Increased Central Venous Pressure Is Associated With Impaired Renal Function and Mortality in a Broad Spectrum of Patients With Cardiovascular Disease
Heart Failure
Objectives:
We sought to investigate the relationship between increased central venous pressure (CVP), renal function, and mortality in a broad spectrum of cardiovascular patients.
Background:
The pathophysiology of impaired renal function in cardiovascular disease is multifactorial. The relative importance of increased CVP has not been addressed previously.
Methods:
A total of 2,557 patients who underwent right heart catheterization in the University Medical Center Groningen, the Netherlands, between January 1, 1989, and December 31, 2006, were identified, and their data were extracted from electronic databases. Estimated glomerular filtration rate (eGFR) was assessed with the simplified modification of diet in renal disease formula.
Results:
Mean age was 59 ± 15 years, and 57% were men. Mean eGFR was 65 ± 24 ml/min/1.73 m2, with a cardiac index of 2.9 ± 0.8 l/min/m2 and CVP of 5.9 ± 4.3 mm Hg. We found that CVP was associated with cardiac index (r = −0.259, p < 0.0001) and eGFR (r = −0.147, p < 0.0001). Also, cardiac index was associated with eGFR (r = 0.123, p < 0.0001). In multivariate analysis CVP remained associated with eGFR (r = −0.108, p < 0.0001). In a median follow-up time of 10.7 years, 741 (29%) patients died. We found that CVP was an independent predictor of reduced survival (hazard ratio: 1.03 per mm Hg increase, 95% confidence interval: 1.01 to 1.05, p = 0.0032).
Conclusions:
Increased CVP is associated with impaired renal function and independently related to all-cause mortality in a broad spectrum of patients with cardiovascular disease.
Introduction
Renal dysfunction is a strong and independent predictor of prognosis in the general population but also in patients with diabetes, hypertension, coronary artery disease, and heart failure (1–7). The pathophysiology is multifactorial and associated with decreased renal perfusion, atherosclerosis and inflammation, endothelial dysfunction, and neurohormonal activation (8–10). We recently showed that in patients with cardiac dysfunction secondary to pulmonary hypertension, not only was renal perfusion strongly associated with renal function impairment but also with venous congestion (11). However, it is unclear whether this observation is limited to those patients with reduced cardiac function and pulmonary hypertension or whether it also may be present in patients with a mixture of cardiovascular diseases with varying etiologies and treatments. In addition, there are only limited data on the relationship between venous congestion, as estimated by central venous pressure (CVP) and the impact on prognosis, even in patients with and without heart failure. The studies that have been conducted are either small or include only noninvasive assessment of increased venous congestion, such as jugular venous pressure (12–15). In the present study, we therefore aimed to investigate the relationship between CVP, renal function, and mortality in patients with a mixture of cardiovascular diseases with varying etiologies and treatments.
Methods
Case identification
Case identification
Using the patient registration system of the University Medical Center Groningen, the Netherlands, all patients that underwent right heart catheterization between January 1, 1989, and December 31, 2006, were identified.
Data extraction
Retrospective chart review was performed to analyze characteristics of all patients that were identified during the electronic search. For each patient, date of birth, sex, race, and weight and height were collected. Comorbid conditions, including hypertension, coronary artery disease, cardiac valve disease, congenital heart disease, history of stroke, hypercholesterolemia, and diabetes, in addition to medical treatment at the time of catheterization also were extracted for each patient. Furthermore, the reason for performing right heart catheterization was identified. The study was approved by the institutional review board of the University Medical Center Groningen.
Heart catheterization
Hemodynamic variables obtained during catheterization included systolic blood pressure (mm Hg), diastolic blood pressure (mm Hg), cardiac output (thermodilution, l/min), and right atrial pressure as indicator of CVP (CVP, mm Hg). Cardiac index (l/min/m2) was determined as cardiac output divided by the body surface area, which was calculated as: 0.007184·weight0.425·length0.725. Measurements obtained from cardiac catheterization were obtained from the patient during a resting state.
