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Background: The range of central blood pressure (BP) found in individuals with high-normal brachial BP overlaps the one found in hypertension (HTN) and normotension. As central BP is possibly a better predictor of cardiovascular (CV) disease, the aim of this study was to determine the risk associated with different central/brachial BP patterns. Methods: 13,759 participants from a populational cohort with central BP and prospective data from governmental databases who were not treated for HTN were selected. Major adverse CV events (MACE) comprised myocardial infarction, stroke, heart failure and CV death. Thresholds for brachial and central HTN were identified as 135 and 125 mmHg respectively. Individuals were separated into 4 BP patterns: normal BP; isolated brachial HTN; isolated central HTN; concordant brachial and central HTN. CV risk for each pattern was compared to normal BP with a Cox proportional hazard model adjusted for multiple covariables. Results: 688 MACE occurred over a median follow-up of 70.0 months. Characteristics of individuals in each BP phenotype are presented in Table 1. Only the concordant brachial and central HTN pattern had higher risk of MACE [HR 1.37 95% CI (1.15–1.64), p = 0.001] compared to normal BP. Sensitivity analyses with different definitions of central HTN and after stratification for sex yielded similar results. Demographic characteristics Normal BP (n = 10,611) Isolated brachial HTN (n = 394) Isolated central HTN (n = 496) Concordant HTN (n = 2,258) n 10,611 394 496 2,258 Age 51 (46–57) 53 (47–60) 54 (49–62) 56 (51–63) Male sex 43% 88% 38% 58% Caucasian race 89% 88% 91% 89% Cardiovascular disease 2% 2% 4% 2% Diabetes 4% 8% 3% 6% Active smoking 19% 22% 16% 21% BMI (kg/m2) 26 ± 5 28 ± 3 28 ± 5 28 ± 5 eGFR (ml/min/1.73 m2) 90 ± 14 87 ± 15 89 ± 14 88 ± 14 10-year Framingham risk score (%) 8 ± 7 17 ± 10 11 ± 7 18 ± 12 LDL-c (mmol/L) 3.1 ± 0.8 3.1 ± 0.9 3.3 ± 0.9 3.3 ± 0.9 Heart rate (bpm) 70 ± 10 77 ± 11 65 ± 9 71 ± 11 Aspirin 6% 8% 11% 9% Statin 10% 16% 16% 13% Conclusions: In untreated individuals, both central and brachial BP need to be elevated to increase CV risk. These findings provide support for the utility of routine central BP measurements in clinical practice.

Abstract Background Missing preadmission serum creatinine (SCr) values are a common obstacle to assess acute kidney injury (AKI) diagnosis and outcomes. The Kidney Disease Improving Global Outcomes (KDIGO) guidelines suggest using a SCr computed from the Modification of Diet in Renal Disease (MDRD) with an estimated glomerular filtration rate of 75 ml/min/1.73 m2. We aimed to identify the best surrogate method for baseline SCr to assess AKI diagnosis and outcomes. Methods We compared the use of 1) first SCr at hospital admission 2) minimal SCr over 2 weeks after intensive care unit admission 3) MDRD computed SCr and 4) Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) computed SCr to assess AKI diagnosis and outcomes. We then performed multilinear regression models to predict preadmission SCr and imputation strategies to assess AKI diagnosis. Results Our one-year retrospective cohort study included 1001 critically ill adults; 498 of them had preadmission SCr values. In these patients, AKI incidence was 25.1% using preadmission SCr. First SCr had the best agreement for AKI diagnosis (22.5%; kappa = 0.90) and staging (kappa = 0.81). MDRD, CKD-EPI and minimal SCr overestimated AKI diagnosis (26.7%, 27.1% and 43.2%;kappa = 0.86, 0.86 and 0.60, respectively). However, MDRD and CKD-EPI computed SCr had a better sensitivity than first SCr for AKI (93% and 94% vs. 87%). Eighty-eight percent of patients experienced renal recovery at least 3 months after hospital discharge. All methods except the first SCr significantly underestimated the percentage of renal recovery. In a multivariate model, age, male gender, hypertension, heart failure, undergoing surgery and log first SCr best predicted preadmission SCr (adjusted R2 = 0.56). Imputation methods with first SCr increased AKI incidence to 23.9% (kappa = 0.92) but not with MDRD computed SCr (26.7%;kappa = 0.89). Conclusion In our cohort, first SCr performed better for AKI diagnosis and staging, as well as for renal recovery after hospital discharge than MDRD, CKD-EPI or minimal SCr. However, MDRD SCr and CKD-EPI SCr improved AKI diagnosis sensitivity. Imputation methods minimally increased agreement for AKI diagnosis.

Background: Central blood pressure (CBP) is a better predictor of cardiovascular burden than peripheral blood pressure (BP). While studies have suggested a reduction in peripheral BP with statins, it remains uncertain to what extent statins reduce CBP and whether this reduction is mediated through a decrease in LDL-cholesterol (LDL). Methods: Of the 20,004 CARTaGENE participants, 17,011 had CBP and LDL measurements (n = 13,439 without, n = 3,133 with statins). Linear and logistic regression analyses were used to evaluate the association between CBP, LDL and statin use (after stratification for treatment indication for the latter). The impact of LDL on the association between statin use and CBP was determined by mediation analyses. All analyses were adjusted for age, sex, diabetes, cardiovascular disease, smoking, eGFR, BMI, uric acid, heart rate, anti-hypertensive agents and aspirin. Results: Lower levels of LDL were associated with lower systolic and diastolic CBP in participants treated with (b = 0.098 and 0.125; p < 0.001) and without statins (b = 0.089 and 0.105; p < 0.001). Statin use as primary prevention (per ACC/AHA guidelines; n = 8,865) was also associated with lower systolic CBP, diastolic CBP and central pulse pressure (b = −0.091, −0.073 and −0.055; p < 0,001). Mediation analyses demonstrated that 15%, 46% and -22% of these effects were achieved through the concomitant changes in LDL (Table 1). In secondary prevention (n = 995), statins use was not associated with lower CBP, although the small sample size may lack power. Conclusion: In this populational cohort, statin use as primary prevention is associated with lower CBP. These changes are mediated directly by statins but also indirectly through effects on LDL.