摘要
背景阻塞性睡眠呼吸暂停低通气综合征(OSAHS)在高血压患者中患病率高,但诊断率低,其中心率变异性(HRV)和血压变异性(BPV)都是心血管事件相关预测因子,但目前关于OSAHS与高血压患者BPV和HRV内在联系的相关研究较少。目的本研究旨在探讨OSAHS对高血压患者HRV、BPV的影响,并开发和内、外部验证一种通过HRV和BPV相关指标预测高血压患者OSAHS患病风险的列线图。方法选取2018年1月—2020年12月在中南大学湘雅二医院收治的228例高血压患者作为研究对象,根据OSAHS诊断标准分为单纯高血压组(n=114)和高血压合并OSAHS组(n=114);另外收集2021年1—2月住院的34例高血压伴或不伴OSAHS患者作为独立的外部验证组。收集研究对象的一般资料(年龄、性别、BMI等)、平均血压水平〔夜间收缩压(nSBP)等〕、BPV相关指标〔夜间收缩压标准差(nSSD)、夜间舒张压标准差(nDSD)、24 h舒张压标准差(24 hDSD)等〕、血压昼夜节律、HRV相关指标〔RR间期平均值标准差(SDANN)、低频带(LF)等〕、多导睡眠监测(PSG)参数〔氧减指数(ODI)、睡眠呼吸暂停低通气指数(AHI)、最低血氧饱和度(MinSpO_(2))等〕。采用多元线性回归分析探究HRV和BPV相关影响因素;并绘制限制性立方样条图检验高血压患者平均血压水平、BPV和HRV相关指标与OSAHS患病风险的相关性;通过多因素Logistic回归分析高血压患者患OSAHS的影响因素,构建列线图预测模型,采用Bootstrap方法在检验内、外部组验证组在列线图模型中的性能;采用受试者工作特征(ROC)曲线评估内、外部验证组列线图对高血压患者OSAHS患病风险的预测价值,计算ROC曲线下面积(AUC)等指标。结果多元线性回归分析结果显示:BMI、ODI、MinSpO_(2)是高血压合并OSAHS组患者nSSD、nDSD水平和HRV相关指标的独立影响因素(P<0.05);限制性立方样条模型结果显示BPV、HRV相关指标与发生OSAHS存在非线性相关(P<0.05),纳入多元Logistic回归分析后发现nSBP、nSSD、24 hDSD、SDANN、LF、年龄、BMI是高血压患者发生OSAHS的影响因素(P<0.05);以年龄、BMI、nSBP、nSSD、24 hDSD、SDANN、LF为预测因子构建列线图预测模型,Bootstrap方法验证结果显示,内、外部验证组的绝对误差分别为0.013、0.021,表明列线图模型的校准度良好。内、外部验证组列线图预测高血压患者OSAHS患病风险的AUC分别为0.861〔95%CI(0.818,0.919),P<0.001〕、0.744〔95%CI(0.691,0.839),P<0.001〕。结论OSAHS可增加高血压患者夜间BPV,降低HRV,HRV和BPV均与OSAHS病情严重程度密切相关,夜间缺氧或许更能引起血压和心率变化。本研究构建的列线图也许可用于高血压患者发生OSAHS风险的个体化预测,HRV和BPV参数或许是筛选OSAHS的有力工具。
Background Obstructive sleep apnea-hypopnea syndrome(OSAHS)is highly prevalent but is underdiagnosed in hypertensive patients.There are few studies on the internal association of OSAHS with two predictors of cardiovascular events,namely heart rate variability(HRV)and blood pressure variability(BPV),in hypertensive patients.Objective To explore the influence of OSAHS on HRV and BPV in hypertension patients,and to develop and validate a nomogram for predicting the risk of OSAHS in these patients using HRV and BRV related indicators.Methods Two hundred and twenty-eight hypertensive patients〔including 114 without OSAHS(simple hypertension subgroup)and 114 with OSAHS(hypertension with OSAHS subgroup)assessed by the diagnostic criteria of OSAHS〕were selected as internal validation group from the Second Xiangya Hospital of Central South University from January 2018 to December 2020,and other 34 hypertensive patients with or without OSAHS who hospitalized in the same hospital during January to February 2021 were selected as an independent external verification group.General information(age,gender,BMI,etc.),average blood pressure level〔nighttime systolic blood pressure(nSBP),etc.〕,BPV related indices〔nighttime systolic blood pressure standard deviation(nSSD),nighttime diastolic blood pressure standard deviation(nDSD),24-hour diastolic blood pressure standard deviations(24 hDSD),etc〕,blood pressure circadian rhythm,HRV related parameters〔standard deviation of the mean RR intervals(SDANN),low frequency(LF),etc.〕,polysomnography parameters〔oxygen desaturation index(ODI),apnea hypopnea index(AHI),minimum oxygen saturation(MinSpO_(2)),etc.〕.Multiple linear regression analysis were used to explore the influencing factors of HRV and BPV.Restricted cubic splines were used to test the correlation of the average blood pressure level,BPV and HRV related indicators with the risk of OSAHS.Multivariate Logistic regression model was used to analyze the influencing factors of OSAHS,and the screened factors were used to construct a nomogram for predicting OSAHS risk.The Bootstrap method was used to validate the performance of the internal and external groups in the nomogram model.And its predictive value for OSAHS risk in the two groups was assessed using the receiver operating characteristic(ROC)curve with the area under the curve(AUC)and other indicators calculated.Results Multiple linear regression analysis showed that BMI,ODI and MinSpO_(2) were independently associated with nSSD,nDSD or HRV related indices in hypertensive patients with OSAHS(P<0.05).Restricted cubic splines revealed that BPV related indices had a nonlinear relationship with OSAHS,and so did HRV related indices(P<0.05).Multivariate Logistic regression analysis showed that nSBP,nSSD,24 hDSD,SDANN,LF,age and BMI were associated with OSAHS in hypertensive patients(P<0.05).The Bootstrap method showed that,the absolute error of the nomogram constructed using age,BMI,nSBP,nSSD,24 hDSD,SDANN and LF was 0.013 in internal verification group,and was 0.021 in external verification group,indicating that the model had good calibration.The values of the AUC of the nomogram in predicting the risk of OSAHS in hypertension in internal and external validation groups were 0.861〔95%CI(0.818,0.919),P<0.001〕and 0.744〔95%CI(0.691,0.839),P<0.001〕,respectively.Conclusion OSAHS can increase the nSSD and nDSD and decrease HRV in hypertensive patients.Both HRV and BPV are closely related to the severity of OSAHS.Nocturnal hypoxia may be more likely to cause changes in blood pressure and heart rate.Our nomogram could be used to facilitate individualized prediction of OSAHS risk in hypertensive patients.HRV and BPV parameters might be powerful tools to screen for OSAHS.
作者
费敏
雷思
许琰
叶云
卓慧
张慧
罗荧荃
FEI Min;LEI Si;XU Yan;YE Yun;ZHUO Hui;ZHANG Hui;LUO Yingquan(Department of General Medicine,the Second Xiangya Hospital of Central South University,Changsha 410001,China;Department of Geriatrics,the Second Xiangya Hospital of Central South University,Changsha 410001,China)
出处
《中国全科医学》
CAS
北大核心
2023年第20期2459-2468,共10页
Chinese General Practice
基金
湖南省自然科学基金资助项目(2021JJ30944)。
关键词
睡眠呼吸暂停
阻塞性
高血压
血压变异性
心率变异性
列线图
Sleep apnea,obstructive
Hypertension
Blood pressure variability
Heart rate variability
Nomogram