Correlation Between Blood Pressure Variability And Contrast-induced Nephropathy

Objective: High blood pressure may cause the impact of heart, brain,kidney and other important organs, and blood pressure variability （BPV） is theindependent predictor of the target organ damage. Studies have shown thatBPV has relate to the kidney damage. As the developing of percutaneouscardiac intervention, the use of contrast medium is becoming more and morecommon, and contrast medium induced acute kidney injury, that is, Contrastinduced nephropathy （CIN）, has increased sharply. Studies also show that thedysfunction of the kidney can increase the incidence of Contrast inducednephropathy. And this study aims at the explore of the correlation betweenblood pressure variability and contrast-induced nephropathy.Methods: We collected70patients accepted the percutaneous cardiacinterventions, including45males and25females. Age31.00⁷9.00years（58.00±10.00years）. Weight49.00¹02.00kg （70.00±10.00kg）. Body massindex （BMI）17.70³3.70kg/m²（25.26±3.15kg/m²）.3patients suffered fromCIN，including1male and2females. Age44.00⁶4.00years （54.00±10.00years）.weight64.00⁷5.00kg （70.00±6.00kg）.BMI24.40²8.90kg/m²（26.27±2.35kg/m²）.we got the BPV （standard deviation SD） by ambulatory bloodpressure monitor before the percutaneous cardiac interventions. The BPV（standard deviation SD） includes24hours blood pressure variability:24hourssystolic blood pressure variability,24hours diastolic blood pressurevariability,24hours mean blood pressure variability,24hours pulse pressurevariability; Day blood pressure variability: day systolic blood pressurevariability, day diastolic blood pressure variability, day mean blood pressurevariability, day pulse pressure variability; Night blood pressure variability:night systolic blood pressure variability, night diastolic blood pressurevariability, night mean blood pressure variability, night pulse pressure variability. And we set the time area like this:6:00-22:00was the day time,22:00-6:00was the night time. The ambulatory blood pressure monitor（ABPM） took the blood pressure every15minutes at day time, and every30minuts at night time. We tested the serum creatinine （Scr） before operation,and reviewed the Scr48hours after the operation, then calculated thecreatinine clearance （Ccr） by the Cockcroft-Gault formula: Ccr （ml/min）=（140-age）×weight/（72×Scr）×0.85（if female）. And patients whosepost-operation serum creatinine increased25%or0.5mg/dl would get thediagnosis of CIN. We got the glomerular filtration rate （GFR） by the followingformula, that was, GFR （ml/min/1.73m²）=186×（Scr）^-1.154×（age）^-0.203×0.742（if female）, and the renal dysfunction was diagnosed by the standard of theGFR＜60ml/min/1.73m². We took the statistical analysis by SPSS13.0software packet. Quantitative data was described as mean±SD, and thequalitative data as%. Analysing the correlation between BPV andpre-operation and post-operation Ccr by bivariate correlations, and comparingthe BVP of CIN and non-CIN samples by Mann-Whitney U test. P＜0.05signifies significant difference.Results:70patients’ data have been collected, and3patients of themsuffered from CIN, and the incidence of CIN is4.2%.2patients suffered fromthe renal dysfunction, but not the CIN. The same as the linear trend between24hours PP variability and the pre-operation Ccr,24hours PP variability andthe post-operation Ccr, DBP variability and the post-operation Ccr, we couldalso find the obscure linear trend between24hours SBP variability andpre-operation Ccr from the scatter plot. Analysing the correlation betweenBPV and pre-operation and post-operation Ccr by bivariate analysis, therewere no significant differences between them. No significant differences ofBPV could be shown between CIN and non-CIN patients.Conclusion: No significant differences of BPV could be shown betweenCIN and non-CIN patients.