syndrome. J Obstet Gynaecol Res,2013,39:203-209.
[37]Dejager S, Pichard C, Giral P, et al. Smaller LDL particle size in women with polycystic ovary syndrome compared to controls. Clin Endocrinol (Oxf), 2001,54:455-462.
[38]McQueen MJ, Hawken S, Wang X, et al. Lipids, lipoproteins, and apolipoproteins as risk markers of myocardial infarction in 52 countries (the INTERHEART study):a case-control study. Lancet,2008,372:224-233.
[39]Walldius G, Jungner I, Aastveit AH, et al. The apoB/apoA-I ratio is better than the cholesterol ratios to estimate the balance between plasma proatherogenic and antiatherogenic lipoproteins and to predict coronary risk. Clin Chem Lab Med,2004,42:1355-1363.
[40]Kalra A, Nair S, Rai L. Association of obesity and insulin resistance with dyslipidemia in Indian women with polycystic ovarian syndrome. Indian J Med Sci,2006,60:447-453.
[41]Ying X, Qian Y, Jiang Y, et al. Association of the apolipoprotein B/apolipoprotein A-I ratio and low-density lipoprotein cholesterol with insulin resistance in a Chinese population with abdominal obesity. Acta Diabetol, 2012,49:465-472.
[1]Tehrani FR, Simbar M, Tohidi M, et al. The prevalence of polycystic ovary syndrome in a community sample of Iranian population:Iranian PCOS prevalence study. Reprod Biol Endocrinol,2011,9:39.
[2]Wild RA, Carmina E, Diamanti-Kandarakis E, et al. Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome:a consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society. J Clin Endocrinol Metab,2010,95(5):2038-2049.
[3]Zhang J, Fan P, Liu H, et al. Apolipoprotein A-I and B levels, dyslipidemia and metabolic syndrome in south-west Chinese women with PCOS. Hum Reprod,2012,27(8):2484-2493.
[4]Wild RA. Dyslipidemia in PCOS. Steroids,2012,77(4):295-299.
[5]Valkenburg O, Steegers-Theunissen RP, Smedts HP, et al. A more atherogenic serum lipoprotein profile is present in women with polycystic ovary syndrome:a case-control study. J Clin Endocrinol Metab,2008,93(2): 470-476.
[6]Macut D, Panidis D, Glisic B, et al. Lipid and lipoprotein profile in women with polycystic ovary syndrome. Can J Physiol Pharmacol,2008,86(4): 199-204.
[7]Andrikoula M, McDowell IF. The contribution of ApoB and ApoA I measurements to cardiovascular risk assessment. Diabetes Obes Metab, 2008,10(4):271-278.
[8]Prassl R, Laggner P. Molecular structure of low density lipoprotein:current status and future challenges. Eur Biophys J,2009,38(2):145-158.
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