The peak period of cardiovascular disease (CVD) is around the time of awakening in the morning, which may be related to the surge of sympathetic activity at the end of nocturnal sleep. This paper chose 140 participants as study object, 70 of which had occurred CVD events while the rest hadn’t during a two-year follow-up period. A two-layer model was proposed to investigate whether hypnopompic heart rate variability (HRV) was informative to distinguish these two types of participants. In the proposed model, the extreme gradient boosting algorithm (XGBoost) was used to construct a classifier in the first layer. By evaluating the feature importance of the classifier, those features with larger importance were fed into the second layer to construct the final classifier. Three machine learning algorithms, i.e., XGBoost, random forest and support vector machine were employed and compared in the second layer to find out which one can achieve the highest performance. The results showed that, with the analysis of hypnopompic HRV, the XGBoost+XGBoost model achieved the best performance with an accuracy of 84.3%. Compared with conventional time-domain and frequency-domain features, those features derived from nonlinear dynamic analysis were more important to the model. Especially, modified permutation entropy at scale 1 and sample entropy at scale 3 were relatively important. This study might have significance for the prevention and diagnosis of CVD, as well as for the design of CVD-risk assessment system.
Calculation of linear parameters, such as time-domain and frequency-domain analysis of heart rate variability (HRV), is a conventional method for assessment of autonomic nervous system activity. Nonlinear phenomena are certainly involved in the genesis of HRV. In a seemingly random signal the Poincaré plot can easily demonstrate whether there is an underlying determinism in the signal. Linear and nonlinear analysis methods were applied in the computer words inputting experiments in this study for physiological measurement. This study therefore demonstrated that Poincaré plot was a simple but powerful graphical tool to describe the dynamics of a system.
Blood pressure variability (BPV) refers to the fluctuations of blood pressure in a certain period of time. In recent years, BPV is becoming a predictive marker for cardiovascular events. Given the hemodynamic and internal environmental change brought by hemodialysis as well as the complex complications, hemodialysis patients always have complex BPV. Nowadays there is no consensus on an optimal standard to evaluate BPV in hemodialysis population. Metrics usually used are as follows: blood pressure change during a certain period of time, standard deviation, coefficient of variation, variation independent of mean, average real variability, weighted mean of daytime and night-time standard deviation, residual derived from generalized linear models, and residual standard deviation. Impact factors of BPV in hemodialysis patients include age, ultrafitration volume, hemodialysis frequency and time length, peripheral vascular disease, serum calcium, antihypertensive drugs and so on. Recent studies showed significant associations between both long-term and short-term BPV with prognosis of hemodialysis patients. This review focuses on the evaluation methods, the influencing factors and the impact on prognosis of BPV.
ObjectiveTo systematically review the clinical effect and safety of traditional Chinese medicine (TCM) in the treatment of cough variant asthma (CVA). MethodsWe searched MEDLINE (Ovid), PubMed, EMbase, The Cochrane Library, VIP, WanFang Data, CNKI and CBM databases to collect randomized controlled trials (RCTs) about TCM for CVA from inception to May 2014. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Then meta-analysis was performed by RevMan 5.2 software. ResultsA total of 17 RCTs were included. The results of qualitative analysis showed that:in improving cough symptom, three of four RCTs showed that TCM was superior to western medicine alone. In improving airway hyper responsiveness and overall treatment effect, the difference between TCM and western medicine alone remained uncertain. No serious adverse reactions related to TCM was reported in 17 RCTs. ConclusionBased on the current evidence, some trials suggest the TCM is superior to western medicine alone in improving cough symptom, however in the improvement of airway hyper responsiveness and overall efficacy, the difference between TCM and western medicine alone remains uncertain. Due to the variety of TCM and western medicine as well as limited methodological quality and different intervention of the included studies, more high-quality RCTs with large scale are needed to verify the above conclusion.
