Changes in left wrist pulse wave transit time in patients with hypertension and influencing factors / 西安交通大学学报(医学版)

【Objective】 To investigate the changes in left wrist pulse wave transit time （PTT） in patients with hypertension， as well as the effects of serological indicators and unhealthy lifestyle. 【Methods】 We recruited 321 hypertensive patients admitted to Chinese PLA General Hospital Hainan Branch from June 2020 to April 2021 and divided them into two groups according to the simple randomization method. Totally 135 patients in the control group drank 20 mL of water after getting up in the morning and 186 patients in the observation group took the nifedipine controlled release tablets on the basis of the control group. A smart watch was used to collect the PTT at 0.5 h， 4.5 h， and 8.5 h after taking the medicine （drinking water） for the two groups. Repeated measurement analysis of variance was used to observe the influences of the time， interaction effect， and medicine on PTT. The data of gender， age， height， weight， left arm circumference， left arm length， resting heart rate， smoking， and alcohol drinking were collected. Fasting blood of 4 mL was collected to detect indicators such as fasting blood glucose （FBG）， total cholesterol （TC）， triglyceride （TG）， and uric acid （UA） to analyze possible factors affecting PTT. 【Results】 The time effect was statistically significant （F=12.065， P<0.001）， while the interaction effect was not （F=0.089， P=0.915）. There was no statistically significant difference between the two groups （F=2.074， P=0.155）. FBG， TC， TG， resting heart rate， and limited alcohol drinking differed significantly （P<0.05）. 【Conclusion】 PTT gradually shortens with time， and it has no significant relationship with antihypertensive drugs， but may be related to FBG， TC， TG， resting heart rate， alcohol drinking and other indicators.

Establishment of predictive model for blood pressure elevation in outpatients with hypertension / 中国中西医结合急救杂志

Objective To establish the regression equation of blood pressure in population based on the pulse wave transit time (PWTT) and verify its accuracy. Methods A convenient sampling method was used to collect gender, age, arm circumference, arm length, PWTT, history of hypertension, and body height, etc. of 4 121 outpatients' information from the Hainan Branch of Chinese PLA General Hospital from June 2016 to May 2018 to establish a binary variable logistic regression equation for blood pressure elevation or not and screen out the influencing factors of time point blood pressure. The accuracy of the equation was then verified in 252 outpatients. Results Logistic regression analysis showed that PWTT, gender, age, history of hypertension present or not, body height might be the influencing factors of blood pressure elevation [odds ratio (OR) values were 0.995, 0.530, 0.980, 107.128, 0.979, 95% confidence interval (95% CI) were 0.991-0.999, 0.405-0.695, 0.971-0.989, 73.935-155.223, and 0.962-0.996, respectively, all P < 0.05]. The classification prediction equation: Ln [P / (1-P)] = 2.087-0.005×PWTT-0.635×gender (man = 1, woman = 2)-0.02×age + 4.674×hypertension history present or not-0.021×body height [P indicates the probability of a positive result: systolic blood pressure≥140 mmHg (1 mmHg = 0.133 kPa) and/or diastolic blood pressure≥90 mmHg]. The overall test results showed that χ2 = 1 835.305, P < 0.05, statistically significant; The goodness of fit test results:χ2 = 5.881, P > 0.05, the data was conform to the equal proportion distribution. Model-confirmed results showed that in patients with a history of hypertension, the probability of predicting accuracy was 95%-99%. In patients without a history of hypertension, the probability of predicting accuracy was 45%-89%. Conclusion The predictive value of blood pressure elevation with this model in patients with a history of hypertension is superior to that of patients without the history of hypertension.

Comparison between continuous non-invasive estimated cardiac output by pulse wave transit time and thermodilution method.

Aims and Objectives: Cardiac output (CO) measurement is essential for many therapeutic decisions in anesthesia and critical care. Most available non‑invasive CO measuring methods have an invasive component. We investigate “pulse wave transit time” (estimated continuous cardiac output [esCCO]) a method of CO measurement that has no invasive component to its use. Materials and Methods: After institutional ethical committee approval, 14 adult (21–85 years) patients undergoing surgery and requiring pulmonary artery catheter (PAC) for measuring CO, were included. Postoperatively CO readings were taken simultaneously with thermodilution (TD) via PAC and esCCO, whenever a change in CO was expected due to therapeutic interventions. Both monitoring methods were continued until patients’ discharge from the Intensive Care Unit and observer recording values using TD method was blinded to values measured by esCCO system. Results: Three hundred and one readings were obtained simultaneously from both methods. Correlation and concordance between the two methods was derived using Bland‑Altman analysis. Measured values showed significant correlation between esCCO and TD (r = 0.6, P < 0.001, 95% confidence limits of 0.51-0.68). Mean and (standard deviation) for bias and precision were 0.13 (2.27) L/min and 6.56 (2.19) L/min, respectively. The 95% confidence interval for bias was ‑ 4.32 to 4.58 L/min and for precision 2.27 to10.85 L/min. Conclusions: Although, esCCO is the only true non‑invasive continuous CO monitor available and even though its values change proportionately to TD method (gold standard) with the present degree of error its utility for clinical/therapeutic decision‑making is questionable.

A System for Measurement of Pulse Wave Transit Time Continuously Based on Wireless Sensor Network / 航天医学与医学工程

Objective To design a system for monitoring pulse wave transit time (PWTT) in working condition non-intrusively and continuously. Method The system was composed of wireless ECG sensor and wireless pulse wave sensor which measure pulse wave signal from the temporal artery and ECG signal from body synchronously and calculates PWTT continuously. Result Both the wireless ECG sensor and the wireless pulse wave sensor were small sized and powered by button battery. And the accuracy of time synchronization about sensors was less than 1 ms. The calculated PWTT changed slowly with deep breathing. Conclusion The system works smoothly for continuous monitoring of PWTT in working condition.

Continuous measurement of blood pressure using pulse wave transit time / 医疗卫生装备

A continuous noninvasive method for blood pressure (BP) estimation by pulse wave transit time (PWTT) is described. A constant linear relation is available between PWTT and BP, but characteristic parameter for the relation is different for different persons. According to hydrostatics, BP in some vessel changes with different body postures. In this paper, the difference, i.e. △BP, between two BP values with different body postures is gained. ECGs and surface pulse waves are also obtained, and then values of PWTT are calculated. Through the A BP and PWTT acquired above, parameter b of BP equation can be determined, and then parameter a is computerized through the measurements and one BP value. Thus a BP equation is got, which can be used to estimate BP values through continuous measurement of PWTT. Compared with the value from invasive BP measurement, the value from this method has an error rate less than 5%. The method is feasible for noninvasive continuous BP monitoring.