Renal function measurement
Serum creatinine at the day of catheterization was extracted. For the patients who did not have laboratory measurements on the day of catheterization, measurements obtained within 3 days before catheterization were taken as the baseline value. Of patients included in the study, 2,282 (89%) had at least 1 serial creatinine measurement within 3 days of catheterization. Renal function was estimated as glomerular filtration rate (GFR) by using the simplified modification of diet in renal disease equation (estimated glomerular filtration rate [eGFR] [ml/min/1.73 m2] = 186.3 × [serum creatinine]−1.154 × age−0.203 × [0.742 if female]) (16). Estimated GFR values >200 ml/min/1.73 m2 were set equal to 200 ml/min/1.73 m2, according to Coresh et al. (17).
Mortality data
Survival status was determined using the electronic patient registration database of the University Medical Center Groningen. Follow-up started directly after right heart catheterization. The primary end point consisted of death from any cause.
Statistical analysis
Data are given as mean ± standard deviation when normally distributed, as median and interquartile range when skewed distributed, and as frequencies and percentages for categorical variables. Associations between baseline variables were evaluated by means of 1-way analysis of variance, the Kruskal-Wallis test, and chi-square or Fisher exact tests, when appropriate. Two-sided p values were used, taking p < 0.05 to be statistically significant. CVP was divided into tertiles to assess relationships between baseline characteristics and CVP. A fractional polynomial parameterization of exposure was used to explore nonlinearity between different predictors and renal function. In this technique, each exposure value is expressed as a polynomial of degree >1 (e.g., quadratic, cubic, and so on), yielding an estimated model with multiple predictors (i.e., separate predictors for the linear, quadratic, terms, respectively). We used a Cox proportional hazards survival model to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). At first, in multivariate analysis, CVP was fitted into a stepwise multivariate Cox regression analysis on a continuous scale. In secondary analysis, CVP was fitted into the model and, in multiple steps, the model was adjusted for other variables and parameters. The internal validity of the regression model was assessed by the bootstrap resampling technique (18). For each of 100 bootstrap samples, the model was refitted and tested on the original sample to obtain a bias-corrected estimate of predictive accuracy. Statistical analyses were performed using SPSS version 12.0 (Chicago, Illinois) and STATA version 9.0 (College Station, Texas).
Results
Baseline characteristics
Baseline characteristics
A total of 3,757 right heart catheterizations were conducted between 1989 and 2006. Of these, 2,557 (68%) were first or only right heart catheterization of unique patients and formed the study population. Main reasons for right heart catheterization are shown in Table 1. Aortic and mitral valve disorders accounted for 44% of indications, whereas in 16%, acute or chronic heart failure was the predominant reason. Mean age was 59 ± 15 years, and 57% were men (Table 2). In the total study population, both mean cardiac index (2.9 ± 0.8 l/min/m2) and mean CVP (5.9 ± 4.3 mm Hg) were within the normal range. The distribution of CVP among the study population is shown in Figure 1. Mean eGFR was moderately impaired: 65 ± 24 ml/min/1.73 m2.