The extraction of pulse rate variability(PRV) in daily life is often affected by exercise and blood perfusion. Therefore, this paper proposes a method of detecting pulse signal and extracting PRV in post-ear, which could improve the accuracy and stability of PRV in daily life. First, the post-ear pulse signal detection system suitable for daily use was developed, which can transmit data to an Android phone by Bluetooth for daily PRV extraction. Then, according to the state of daily life, nine experiments were designed under the situation of static, motion, chewing, and talking states, respectively. Based on the results of these experiments, synchronous data acquisition of the single-lead electrocardiogram (ECG) signal and the pulse signal collected by the commercial pulse sensor on the finger were compared with the post-auricular pulse signal. According to the results of signal wave, amplitude and frequency-amplitude characteristic, the post-ear pulse signal was significantly steady and had more information than finger pulse signal in the traditional way. The PRV extracted from post-ear pulse signal has high accuracy, and the accuracy of the nine experiments is higher than 98.000%. The method of PRV extraction from post-ear has the characteristics of high accuracy, good stability and easy use in daily life, which can provide new ideas and ways for accurate extraction of PRV under unsupervised conditions.
目的:了解阻塞性睡眠呼吸暂停综合征患者的心率变异改变。方法:对67例睡眠打鼾患者同步进行24小时动态心电图及多导睡眠图监测。根据PSG检测结果分为OSAS组和单纯鼾症组,比较组间低频峰(LF),高频峰(HF),低频峰与高频峰的比值(LF/HF),正常RR间期平均值及其标准差值(SDNN),正常RR间期差值均方根(rMSSD)。结果:OSAS组中,频域分析指标:LF,HF,均低于单纯鼾症组,LF/HF高于对照组,时域分析指标:SDNN,rMSSD均低于对照组。结论:OSAHS患者心率变异性降低。
目的:研究老年患者依托咪酯靶控输注时不同BIS值(脑电双频指数)的HRV(心率变异性)的变化情况,探讨不同镇静深度与HRV之间的关系。方法:选择65岁以上行门诊胃镜检查患者30例,随机分为3组,A组BIS45~55,B组55~65,C组65~75,各组均在麻醉前、麻醉诱导后,术中、术毕监测BIS、HRV及血液动力学指标。结果:A组各监测HRV明显降低(Plt;0.05),B组仅有轻度下降(Pgt;0.05),C组明显升高(Plt;0.05)。结论:患者镇静深度BIS55~65时,即可明显抑制内镜操作刺激所致的HRV变化,是临床较为合适的镇静深度,可显著降低老年患者交感神经活性、交感/迷走神经均衡性和自主神经总张力,利于机体血液动力学稳定。
ObjectiveTo explore the relationship between blood glucose variability index and persistent organ failure (POF) in acute pancreatitis (AP). MethodsWe prospectively included those patients who were diagnosed with AP with hyperglycemia and were hospitalized in the West China Center of Excellence for Pancreatitis of West China Hospital of Sichuan University from July 2019 to November 2021. The patients were given blood glucose monitoring at least 4 times a day for at least 3 consecutive days. The predictive value of blood glucose variability index for POF in patients with AP was analyzed. ResultsA total of 559 patients with AP were included, including 95 cases of POF. Comparing with those without POF, patients with AP complicated by POF had higher levels of admission glucose (11.0 mmol/L vs. 9.6 mmol/L), minimum blood glucose (6.8 mmol/L vs. 5.8 mmol/L), mean blood glucose (9.6 mmol/L vs. 8.7 mmol/L), and lower level of coefficient of variation of blood glucose (16.6 % vs. 19.0 %), P<0.05. Logistic regression analyses after adjustment for confounding factors showed that the risk of POF increased with the increase of admission glucose [OR=1.11, 95%CI (1.04, 1.19), P=0.002], minimum blood glucose [OR=1.28, 95%CI (1.10, 1.48), P=0.001] and mean blood glucose [OR=1.18, 95%CI (1.04, 1.33), P=0.010]; with the higher level of coefficient of variation of blood glucose [OR=0.95, 95%CI (0.92, 0.99), P=0.021], the risk of POF decreased. The results of area under the curve (AUC) of the receiver operator curves showed that AG [AUC=0.787, 95%CI (0.735, 0.840)] had the highest accuracy in predicting POF, with sensitivities of 60.0% and specificities of 84.7%. ConclusionHigh admission glucose, minimum blood glucose, mean blood glucose, and low coefficient of variation of blood glucose were risk factors for the development of POF in patients with hyperglycemic AP on admission.