Objective To evaluate the left ventricle geometry shape and left heart regional function in mitral insufficiency (MI) by quantitative tissue velocity imaging (QTVI) and the left ventricle systolic and diastolic geometry spbericity index. Methods Thirty normal subjects and 62 MI patients underwent QTVI and color Doppler imaging (CDFI) were enrolled in this study in order to measure the left ven-tricular geometry shape and left ventrieular regional function along LV apical long-axis view. Off-line LV regional velocity images along LV apical long-axis view were synchronously obtained. Peak tissue velocities of LV regional muscular tissue during systole(Vs),systolic acceler-ation(a), early diastole(Ve), LA contraction(Va)were synchronously measured as the index of left ventricular regional systolic and dias-tolic function. The left ventricle geometry shape index were reflected from the systolic and diastolic geometry sphericity index (SIs and Sid) and the left ventrieular ejection fraction (LVEF) and the peak D and peak a (PVd/PVa) of pulmonary veins flowing spectrum reflected the global left ventricular function index. The Vs, Ve, Va, a, PVd/PVd ratio, LVEF, SIs, SId were recorded and their correlation between normal subjects and patients with MI were compared. Result Vs, Ve,Va,a,PVd/ PVa ratio,SIs,SId in patients with MI were significantly re-duced. There was positive relation between Sis and a(r=0.602)and Ve/Va and SId(r=0.635). Conclusion There was negative rela-tion between regional cardiac function and LV spberieity, the higher cardiac function was accompanied with the lower SI.

Objective To construct and validate a predictive model for the risk of deep vein thrombosis(DVT)after lower extremity orthopedic surgery.Methods Clinical records of hospital-ized patients who underwent lower extremity orthopedic surgery in Wuxi Traditional Chinese Medicine Hospital from January 2017 to October 2019 were collected.The univariate and multivariate analysis with the backward stepwise method were applied to screen variables and build a nomogram prediction model,and the performance of the nomogram was evaluated with respect to its discriminant capabili-ty,calibration ability,and clinical utility.Results A total of 5 773 hospitalized patients with ortho-pedic surgery of lower extremity were included in the study,with the incidence of DVT of 0.9％.Through single factor and multi-factor stepwise regression analysis,5 variables were selected from 31 variables to construct the prediction model,including age,mean corpuscular hemoglobin concentra-tion(MCHC),D-dimer,platelet distribution width(PDW),and thrombin time(TT).The receiver operating characteristic(ROC)curve showed that areas under the ROC curve in the training and vali-dation cohort were 0.859 and 0.857,respectively.The model had good calibration ability and clini-cal practicability.Conclusion The DVT risk prediction model constructed in this study has good dif-ferentiation ability,calibration ability and clinical practicability,which is helpful for doctors to classi-fy DVT patients after lower extremity orthopedic surgery and formulate early treatment plan.

Objective To construct and validate a predictive model for the risk of deep vein thrombosis(DVT)after lower extremity orthopedic surgery.Methods Clinical records of hospital-ized patients who underwent lower extremity orthopedic surgery in Wuxi Traditional Chinese Medicine Hospital from January 2017 to October 2019 were collected.The univariate and multivariate analysis with the backward stepwise method were applied to screen variables and build a nomogram prediction model,and the performance of the nomogram was evaluated with respect to its discriminant capabili-ty,calibration ability,and clinical utility.Results A total of 5 773 hospitalized patients with ortho-pedic surgery of lower extremity were included in the study,with the incidence of DVT of 0.9％.Through single factor and multi-factor stepwise regression analysis,5 variables were selected from 31 variables to construct the prediction model,including age,mean corpuscular hemoglobin concentra-tion(MCHC),D-dimer,platelet distribution width(PDW),and thrombin time(TT).The receiver operating characteristic(ROC)curve showed that areas under the ROC curve in the training and vali-dation cohort were 0.859 and 0.857,respectively.The model had good calibration ability and clini-cal practicability.Conclusion The DVT risk prediction model constructed in this study has good dif-ferentiation ability,calibration ability and clinical practicability,which is helpful for doctors to classi-fy DVT patients after lower extremity orthopedic surgery and formulate early treatment plan.