| Percentage of Patients | |
|---|---|
| Aortic valve disorders | 29 |
| Aortic valve stenosis | 23 |
| Aortic valve insufficiency | 6 |
| Mitral valve disorders | 15 |
| Mitral valve insufficiency | 14 |
| Mitral valve stenosis | 1 |
| Pulmonary valve disorders | 1 |
| Pulmonary valve insufficiency | 0.8 |
| Pulmonary valve stenosis | 0.2 |
| Heart failure | 16 |
| Coronary artery disease | 13 |
| Pre-transplantation (noncardiac) | 11 |
| Rhythm disorders | 5 |
| Pulmonary hypertension | 3 |
| Congenital heart disease | 2 |
| Post-heart transplantation | 2 |
| Other | 6 |
| Total | Tertile 1 (0 to 3 mm Hg) | Tertile 2 (4 to 6 mm Hg) | Tertile 3 (>6 mm Hg) | p Value for Trend | |
|---|---|---|---|---|---|
| n | 2,557 | 911 | 855 | 791 | |
| Age (yrs) | 59±15 | 60±15 | 59±15 | 58±15 | 0.0032 |
| Sex (% male) | 57 | 59 | 58 | 54 | NS |
| SBP (mm Hg) | 133±29 | 133±28 | 134±27 | 129±31 | 0.0100 |
| DBP (mm Hg) | 68±13 | 66±12 | 68±12 | 69±13 | 0.0010 |
| CO (l/min) | 5.5±1.6 | 5.7±1.6 | 5.5±1.5 | 5.0±1.5 | <0.0001 |
| Cardiac index (l/min/m2) | 2.9±0.8 | 3.1±0.7 | 3.0±0.7 | 2.7±0.8 | <0.0001 |
| CVP (mm Hg) | 5.9±4.3 | 2±1 | 5±1 | 11±4 | <0.0001 |
| eGFR (ml/min/1.73 m2) | 65±24 | 65±23 | 67±24 | 62±24 | 0.0001 |
| Medical history (%) | |||||
| Heart failure | 16 | 15 | 15 | 19 | NS |
| Coronary artery disease | 24 | 24 | 25 | 24 | NS |
| Congenital heart disease | 5 | 4 | 5 | 7 | 0.0189 |
| Valve disease | 51 | 50 | 55 | 49 | NS |
| Hypercholesterolemia | 6 | 7 | 5 | 6 | NS |
| Diabetes mellitus | 9 | 8 | 8 | 10 | NS |
| Hypertension | 20 | 21 | 20 | 18 | NS |
| Stroke | 5 | 4 | 5 | 6 | NS |
| Medication (%) | |||||
| Diuretics | 42 | 37 | 38 | 53 | 0.0001 |
| Beta-blocker | 28 | 25 | 29 | 31 | 0.0388 |
| ACEI or ARB | 38 | 36 | 32 | 45 | 0.0001 |
| Aldosterone antagonist | 9 | 5 | 6 | 15 | 0.0001 |
Distribution of CVP and Curvilinear Relationship Between CVP and eGFR in the Study Population
Adjusted for age, sex, and cardiac index. The curvilinear model had the following individual polynomial components for the relationship between CVP and eGFR: First order: Y = −25.8·(CVP + 1)/10 (Wald 28.2, p < 0.0001) and second order: Y = 35.7·([CVP + 1]/10)0.5 (Wald 17.4, p < 0.0001). CVP = central venous pressure, eGFR = estimated glomerular filtration rate.
The distribution of different factors over tertiles of CVP is shown in Table 2. Most of the characteristics were equally distributed across tertiles of CVP, except for the highest tertile (CVP >6 mm Hg). Both cardiac output and cardiac index were significantly lower in the highest tertile compared with lower tertiles (p < 0.0001), corresponding to r = −0.259 (p < 0.0001) for the association between CVP and cardiac index. Furthermore, patients in the highest tertile were treated more frequently with angiotensin-converting enzyme inhibitor/angiotensin-II receptor blockers, beta-blockers, diuretics, and aldosterone antagonists. Prevalence of heart failure showed a trend toward increasing with higher tertiles of CVP (p = 0.0781), whereas congenital heart disease was also more prevalent in the highest tertile. Finally, eGFR was significantly lower in the highest tertile of CVP, compared with both lower tertiles (p < 0.001).
Curvilinear fitting and the relationship between CVP and eGFR
Figure 1 shows the curvilinear relationship between CVP and eGFR in the total study population as obtained by fractional polynomial modeling. Estimated GFR showed a small increase when CVP increased from 1 to 6 mm Hg. However, in CVP values >6 mm Hg, a steep decrease is observed with increasing CVP values. This finding resulted in a partial correlation of r = 0.064, p = 0.0218 in patients with CVP ≤6 mm Hg, and r = −0.212, p < 0.0001 in patients with CVP >6 mm Hg (adjusted for age, sex, and cardiac index). On a continuous scale, CVP was also significantly associated with eGFR (r = −0.110, p < 0.0001) after transformation.
