| BackgroundChronic kidney disease is the independent risk factor of cardiovascular disease, and cardiovascular complications has become the leading cause of death in these patients. Early diagnosis and intervention of the cardiovascular dysfunction in patients with chronic kidney disease is very important.The echocardiographyic parameter LVEF is commonly used to estimate the cardiac systolic function. However, many CKD patients may keep preserved EF for a long time, so a more sensitive and comprehensive method is in need.2D-STI(Two-dimensional speckle tracking imaging) is a new echocardiographyic technology which comes to widely use recently. The technology simultaneously obtains myocardial longitudinal, radial and circumferential deformation indices. It is a promising method which is easy to operate with high sensitivity, angle-independence, good interobserver and intraobserver reproducibility.This research measures both the routine echocardiographyic parameters and speckle tracking parameters to evaluate changes of cardiac structure and function in patients with chronic kidney disease. Serum biomarkers are also detected to reveal their effects.Objectives1. To find out the changing tendency of cardiac structure and function in patients with chronic kidney disease;2. To evaluate how some non-traditional risk factors in patients with chronic kidney disease influence the cardiovascular system;3. To discuss the value of speckle tracking technology in detecting subclinical changes of cardiovascular function in patients with chronic kidney disease.Methods1. Study population 28 patients with chronic kidney disease were enrolled in our study, who had GFR< 90ml/(min·1.73m2) for at least 3 months.20 healthy volunteers matching with them in terms of age and gender were enrolled at the same time.Our objectives are divided into three groups:(1) Control group:20 healthy volunteers,12 male and 8 female; (2) non-renal failure CKD group:Stage 2-4 CKD patients,12 male and 3 female; (3) renal failure group:Stage 5 CKD patients,5 male and 8 female.2. EquipmentPHILIPS EPIQ7C with X5-1 probe is used for the detection. QLAB workstation is used for data analysis.3. ExaminationThe medical history, heart rate, blood pressure and ECG are recorded and routine serological examinations are taken after patients admitted to hospital.Echocardiography is taken to measure LVIDd, LVIDs, SWTd and PWTd. PW and TDI are used to measure E, A and E’.At least 3 cycles of dynamic images of Ap4, Ap3, Ap2, SAM, SAB and SAX are stored for analysis.4. Image processing and data analysisWe use a-2DQ mode of QLAB software to get EDV, ESV and EF automatically. After that, we use a-CMQ mode to get GLS, GCS, Prot-A and Prot-B.We further calculate left ventricular mass, left ventricular mass index, relative ventricular wall thickness, PTW, E/A, E/E’with the measured data.5. Statistical analysisWe applicate SPSS 19.0 statistical software for analysis, and data is expressed as mean±standard deviation. Differences of the three groups are tested by ANOVA, and LSD test is used to comparison between two of them. Pearson and Spearman analysis are used to determine the correlation of two variations. Through multiple linear regression analysis, we determine the independent factors of GLS.RESULT1. General statesHR and PTH of renal failure patients increases compared with the non-renal failure group. The difference is statistically significant (p< 0.05).2. The changes of Left ventricular structure(1) PWTd, LVM, LMI and RWT of non-renal failure patients increase compared with control. The difference is statistically significant (p< 0.05);(2) LVIDd and LVIDs of renal failure patients increase compared with control. The difference is statistically significant (p< 0.05);(3) 10 of the non-renal failure patients (67%) develop ventricular remodeling, including 2 cases with concentric remodeling (13%),7 cases with concentric hypertrophy (47%) and 1 case with eccentric hypertrophy (7%).12 of the renal failure patients develop ventricular remodeling (92%), including 2 cases with concentric remodeling (15%),8 cases with concentric hypertrophy (62%) and 2 cases with eccentric hypertrophy (15%). The incidence of LVH in renal failure patients increases. The difference is statistically significant (p< 0.05).3. Systolic function(1) GLS of the control group, the non-renal failure group and the renal failure group decreases gradually, and the difference is statistically significant (p< 0.05);(2) Compared with non-renal failure patients, PTW and GCS of renal failure patients decrease, and the difference is statistically significant (p< 0.05);(3) Compared with control, ESV and ProtA of renal failure patients decrease, and the difference is statistically significant (p< 0.05);(4) Compared with control, EDV of non-renal failure patients increases, and the difference is statistically significant (p< 0.05).4. Diastolic function(1) E/E’ of the control group, the non-renal failure group and the renal failure group increases gradually, and the difference is statistically significant (p< 0.05);(2) E’ of the control group, the non-renal failure group and the renal failure group decreases gradually, and the difference is statistically significant (p< 0.05);(3) Compared with the control group, E/A of the renal failure group decreases, and the difference is statistically significant (p< 0.05).5. Correlation Analysis(1) After controlling age, sex and blood pressure, the correlations between LVEF and LVM, LVMI are still statistical significant (r=-0.679,-0.74, p<0.05);(2) After controlling age, sex, blood pressure, the correlations between LVEF and GCS, PWTd are still statistical significant(r=0.435,0.751, p<0.05) and PTW still correlates to Cr, eGFR, E/E’,E’, Prot-A significantly (r=0.484、-0.642,-0.49,0.58,0.83, p<0.05);(3) After controlling age, sex, blood pressure, the correlations between E and GCS, GLS, Prot-A, PTW, Cr、GFR are still statistical significant. (r=-0.514、-0.555、-0.441、-0.49、0.586,-0.446, p<0.05). E’ still correlates to GCS,GLS, Prot-A, PTW, Cr and GFR significantly (r=0.57、0.416、0.555、0.576、-0.581、-0.416, p<0.05)(4) After controlling age, sex, blood pressure, the correlations between GLS and Hb, BUN, Cr, PTH and eGFR are still statistical significance; Multiple regression shows that Hb, BUN, Cr and PTH are independent influencing factors of GLS.CONCLUSION1. Cardiac function in CKD patients reduces, and cardiac structure obviously changes even in the early stage of CKD. The cardiac state usually deteriorates as CKD progresses;2. Compared with the traditional echocardiographyic parameters, GLS is more sensitive to reflect the changes of myocardial systolic function in patients with chronic kidney disease (CKD);3. Cardiac function in CKD patients is closely related to the CKD-specific non-traditional risk factor;... |
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