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目的探讨门诊患者时点收缩压与脉搏波传导时间(Pulse Wave Transit Time,PWTT)的相关性。方法对门诊3280例患者通过智能腕表采集脉搏波数据,将可能影响时点收缩压的自变量引入多重线性回归模型,将时点收缩压(即脉搏波数据采集的同时,为患者测量的坐位、静息状态下、同侧上臂收缩压)作为因变量进行多重线性拟合,采集252例门诊患者进行预测分析。结果(1)多重线性回归方程拟合较好且有显著性(R=0.663,F=425.875,P<0.05);(2)PWTT可能与时点收缩压具有显著相关性;(3)252例门诊数据中预测值与实测值误差<5 mm Hg的82例,占比32.54%;误差<10 mm Hg的151例,占比59.92%。结论PWTT与时点收缩压具有良好的相关性,将其用于血压的早期预测具有可能性,但要做到精准的预测尚待深入研究。
Objective To investigate the relationship between systolic blood pressure and pulse wave transit time (PWTT) in outpatients. Methods A total of 3280 outpatients were collected pulsewave data through the smart wristwatch. Independent variables that may affect the systolic pressure at the time point were introduced into the multiple linear regression model. Time-dependent systolic blood pressure (ie, , Resting state, ipsilateral upper arm systolic pressure) as the dependent variable multiple linear fit, 252 outpatients were collected for predictive analysis. Results (1) Multiple linear regression equation fitted well and significant (R = 0.663, F = 425.875, P <0.05); (2) PWTT may have a significant correlation with time point systolic pressure; (3) 252 cases Outpatient data in the prediction and the measured value of error <5 mm Hg in 82 cases, accounting for 32.54%; error <10 mm Hg 151 cases, accounting for 59.92%. Conclusions There is a good correlation between PWTT and systolic blood pressure. It is possible to use PWTT for early prediction of blood pressure, but accurate prediction is yet to be further studied.