Besides CVP, age (r = −0.438, p < 0.0001), sex (r = 0.137, p < 0.0001), and cardiac index (r = 0.249, p < 0.0001) were associated with eGFR. In addition, lower eGFR values also were found to be related with the use of any type of cardiovascular medication and a history of diabetes and hypertension. There was a significant interaction between CVP and cardiac index on the relationship with eGFR. The observed biphasic relationship between CVP and eGFR was most pronounced in patients with relatively normal cardiac index (Fig. 2).
Curvilinear Relationship Between CVP and eGFR According to Different Cardiac Index Values
p = 0.0217 for interaction between cardiac index and CVP on the relationship with eGFR. Solid line = cardiac index <2.5 l/min/m2; dashed line = cardiac index 2.5 to 3.2 l/min/m2; dotted line = cardiac index >3.2 l/min/m2. Abbreviations as in Figure 1.
In multivariate analysis, CVP remained associated with eGFR (r = −0.108, p < 0.0001, adjusted for covariates), which was confirmed by bootstrap analysis (Online Table 1). After adjustment for the year of catheterization, the association between CVP and eGFR was numerically unchanged: r = −0.105, p < 0.0001. Excluding patients with a history of heart transplantation, who were likely to receive renal function compromising immunotherapy, CVP remained associated with eGFR (r = −0.108, p < 0.0001) in multivariate analysis. Including only patients without heart failure, similar associations were present (r = −0.080, p = 0.0034). Excluding both heart transplant recipients and heart failure patients, the association between CVP and eGFR remained (r = −0.079, p = 0.0042).
CVP and mortality
Mortality data were available in all patients, whereas time of death was available in 2,424 (95%) of patients. Median follow-up among survivors was 10.7 years and, during follow-up, 741 (29%) of the patients died. Crude mortality ranged from 24% in the lowest tertile to 29% and 35% in the 2 highest tertiles of CVP (p = 0.0001 for trend). On a continuous scale, greater CVP levels were associated with impaired survival (HR: 1.05 per mm Hg increase, 95% CI: 1.04 to 1.07, p < 0.0001). Kaplan-Meier survival curves for tertiles of CVP are shown in Figure 3, showing that patients with the greatest CVP in particular were at risk for increased mortality (HR for CVP >6 mm Hg vs. ≤6 mm Hg: 1.49, 95% CI: 1.26 to 1.76, p < 0.0001). Baseline eGFR (HR: 1.09 per 10 ml/min/1.73 m2 decrease, 95% CI: 1.05 to 1.13, p < 0.0001) and cardiac index (HR: 0.74 per l/min/m2 increase, 95% CI: 0.66 to 0.84, p < 0.0001) also were strong predictors of mortality. Other factors associated with reduced survival are shown in Table 3. In stepwise multivariate Cox regression analysis, CVP remained significantly associated with reduced survival (HR: 1.03 per mm Hg increase, 95% CI: 1.01 to 1.05, p = 0.0032) (Table 3). Finally, we fitted a second model, adjusting CVP for other covariates (Online Table 2). CVP remained an independent predictor of impaired survival (HR: 1.03 per mm Hg increase, 95% CI: 1.01 to 1.05, p = 0.0144). To account for the effects of changing therapy during the study inclusion time, we adjusted for the year of catheterization. This secondary analysis yielded similar results (HR: 1.03 per mm Hg increase, 95% CI: 1.00 to 1.05, p = 0.0207). Excluding patients with known heart failure and heart transplant recipients, CVP was still associated with mortality (HR: 1.03 per 5 mm Hg increase, 95% CI: 1.00 to 1.06, p = 0.0369).
