专论——基于PWTT的血压预测相关算法的系列研究

Study on the Correlation Between Systolic Blood Pressure and Pulse Wave Transit Time in Outpatient Patients

目的探讨门诊患者时点收缩压与脉搏波传导时间（PulseWaveTransitTime，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）；②PWTT可能与时点收缩压具有显著相关性；③252例门诊数据中预测值与实测值误差<5mmHg的82例，占比32.54%；误差<10mmHg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 explore the correlation between pulse wave transit time(PWTT)and systolic blood pressure(SBP)in outpatients.Methods The pulse wave data of3280outpatients were collected.Multiple linear regression was established by the independent variable,which might influence the systolic blood pressure(SBP).252cases of outpatients were collected for predictive analysis.Results①The multiple linear regression was fit well and the correlation was significant(R=0.663,F=425.875,P<0.05);②There was significant correlation between PWTT and SBP(P<0.05);③There were82patients in252of whose predicted value and the measured value error<5mmHg,which accounted for32.54%;the predicted value and the measured value error<10mmHg was detected in151patients,which accounted for59.92%.Conclusion There was a good correlation between PWTT and SBP.It is possible to predict the early prediction of blood pressure via the correlation between PWTT and SBP,but accurate prediction is still need to be studied.