Correlation Study Between A Score System Based On Blood Pressure Variability And The Change Of Heart And Blood Vessels In Patients With Hypertension

BackgroundCardio-cerebrovascular disease has become a major health threat to residents. According to statistics, in China, about 3 million people die of cardiovascular disease each year, accounting for about 45% of all deaths. Therefore, it is called the No.l killer of Chinese residents. And hypertension is one of the major causes of the death in patients with Cardio-cerebrovascular disease. The latest authoritative data showed that there were 160 million hypertension patients in China and showed a trend of increasing. Nevertheless, the attention attached to hypertension is far from enough. The problems can be concluded into 3-High,3-Low,3-Not.3-High refers to high prevalence （18.8%）, high disability （40.7%） and high mortality （38.3%）; 3-Low refers to low awareness （30.6%）, low treatment （24.7%） and low control （6.1%）; besides, hypertension patients don’t medicine or take it irregularly. Some of them don’t take medicine until they feel awful.Smoking, alcohol abuse, obesity, mental tension, excessive salt taking, blood glucose rise and genetic factors all could lead to the increase in blood pressure, which will eventually cause hypertension. Hypertension can damage vessels and make cholesterin in blood deposit on coronary artery, which will lead to atherosclerosis, aortic wall thickening, viscoelasticity decrease, and even vascular narrowing, angor pectoris and final myocardial infarction. In addition, as the heart has to pump out higher pressure for a long time, at the early stage, it causes ventricular thickening, but with the development of the disease, the heart will be very tired and expanded. At last, cardiac failure or even death will occur. In addition to coronary vascular and heart target-organ damage, hypertension could also damage other target organs. For instance, its damage to cerebral vessels can lead to brain stock and systematic artery may cause arteriosclerosis obliterans, etc.Independent of the average level of blood pressure, Blood Pressure Variability （BPV） refers to the fluctuation of blood pressure, which can be used as a powerful predictor of cardiovascular events. BPV can be divided into short-term and long-term ones, of which the short-term BPV measured by 24-hour ambulatory blood pressure monitoring is the most commonly used. The clinical study, IVSd and LVPWd can reflect the damage of the heart structure; baPWV, the arterial hardness evaluation index, can reflect the arterial pathological changes; IMT and carotid plaque can reflect arterial structural lesions. In conclusion, IVSd, LVPWd, BaPWV IMT as well as carotid plaque can be used to reflect target-organ damage in hypertension patients from different angles. As for the treatment of hypertension, in clinical practice, the simple method of lowering blood pressure has been mostly adopted. However, less attention has been paid to BPV. Researches reported that for the patients with similar 24-hour average blood pressure, with the increase of their 24-hour BPV, the damage to their vessels, kidneys and heart target organs also increase relatively. Many studies have shown that BPV is closely related to target-organ damage of hypertension patients. Therefore, the fundamental measure to delay and control cardiovascular events is to reverse target-organ damage on the basis of early detection and early intervention. But the correlation between the traditional BPV indicators and target organs such as heart and blood vessels are not completely consistent, Mancia G, et found SBP₂4h_ARV associated with IMT; But in the study of Kawai T, et, SBP₂4h_ARV don’t correlation with IMT, at the same time, found SBP_day_ARV and SBP_night_ARV has correlation with IMT. Tian X and others found that there was correlation related to age between BPV and IMT, SBP_day_ARV and SBP₂4h ARV has correlation with IMT in the patients with 46 to 55 years old. Duke Score （DTS） is a can be used to calculate the comprehensive index years of survival rate and widely used in cardiovascular disease risk stratification. The score based on the results of the exercise test, with relevant parameters include:ST segment down, chest pain, and duration of the campaign. DTS= exercise duration in minutes-（5 x ST-segment deviation in millimeters）-（4 x exercise angina index）, where the exercise angina index= 0 for no angina,1 for non-limiting angina, and 2 for exercise-limiting angina.In view of the correlation of BPV indicators and change the target organs such as heart and blood vessels was not consistent, so we intend to build