Kaplan-Meier Analysis of Event-Free Survival According to Tertiles of CVP
HR: 1.22 (95% CI: 1.00 to 1.49), p = 0.0466 for CVP 4 to 6 mm Hg; HR: 1.65 (95% CI: 1.35 to 2.01), p < 0.0001 for CVP >6 mm Hg, both compared with CVP 0 to 3. CI = confidence interval; HR = hazard ratio; other abbreviations as in Figure 1.
| Univariate | Multivariate | ||||
|---|---|---|---|---|---|
| Variables | Hazard Ratio (95% CI) | p Value | Hazard Ratio (95% CI) | Wald Statistic | p Value |
| Age (per 10 yr increase) | 1.05(1.00–1.10) | 0.0880 | 1.21(1.12–1.31) | 25.4 | <0.0001 |
| Sex | 1.03(0.88–1.20) | 0.713 | |||
| Cardiac index (per l/min/m2 increase) | 0.74(0.66–0.84) | <0.0001 | 0.81(0.71–0.93) | 9.1 | 0.0026 |
| CVP (per mm Hg increase) | 1.05(1.04–1.07) | <0.0001 | 1.03(1.01–1.05) | 8.7 | 0.0032 |
| eGFR (per 10 ml/min/1.73 m2 decrease) | 1.09(1.05–1.13) | <0.0001 | |||
| Medication | |||||
| Diuretic use | 1.43(1.22–1.67) | <0.0001 | |||
| ACEI or ARB use | 1.29(1.10–1.52) | 0.0017 | |||
| Aldosterone antagonist use | 1.92(1.50–2.45) | <0.0001 | 1.50(1.10–2.02) | 6.9 | 0.0087 |
| Medical history (%) | |||||
| Coronary artery disease | 1.26(1.05–1.50) | 0.0112 | |||
| Diabetes mellitus | 1.83(1.44–2.31) | <0.0001 | 1.76(1.34–2.31) | 16.6 | <0.0001 |
| Indication for catheterization | |||||
| Aorta insufficiency | 0.63(0.43–0.93) | 0.0203 | |||
| Congenital heart disease | 0.36(0.17–0.77) | 0.0078 | |||
| Pre-transplantation (noncardiac) | 1.50(1.21–1.85) | <0.0001 | 2.54(1.90–3.40) | 39.2 | <0.0001 |
| Heart failure | 1.48(1.21–1.85) | 0.0001 | 1.71(1.34–2.20) | 18.1 | <0.0001 |
| Rhythm disorders | 0.49(0.29–0.82) | 0.0062 | |||
Discussion
The present study shows that increased CVP is associated with impaired renal function in a broad spectrum of cardiovascular patients who underwent right heart catheterization. In addition, the slope between CVP and impaired eGFR was steeper with relatively preserved cardiac function. Finally, an increased CVP was a strong and independent determinant of all-cause mortality, which was especially observed in patients with a CVP >6 mm Hg.
There are only limited data on the relationship between increased CVP and renal impairment. Studies in animals have shown that increasing renal venous pressure leads to a reduction in glomerular filtration, which was probably mediated by a decreased renal perfusion (19). Renal vein constriction led to a decrease in GFR in rats (20), whereas renal function decreased when renal vein pressure was increased in dogs, but only when cardiac output was reduced (21). We recently showed that in patients with reduced cardiac function, secondary to pulmonary hypertension, increased CVP was strongly associated with renal impairment, especially when renal perfusion was already impaired (11). Early studies on increased renal vein pressure in heart failure patients and animals showed a marked reduction in renal blood flow as well as water and salt excretion (22,23), but the effect on GFR was not uniform. One small report showed a strong relationship between CVP and renal blood flow in advanced heart failure (24).
Drazner et al. (13) reported that in patients with increased jugular venous pressure on examination, serum creatinine was significantly greater. In patients who underwent elective cardiac surgery, pre-operative presence of high CVP was a strong predictor of the occurrence of acute renal injury, independent of the presence of low CO (25).
However, especially in patients with preserved cardiac function, data regarding the relationship between CVP and renal function are scarce. Diastolic dysfunction, a disease characterized by increased filling pressures, often coexists with renal failure and vice versa (26–28). Interestingly, a recent study showed that renal dysfunction is even more important in defining mortality risk in patients with preserved cardiac function compared with those with systolic dysfunction (29,30). Our present study confirmed that increased CVP is an important risk factor for decreased renal function in patients with preserved and decreased cardiac function.
