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Abstract Introduction: Subclinical kidney dysfunction may contribute to salt-sensitive hypertension. We assessed the association between the urinary sodium-potassium ratio (Na/K ratio) and blood pressure (BP) in a general population cohort without diabetes, chronic kidney disease, cardiovascular disease, or treated hypertension. We investigated whether any such association was mediated by the kidney function markers measured glomerular filtration rate (mGFR), urinary albumin-creatinine ratio (ACR), and urinary epidermal growth factor-creatinine ratio (EGF-Cr). Methods: The Tromsø Study is a population-based study of inhabitants of the municipality of Tromsø, Northern Norway. Participants aged 50–62 years, without diabetes, chronic kidney disease, or cardiovascular disease, were invited to the substudy Renal Iohexol Clearance Survey in Tromsø 6 (RENIS-T6; 2007–09). For the present study, we excluded participants reporting the use of 1 or more antihypertensive agents, leaving 1,311 RENIS-T6 participants for a cross-sectional analysis. We measured office BP, 24-h ambulatory blood pressure (ABP), and mGFR using iohexol clearance. Na/K ratio, ACR, and EGF-Cr were measured in morning urine samples. Results: Urinary Na/K ratio was significantly associated with systolic office BP and ABP independently of cardiovascular risk factors and kidney function markers. A one-standard deviation unit increase in the Na/K ratio was associated with increased systolic ABP by 1.0 (0.3–1.6) mm Hg. Urinary Na/K ratio showed a stronger association with office BP than ABP. EGF-Cr, ACR, and mGFR did not mediate the relationship between urinary Na/K ratio and systolic BP. Conclusions: In a representative sample of the middle-aged North-European population without diabetes, chronic kidney disease, cardiovascular disease, or treated hypertension, there was a consistent association between urinary Na/K ratio and BP. The association with BP was not mediated through kidney function measures, suggesting a relationship between a diet with high sodium and low potassium and higher BP regardless of kidney function.

Background Elevated serum uric acid (SUA) is associated with poor prognosis in patients with cardiovascular disease, yet it is still not decided whether the role of SUA is causal or only reflects an underlying disease. The purpose of the study was to investigate if SUA was an independent predictor of 5-year all-cause mortality in a propensity score matched cohort of chronic heart failure (HF) outpatients. Furthermore, to assess whether gender or renal function modified the effect of SUA. Methods Patients ( n  = 4684) from the Norwegian Heart Failure Registry with baseline SUA were included in the study. Individuals in the highest gender-specific SUA quartile were propensity score matched 1:1 with patients in the lowest three SUA quartiles. The propensity score matching procedure created 928 pairs of patients (73.4% males, mean age 71.4 ± 11.5 years) with comparable baseline characteristics. Kaplan Meier and Cox regression analyses were used to investigate the independent effect of SUA on all-cause mortality. Results SUA in the highest quartile was an independent predictor of all-cause mortality in HF outpatients (hazard ratio (HR) 1.19, 95% confidence interval (CI) 1.03–1.37, p -value 0.021). Gender was found to interact the relationship between SUA and all-cause mortality ( p -value for interaction 0.007). High SUA was an independent predictor of all-cause mortality in women (HR 1.65, 95% CI 1.24–2.20, p -value 0.001), but not in men (HR 1.06, 95% CI 0.89–1.25, p -value 0.527). Renal function did not influence the relationship between SUA and all-cause mortality ( p -value for interaction 0.539). Conclusions High SUA was independently associated with inferior 5-year survival in Norwegian HF outpatients. The finding was modified by gender and high SUA was only an independent predictor of 5-year all-cause mortality in women, not in men.