a new scoring system based on BVP （BPVSS）, analysis of correlation between BPVSS and Duke score, and validate its clinical significance. Aimed to explore application of noninvasive, and easy, low risk assessment means early intervention and long-term monitoring about the change target organs such as heart and blood vessels of hypertension, delay and reduce the cardiovascular eventsObjectivesCombined with the average level, age and biochemical indexes, this paper attempts to conduct correlation analysis and multiple stepwise regression analysis on 24-hour BPV and treadmill exercise test. Regression equations are to be established to produce a new blood pressure variability scoring system （BPV scoring）, which is similar to Duke scoring （from treadmill exercise test）. The correlations between BPV score and the damage of target organs such as heart and vessels are to be further analyzed. And then the BPV score will be studied quantitative and grouping method to verify the clinical significance of the BPV scoring. The ultimate objective is to co-build a BPV scoring data platform to strengthen the management of hypertension patients’blood pressure variability. An intelligent system integrating treatment with rehabilitation is wished to be established to optimize the community health management of hypertension patients.Objects220 essential hypertension patients accepted treatment in the Department of Cardiology of Guangzhou General Hospital of Guangzhou Military Area from June, 2014 to June,2015 have been selected as the research objects. The objects have been selected according to the following criteria: ①econdary hypertension patients and malignant hypertension patients have been excluded in accordance with " The 2010 Chinese Guidelines for the Management of Hypertension". ②ll the objects selected have completed biochemical testing, cardiovascular screening, Cardiac ultrasonic testing, carotid artery ultrasonography, treadmill exercise test and 24-hour dynamic blood pressure measurement. Excluding criteria:① acute myocardial infarction within five days; ②nstable angina has not been controlled by medical treatment; ③ncontrolled symptomatic heart failure;④severe hypertension（systolic pressure>200mmHgand （or） diastolic pressure>110mmHg）. The 220 objects have been divided into A and B groups, with 125 patients in Group A to get BPV scoring and 95 patients in Group B to verify the clinical significance of BPV scoring. In addition, Group A is divided further into sub-group A1 and A2. Sub-group A1 with 84 patients is the training sample, while Sub-group A2, with 41 patients, is the verification sample. Group B patients are sub-grouped by 3.9 to quantify the BPV score. The patients whose BPV score>3.9 belong to Sub-group B1, the control group（43 patients）, while the patients whose BPV score<3.9 belong to Sub-group B2, the investigation group（52 patients）. After the evaluation of the clinical performance and application of BPV scoring system, it attempts to carry out industrialization promotion, including inpatients, outpatients and suspicious hypertension patients in communities, to establish a dynamic and round-the-clock new ecosystem of community health management of hypertension patients by integrating hospitals, communities and families.MethodologyThe statistical software SPSS 19.0（IBM company,America）is used to analyze the data. First, it describes the demographic baseline data and clinical baseline data of the patients from Group A and two subgroups. The quantitative data is described by means±D and the qualitative data is described in percentage （%）. The heterogeneity± of the two sub-groups is compared by t test and X2 test, among which the quantitative data is compared by t test while qualitative data is compared with X2 test. P<0.05 is of statistical significance. Second, the BPV parameters and Duke Scores of Group A patients are analyzed by correlation. Furthermore, apart from the above statistical methods, Holdout test has also been adopted. That is, Group A is divided into two sub-groups, of which one sub-group is the training sample （randomly select two-thirds of the patients）, composed of 84 patients and the other sub-group is the verification sample（the rest of the one-third patients）, composed of 41 patients. To conduct multiple regression analysis through the training sample, and establish multiple regression analysis model （define BPV parameters, the average blood pressure, age and biochemical indicators as the dependent variables, Duke scores as independent variables, and finally adopt the method of stepwise regression analysis） to achieve the regression equation, i.e the new blood pressure