Curvilinear effect of CVP with eGFR
We observed a biphasic relationship between eGFR and increasing CVP. In the physiologic ranges of CVP, up to 6 mm Hg, eGFR increases gradually. This subtle increase in eGFR may be a reflection of increased cardiac filling to preserve cardiac function by Frank-Starling mechanism (pre-load), and subsequent renal perfusion (31). This gradual increase in eGFR was observed across the full spectrum of low to high cardiac index. We observed a decrease in eGFR when CVP increases above 6 mm Hg. In these patients, the equilibrium among venous return, CO, and CVP may have shifted toward a plateau phase or optimum, where CO is not further increased in response to greater CVP (32). Greater CVP levels will then decrease renal perfusion pressure, which will further impair eGFR. However, if greater CVP levels preserve CO, and despite this mechanism, eGFR decreases with greater CVP, this action suggests that increased CVP also may exert an effect on GFR in this group of patients, independent of renal perfusion.
Importantly, the relationship between CVP and GFR is bound to be bidirectional. Not only may CVP influence GFR, but even mildly impaired renal function may initiate salt and water retention, resulting in increased cardiac filling pressures (33). Because of the cross-sectional nature of our analysis, we were unable to investigate the cause-effect associations, and our present analysis must be regarded as hypothesis generating.
CVP and eGFR in patients with and without cardiac dysfunction
Of particular interest is the interaction between cardiac index and CVP on eGFR. Patients who have a combination of reduced perfusion (cardiac index) and increased venous congestion (CVP) suffer from fluid overload and decreased organ perfusion, leading, among other things, to renal dysfunction. We showed that patients with high CVP levels often also have decreased cardiac index and reduced eGFR. Remarkably, CVP and cardiac index showed an interaction on the relationship with eGFR, with an even more pronounced relationship in patients with relatively normal cardiac index. This further strengthens the observation of a relationship between CVP and eGFR, which is not exclusively due to reduced cardiac systolic function. It also challenges the intuitive notion that fluid overload, although deleterious from a cardiovascular perspective, will invariably be beneficial from the point of view of preservation of renal function. Because our analysis does not allow to dissect cause and effect relationships, however, it might also well be that the relatively normal cardiac index is maintained at the expense of the increased CVP. In that case, apparently, such a renal hemodynamic profile does not translate into better renal function. Our present findings seem inconsistent with our earlier findings, showing that patients with reduced renal perfusion in particular are prone to a detrimental effect of CVP on GFR (11). However, we did not measure renal hemodynamics or renal function by clearance techniques in the present study, and the population was also different. Furthermore, our previous study consisted of patients with much lower cardiac indexes, all of which makes a comparison difficult. Nevertheless, this inconsistency needs to be further addressed in future studies.
New therapeutic agents in the treatment of acute heart failure that are specifically targeted at improvement of cardiac function and reducing venous congestion recently have shown promising results regarding renal function. A substudy of the SURVIVE (Survival of Patients With Acute Heart Failure in Need of Intravenous Inotropic Support) study, in which levosimendan was compared with dobutamine, showed that improvement of renal function was more pronounced in the group receiving levosimendan, despite the obvious positive inotropic effect of dobutamine (34). The specific venodilatory effect observed with levosimendan, with subsequent reduced CVP, may be the pathophysiologic mechanism, supporting a direct pathophysiologic link between CVP and renal impairment (35).
CVP and mortality
Increased CVP and jugular venous pressure predispose to the development of heart failure in patients with cardiac dysfunction and have been associated with reduced survival in patients with heart failure (12,13,36). Small studies have shown that invasive assessment of CVP is a predictor of cardiovascular outcome in patients with advanced heart failure (14,15). In other selected patient populations, such as patients who underwent Fontan surgery or lung transplantation, greater CVPs were strong predictors of outcome (37,38). The prognostic importance of increased CVP in patients with normal cardiac function has not been reported previously. We show that in a selected patient population, increased CVP remained a determinant of all-cause mortality, independent of cardiac function. This association with mortality was most prominent in patients with severely increased CVP, even after adjustment for other baseline characteristics. This finding was additive to the observation that greater CVP levels predispose to lower eGFR, which may influence survival by different mechanisms.