The impact of serum uric acid on cardiovascular outcomes in the LIFE study. The Losartan Intervention For Endpoint reduction in hypertension (LIFE) study demonstrated the superiority of a losartan-based regimen over atenolol-based regimen for reduction of cardiovascular (CV) morbidity and mortality. It has been suggested that the LIFE study results may be related to the effects of losartan on serum uric acid (SUA). SUA has been proposed as an independent risk factor for CV morbidity and death. Cox regression analysis was used to assess relationship of SUA and treatment regimens with the LIFE primary composite outcome (CV death, fatal or nonfatal myocardial infarction, fatal or nonfatal stroke). Baseline SUA was significantly associated with increased CV events [hazard ratio (HR) 1.024 (95% CI 1.017–1.032) per 10 μmol/L, P < 0.0001] in the entire study population. The association was significant in women [HR = 1.025 (1.013–1.037), P < 0.0001], but not in men [HR = 1.009 (0.998–1.019), P = 0.108]. After adjustment for Framingham risk score (FRS), SUA was no longer significant in the entire study population [HR = 1.006 (0.998–1.014), P = 0.122] or in men [HR = 1.006 (0.995–1.017), P = 0.291], but was significant in women [HR = 1.013 (1–1.025), P = 0.0457]. The baseline-to-end-of-study increase in SUA (standard deviation, SD) was greater (P < 0.0001) in atenolol-treated subjects (44.4 ± 72.5 μmol/L) than in losartan-treated subjects (17.0 ± 69.8 μmol/L). SUA as a time-varying covariate was strongly associated with events (P < 0.0001) in the entire population. The contribution of SUA to the treatment effect of losartan on the primary composite end point was 29% (14%-107%), P = 0.004. The association between time-varying SUA and increased CV risk tended to be stronger in women (P < 0.0001) than in men (P = 0.0658), although the gender-outcome interaction was not significant (P = 0.079). The increase in SUA over 4.8years in the LIFE study was attenuated by losartan compared with atenolol treatment, appearing to explain 29% of the treatment effect on the primary composite end point. The association between SUA and events was stronger in women than in men with or without adjustment of FRS.

Background It is unclear whether serum uric acid (SUA) is associated with development of new-onset diabetes (NOD) in patients with hypertension and left ventricular hypertrophy (LVH). The aim of the present investigation was to test the hypothesis that SUA predicts development of NOD in these patients. Methods In the Losartan Intervention For Endpoint reduction in hypertension (LIFE) study, a double-masked, parallel-group design, 9,193 patients with hypertension and electrocardiographic LVH were randomized to losartan- or atenolol-based antihypertensive treatment and followed for a mean of 4.9 years. At baseline, 7,489 patients with available SUA measurements did not have diabetes mellitus and were thus at risk of its development during the study. We used Cox regression analyses to investigate whether SUA predicted development of NOD. Results NOD developed in 522 of 7,489 patients. The association between baseline SUA and development of NOD was significant (hazard ratio (HR) 1.29 per s.d. (1.3 mg/dl), 95% confidence interval (CI) 1.18–1.42, P < 0.001) after adjustment for treatment with losartan vs. atenolol, baseline serum glucose, urinary albumin/creatinine ratio, estimated glomerular filtration rate and Framingham risk score, time-varying systolic and diastolic blood pressure, and time-varying LVH by Cornell voltage-duration product and Sokolow–Lyon voltage. In parallel analyses, baseline quartiles of SUA were significantly associated with increasing NOD (HR 1.28, 95% CI 1.18–1.40, P < 0.001). Time-varying SUA was also associated with NOD (HR 1.10 per s.d. [1.3 mg/dl], 95% CI 1.02–1.19, P = 0.015). Conclusion Our analysis suggests that SUA is an independent risk marker for NOD in hypertensive patients with LVH.

