[OP.2B.05] LONG TERM, BUT NOT SHORT TERM, BLOOD PRESSURE VARIABILITY PREDICTS CARDIOVASCULAR OUTCOMES IN CHRONIC KIDNEY DISEASE PATIENTS. (September 2016)

• Record Type: Journal Article
• Authors: Mallamaci, F.; Minutolo, R.; Stanzione, G.; D'Arrigo, G.; Leonardis, D.; Tripepi, G.; Cicchetti, T.; Postorino, M.; De Nicola, L.; Conte, G.; Borrelli, S.; Zoccali, C.
• Is Part Of: Journal of hypertension. Volume 34:(2016) Supplement 2
• Publication Date: 2016-09
• Subjects: Hypertension -- Periodicals; Hypertension -- Periodicals; 616.132005
• DOI: 10.1097/01.hjh.0000491379.70445.4d
• Languages: English
• ISSNs: 1473-5598

Abstract

Abstract : Objective: Short term [24 h Ambulatory Blood Pressure Blood (ABPM) derived] and long term (visit-to-visit BP variability) hold prognostic value for CV outcomes in essential hypertensives but their prognostic value has never been face-to-face compared in chronic kidney disease (CKD) pts. Design and method: We studied 402 pts with stage G2-5 CKD (age: 63 ± 14 yrs; eGFR: 44 ± 20 ml/min). Each patient underwent 24 h ABPM as well as office BP measurements for assessing short term (24 h ABPM) and long term (visit to visit) BP variabilities. Short term Systolic BP (SBP) variability was assessed by calculating the weighted standard deviation (SD) of 24 h SBP measurements and long term variability was expressed in terms of SD of SBP measurements across visits. The primary study outcome was a combined endpoint including all-cause and CV death and non-fatal CV events. Results: During the follow-up period (62 ± 32 months), 135 pts experienced the combined endpoint. On univariate Cox analyses, both short [HR (1 mmHg): 1.14, 95% CI: 1.08–1.19, P < 0.001] and long term [HR: 1.07, 95% CI: 1.04–1.10, P < 0.001] SBP variabilities predicted the combined end point and this was also true for 24 h mean ABPM SBP [HR: 1.03, 95% CI: 1.02–1.04, P < 0.001] and average SBP across visits [HR: 1.03, 95% CI: 1.02–1.04, P < 0.001]. In two separate Cox models adjusting for average 24 h ABPM SBP (Model 1) or mean SBP across visits (Model 2), both short term [Model 1: HR: 1.10, 95% CI: 1.05–1.16, P < 0.001] and long term [Model 2: HR: 1.04, 95% CI: 1.01–1.07, P = 0.02] SBP variabilities predicted the combined endpoint. By including into Model 1 Framingham risk factors, background CV comorbidities, Hb and eGFR, long term, visit-to-visit, SBP variability maintained an independent relationship with the combined end-point [P = 0.02] while the average SBP across visits did not [P = 0.18]. In contrast short term SBP variability was unrelated to the same endpoint [P = 0.79]. Conclusions: In CKD pts long term SBP variability holds prognostic value for death and CV outcomes beyond and above mean SBP over time while short term SBP variability fails to predict clinical outcomes. Long term SBP variability is the most powerful BP biomarker of CV outcomes in this population.