Clinical implications
Increased CVP frequently is observed in patients with and without reduced cardiac function, comprising almost 20% of patients in the present patient population. Recognition of these patients is essential because not only is renal dysfunction much more frequently observed, but the risk of mortality also increases with increasing CVP levels. Treatment to selectively lower CVP may be favorable to reduce symptoms and signs of congestion, improve GFR, and improve prognosis.
Study limitations
The present study comprises a selected patient population that had a specific indication for right heart catheterization. Patients undergoing right heart catheterization are prone to have greater right-sided filling pressures, and the present observations may therefore not represent the general cardiovascular population. However, this is a large cohort study, with invasive cardiac function and CVP measurements across the full range. Second, this is a retrospective analysis, and no invasive data are available on renal blood flow and true GFR in these patients. Furthermore, it should be addressed that our study population had very different catheterization indications, medical history, and medication regime, all of which could have influenced our results. In our study, the presence of heart failure was a clinical diagnosis, rather than related to reduced cardiac index on catheterization. Therefore, the prevalence of heart failure in our study is most likely underestimated. The relationship between increased CVP and renal perfusion has been observed in heart failure. However our present study is the first to show an independent effect of CVP on renal function. Finally, the retrospective nature of this study and the cross-sectional design limited our ability to investigate the cause-effect relationship between renal impairment and increased CVP, which may actually mutually influence each other.
Conclusion
Increased CVP is associated with impaired renal function and is independently related to all-cause mortality in a broad spectrum of patients with cardiovascular disease.
1. : "Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization". N Engl J Med 2004; 351: 1296.
2. : "Renal function: the Cinderella of cardiovascular risk profile". J Am Coll Cardiol 2001; 38: 1782.
3. : "Accelerated decline and prognostic impact of renal function after myocardial infarction and the benefits of ACE inhibition: the CATS randomized trial". Eur Heart J 2003; 24: 412.
4. : "All-cause and cardiovascular mortality in diabetic subjects increases significantly with reduced estimated glomerular filtration rate (eGFR): 10 years' data from the South Tees Diabetes Mortality study". Diabetes Med 2007; 24: 10.
5. : "Renal outcomes in high-risk hypertensive patients treated with an angiotensin-converting enzyme inhibitor or a calcium channel blocker vs a diuretic: a report from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT)". Arch Intern Med 2005; 165: 936.
6. : "Chronic kidney disease, mortality, and treatment strategies among patients with clinically significant coronary artery disease". J Am Soc Nephrol 2003; 14: 2373.
7. : "Renal function as a predictor of outcome in a broad spectrum of patients with heart failure". Circulation 2006; 113: 671.
8. : "Role of the Kidney in Congestive Heart-Failure - Relationship of Cardiac Index to Kidney-Function". Drugs 1990; 39: 10.
9. : "Impaired renal function is associated with markers of endothelial dysfunction and increased inflammatory activity". Nephrol Dial Transplant 2003; 18: 892.
10. : "Inflammation and atherosclerosis in end-stage renal disease". Blood Purif 2003; 21: 29.
11. : "Decreased cardiac output, venous congestion and the association with renal impairment in patients with cardiac dysfunction". Eur J Heart Fail 2007; 9: 872.
12. : "Factors influencing the one-year mortality of dilated cardiomyopathy". Am J Cardiol 1984; 54: 147.
13. : "Prognostic importance of elevated jugular venous pressure and a third heart sound in patients with heart failure". N Engl J Med 2001; 345: 574.
14. : "The prognostic use of right heart catheterization data in patients with advanced heart failure: how relevant are invasive procedures in the risk stratification of advanced heart failure in the era of neurohormones?". J Heart Lung Transplant 2005; 24: 303.