Observational data have suggested that increased water intake decreases the risk of CHD. A postulated mechanism is that increased water ingestion reduces blood viscosity. The aim of the present study was to assess the effect of increased fluid intake on blood viscosity. Men (n 67) and postmenopausal women (n 27) with one or more risk factors for CVD who reported intake of ≤ 0·5 litres water daily were randomised to a control group (n 31), an intervention group (n 32) that increased their daily water intake by 1 litre/d and an intervention group (n 31) that ingested 1 litre blueberry juice/d. All were encouraged to continue their usual diet and lifestyle. Whole-blood viscosity and blood and urine chemistries were measured by standard techniques after 2 and 4 weeks. Urine volume increased (by a median of 872 and 725 ml in the water and blueberry juice groups, respectively, v. 10 ml in the control group; P ≤ 0·002), confirming the subjects' adherence to the protocol. Urine osmolality and urinary levels of Na, K and creatinine decreased in the water and blueberry juice groups v. the controls (P < 0·05). No change was seen in whole-blood viscosity or in levels of fibrinogen, total protein, lipids, glucose, insulin, C-peptide or other chemistry and haematology variables. In conclusion, a postulated protective effect of increased water or fluid intake is not explained by a change in blood viscosity and increased fluid intake does not influence CVD risk factors in the short term.

There may be a link among stress, adrenal medullary activation, and the development of hypertension. Obesity is characterized by sympathetic activation and predisposes to hypertension, but may be associated with low or normal adrenal medullary activity. We hypothesized that plasma epinephrine (E) levels and adrenal medullary responsiveness to mental stress are lower in overweight than in lean borderline hypertensive subjects. We compared groups of lean ( n = 62) and overweight ( n = 29) borderline hypertensive young men as well as lean ( n = 36) and overweight ( n = 7) normotensive young men from the same population. Plasma catecholamines and heart rate (HR) were measured at rest during a hyperinsulinemic glucose clamp and during mental arithmetic–induced stress. Plasma norepinephrine (NE) and E, HR, and responses to stress were increased in borderline hypertensive subjects. Our results showed that NE was increased only in lean borderline hypertensive subjects at rest, but in overweight subjects as well during stress, with ΔNE being similar in lean and overweight subjects. We found that E was higher in lean than in overweight borderline hypertensive subjects at rest and during stress (both P < .001), as were ΔE and ΔHR (both P < .05). Independent of BP status, body mass index was negatively related to E during stress ( P < .01) and waist circumference negatively related to resting E ( P < .001) and ΔHR ( P = .02). Sympathetic neural activity and responsiveness are increased in borderline hypertensive young men, but measures of overweight are independently related to lower plasma E and HR responses. We suggest that adrenal medullary activation in borderline hypertension mainly characterizes lean subjects.

OR-32 Key Words: Whole Blood Viscosity, Autonomic Nervous System, Hypertension

A fixed-dose combination of losartan/hydrochlorothiazide (HCTZ) therapy may be a logical choice for antihypertensive treatment, including for initial therapy in patients with blood pressure elevation >20/10 mmHg above treatment target. The renin-angiotensin-aldosterone-system-activating effect of hydrochlorothiazide augments the efficacy of blocking the angiotensin II type 1 (AT1) receptor with losartan. Some adverse effects associated with hydrochlorothiazide, including increased risk for new-onset diabetes mellitus, may be offset by losartan. Losartan was frequently administered with hydrochlorothiazide in the Losartan Intervention For Endpoint reduction in hypertension (LIFE) study, in which there was a 25% risk reduction for stroke in the losartan-based compared with the atenolol-based treatment group. The efficacy, tolerability, and convenience of losartan/HCTZ combination therapy may increase patient compliance and lower risk for stroke, a devastating outcome in patients with hypertension.