variability scoring system--BPV scoring. To further study the agreement between BPV score and Duke Score, Bland-Altman analysis as well as Pearson correlation analysis have also been used. And the BPV score is obtained through Bland-Altman analysis and correlation analysis. SBP_mean is selected to be one of the control variables to do partial correlation analysis on BPV score and Duke Score. And finally, the general data of Group B and its two sub-groups has been analyzed. Similarly, the correlations between BPV score and IVSd, LVPWd, BaPWV as well as IMT are analyzed with Pearson correlation analysis. Groups are then divided according to BPV score. The differences of the two sub-groups in IVSd, LVPWd, BaPWV, IMT and carotid plaque proportion are compared with independent sample t test and x2 test. P< 0.05 is shown to be of statistical significance, and P< 0.01 indicates that is is of significant difference.Results1. The general information of Group A and its two sub-groups analysis showed that the difference of the general information of the two sub-groups achieved through complete random grouping is of no statistical significance;2. The mean variance of Group A patients’BPV scores analysis showed that RSD is significantly larger than SD, CV, ARV and SV.3. The Pearson correlation between BPV parameters and Duke Scores of Group A patients analysis showed that correlation only exists between SBP_day_SD, SBP_night_mean, SBP_night_SV, SBP_night_SV, SBP_night_RSD, SBP₂4h_mean, SBP₂4h_ARV, SBP₂4h_SV, SBP₂4h_RSD and Duke Scores.4. In the training sample, multiple stepwise regression analysis is conducted between BPV parameters correlated with Duke Scores combined with age and Duke Scores. The results demonstrate that BPV score=24.096-0.083* SBP_night_RSD-0.130* age-0.206* SBP_night_ARV;5. The Pearson correlation between BPV scores and Duke Scores analysis showed that P=0.047 （P<0.05 is of statistical significance）, showing that there is correlation between BPV scores and Duke scores.6. In order to further verify the correlation between BPV scores and Duke Scores, we analyzed the Bland-Altman analysis result between BPV scores and Duke Scores in the verification sample, which demonstrates that the average difference between the two is 1.1 while the 95% consistency limit falls between 7.4 and-9.5.7. There is a good correlation between BPV scores and Duke Scores. However, BPV scores is calculated with SBP. Therefore, SBPmean is selected into control variables to carry out partial correlation analysis between BPV scores and Duke Scores, so as to adjust SBP. It is finally confirmed that BPV, independent of SBP, is correlated with Duke Scores.8. We analyzed the general information of Group B and its two subgroups, and from the results, it can be concluded that the age and average blood pressure of the two groups are statistically different（P<0.05）, but the biochemical indicators have no statistical difference between the two groups （P> 0.05）;9. The correlation coefficient of target organ damage parameters and BPV scores as well as the value of P analysis showed that BPV scores have statistical correlation with IVSd, LVPWd, baPWV_L, baPWV_R, IMT_L and IMT_R.10. In order to further group the BPV scores, we analyzed the difference comparison of target-organ damage evaluation parameters collected from the two subgroups（control group:BPV score 3.9, observation group:BPV score<3.9） of Group B. Results prove that the difference between the two subgroups is of statistical significance.11. The data platform of BPV scores is built to strengthen the management of hypertension patients’blood pressure variability. And finally, intelligent service system combined diagnosis and rehabilitation has been established to optimize the community health management of hypertension patients.Conclusion1. A new blood pressure variability scoring system--BPV scoring has been achieved through carrying out correlation analysis and multiple stepwise regression analysis of 24-hour BPV and treadmill exercise test and establishing regression equation;2. BPV score is correlated with target-organ damage such as damage to heart and vessels. The larger the BPV, the lower the score, and the more severe the damage to heart and vessels will be. Patients who’s BPV score is less than 3.9 belong to high-risk group. And 3.9 can be used to optimize and simplify the present grouping of hypertension patients’blood pressure level.3. Blood pressure variability management will greatly affect the prognosis of hypertension patients’CR.4. As a new index to evaluate hypertension patients’ CR might be used in community health management of hypertension patients.