15. : "Assessing risk by hemodynamic profile in patients awaiting cardiac transplantation". Am J Cardiol 1994; 73: 379.
16. : "Drawbacks and prognostic value of formulas estimating renal function in patients with chronic heart failure and systolic dysfunction". Circulation 2006; 114: 1572.
17. : "Prevalence of chronic kidney disease in the United States". JAMA 2007; 298: 2038.
18. : "Regression modelling strategies for improved prognostic prediction". Stat Med 1984; 3: 143.
19. : "Effect of increased renal venous pressure on renal function". J Trauma 1999; 47: 1000.
20. : "Effects of renal lymphatic occlusion and venous constriction on renal function". Am J Pathol 1975; 78: 285.
21. : "Effects of renal and hepatic venous congestion on renal function in the presence of low and normal cardiac output in dogs". Circ Res 1980; 47: 883.
22. : "Renal venous pressure in chronic congestive heart failure". J Clin Invest 1950; 29: 342.
23. : "Effect of increased renal venous pressure on renal function". Am J Physiol 1949; 157: 1.
24. : "Relationship between kidney function, hemodynamic variables and circulating big endothelin levels in patients with severe refractory heart failure". Wien Klin Wochenschr 1998; 110: 89.
25. : "Acute kidney injury prediction following elective cardiac surgery: AKICS score". Kidney Int 2007; 72: 624.
26. : "Chronic kidney disease in patients with chronic heart failure—impact on intracardiac conduction, diastolic function and prognosis". Int J Cardiol 2007; 118: 375.
27. : "Left ventricular diastolic dysfunction in patients with chronic renal failure: impact of diabetes mellitus". Diabetes Med 2005; 22: 730.
28. : "Association between left ventricular diastolic dysfunction and renal hemodynamic change in patients with treated essential hypertension". Hypertens Res 2003; 26: 971.
29. : "Chronic kidney disease associated mortality in diastolic versus systolic heart failure: a propensity matched study". Am J Cardiol 2007; 99: 393.
30. : "Transmitral flow patterns and the presence of chronic kidney disease provide independent and incremental prognostic information in patients with heart failure and systolic dysfunction". J Am Soc Echocardiogr 2007; 20: 989.
31. : "Central venous pressure: physiological significance and clinical implications". Am Heart J 1973; 86: 431.
32. : "The clinical role of central venous pressure measurements". J Intensive Care Med 2007; 22: 44.
33. : "Role of diminished renal function in cardiovascular mortality: marker or pathogenetic factor?". J Am Coll Cardiol 2006; 47: 1.
34. : "Levosimendan improves renal function in patients with acute decompensated heart failure: comparison with dobutamine". Cardiovasc Drugs Ther 2007; 21: 431.
35. : "Levosimendan improves renal function in acute decompensated heart failure: cause and clinical application". Cardiovasc Drugs Ther 2007; 21: 403.
36. : "Third heart sound and elevated jugular venous pressure as markers of the subsequent development of heart failure in patients with asymptomatic left ventricular dysfunction". Am J Med 2003; 114: 431.
37. : "Long-term survival, modes of death, and predictors of mortality in patients with Fontan surgery". Circulation 2008; 117: 13.
38. : "High central venous pressure is associated with prolonged mechanical ventilation and increased mortality after lung transplantation". J Thorac Cardiovasc Surg 2005; 129: 912.
Abbreviations and Acronyms
| CI | confidence interval |
| CVP | central venous pressure |
| eGFR | estimated glomerular filtration rate |
| HR | hazard ratio |
Footnotes
Dr. Damman is supported by the Netherlands Heart Foundation (grant 2006B157). Dr. Voors and Dr. van Veldhuisen are Clinical Established Investigators of the Netherlands Heart Foundation (grants 2006T37 and D97-017, respectively).
Editorials published in the Journal of the American College of Cardiology reflect the views of the authors and do not necessarily represent the views of JACC or the American College of Cardiology.