Increased whole-blood viscosity (WBV) is related to hypertension and insulin resistance, which are associated with increased sympathetic and decreased vagal activity. We tested whether WBV increases during mental stress and relates to autonomic nervous system activity and insulin sensitivity, and compared borderline hypertensive and normotensive subjects. Twenty borderline hypertensive men, 21 normotensive men, and 10 women were studied during 90-min hyperinsulinemic glucose clamp and 7-min mental arithmetic stress test (MST). WBV (rotational rheometer) at shear rates 0.5 and 201 s−1, and plasma norepinephrine (NE) were measured. Heart rate variability (HRV) was computed from continuous ECG and baroreflex sensitivity (BRS) from finger blood pressure (BP) recordings (transfer technique). WBV correlated negatively with insulin sensitivity in men (r = −0.40, P <0.01) and women (r = −0.64, P <0.05). WBV increased during MST (shear rate 0.5 s−1: 17.6–18.7 mPas, P <0.01; shear rate 201 s−1: 3.7–3.9 mPas, P <0.0001). NE increased (P <0.0001) while HRV (P <0.0001) and BRS (P <0.001) declined. WBV was positively related to NE and negatively to high-frequency HRV or BRS, independent of adiposity, BP group, and gender. ΔWBV (shear rate 201 s−1: β = 0.27, P <0.05) and ΔNE (β = 0.55, P <0.0001) were independently related to diastolic ΔBP. During MST, WBV (both shear rates) and ΔWBV (shear rate 0.5 s−1) were higher in borderline hypertensive than normotensive men (all P <0.05). WBV is adversely affected by increased sympathetic activity and blunted vagal HR control. The hemorheological effect of mental stress is increased in borderline hypertension and may contribute to the acute increase in BP. Altered autonomic nervous system function and increased WBV may be related components of the insulin resistance syndrome. (See Table)Correlation Coefficients in men (n = 41) between Whole Blood Viscosity and Indices of Autonomic Nervous System Activity. Whole Blood Viscosity RR LF HF BRS NE Glucose Clamp 0.5 s−1 −0.46† −0.17 −0.31* −0.43† 0.44† 201 s−1 −0.51‡ −0.36* −0.31* −0.44† 0.31 Mental Stress 0.5 s−1 −0.46† −0.32* −0.32* −0.41* 0.51‡ 201 s−1 −0.54‡ −0.39* −0.42† −0.31 0.37* RR, mean R-R interval; LF, low-frequency power; HF, high-frequency power; *P< 0.05, ; †>P< 0.01, ‡P< 0.001.

1. We studied insulin sensitivity in relation to mean R-R interval length (RR), heart rate variability (HRV), and baroreflex sensitivity (BRS). 2. Males (age 22-24 years) with high (≥140/90 mmHg, n=20), and low-normal (≤115/75 mmHg, n=21), and females (age 23-27 years) with normal (n=10) screening BP were studied. RR and HRV were assessed from 2 h Holter ECGs (supine rest), recorded during 90 min hyperinsulinemic isoglycemic glucose clamp and preceding 30 min. BRS was calculated (transfer technique) from beat-to-beat finger BP (Finapres), recorded during clamp. Insulin sensitivity was measured (last 20 min) as glucose disposal rate/serum insulin (GDR/I) and related to RR, HRV variables, BRS, fasting insulin:glucose ratio (FIGR), waist circumference (WC), and body mass index (BMI). 3. GDR/I correlated positively with BRS and most HRV variables. RR was related to GDR/I in the whole material, and in all groups: males with high (r = 0.59, P<0.01) and low-normal (r = 0.47, P<0.05) screening BP, and females (r = 0.55, P= 0.1). In stepwise multiple regression, RR (P=0.0008), FIGR (P=0.02), and WC (P=0.03) explained 52% of variance in GDR/I, with adjustment for BP group, gender, and BMI, while HRV variables and BRS were not independently related to GDR/I when adjusting for RR or FIGR. 4. Insulin sensitivity is related to sympathovagal balance and waist circumference. We suggest resting R-R interval (or heart rate) as an independent predictor of insulin sensitivity in young subjects. TableCorrelation Coefficients (r) Between GDR/I and Other Variables in the Whole Material Variable r P BMI −0.44 0.001 WC −0.47 0.0006 FIGR −0.59 <0.0001 RR 0.54 <0.0001 TP 0.44 0.001 HF 0.35 0.01 LF 0.36 0.009 SDNN 0.43 0.001 RMMSD 0.31 0.03 PNN50 0.42 0.02 BRS (n = 47) 0.32 0.03 TP = total power; HF = high frequency power; LF = low frequency power; SDNN = SD of all R-R intervals; RMSSD = square root of mean sum of squares of differences between adjacent R-R intervals. PNN50, % of R-R intervals differing >50 ms from preceding interval. See text for other abbreviations.