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European Heart Journal Advance Access published online on September 2, 2008
European Heart Journal, doi:10.1093/eurheartj/ehn388
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Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2008. For permissions please email: journals.permissions@oxfordjournals.org

Relation of N-terminal pro-brain natriuretic peptide levels and their prognostic power in chronic stable heart failure to obesity status

Lutz Frankenstein1,*, Andrew Remppis1, Manfred Nelles1, Bernd Schaelling1, Dieter Schellberg2, Hugo Katus1 and Christian Zugck1

1 Department of Cardiology, Angiology and Pulmonology, University of Heidelberg, INF 410, Heidelberg 69120, Germany
2 Department of Psychosomatic and General Internal Medicine, University of Heidelberg, INF 410, Heidelberg 69120, Germany

Received 13 April 2008; revised 14 July 2008; accepted 13 August 2008.

* Corresponding author. Tel: +49 6221 56 3 8895, Fax: +49 6221 56 6547, Email: lutz.frankenstein{at}med.uni-heidelberg.de


   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 Conclusion
 Funding
 References
 
Aims: To investigate the relationship between body mass index (BMI) and N-terminal pro-brain natriuretic peptide (NTproBNP) level and resultant prognostic capacity in chronic heart failure (CHF) controlled for known confounders.

Methods and results: We formed 206 triplets of patients (n = 618) with stable systolic CHF matched with respect to age, sex, renal function (MDRD, modification of diet in renal disease formula), and NYHA class, each with a BMI >30 kg/m2 (group 3), 20–24.9 kg/m2 (group 1), and 25–29.9 kg/m2 (group 2). BMI conveys a 4% drop in NTproBNP per unit increase. This influence remained significant after correction for age, sex, MDRD, NYHA, heart rate, rhythm, and ejection fraction. NTproBNP remained an independent predictor of adverse outcome after correction for age, sex, BMI, NYHA, MDRD, and ejection fraction. Despite numerical differences, prognostic power was comparable between BMI groups (log-transformed NTproBNP; group 1: hazard ratio (HR) 1.435, 95% CI 1.046–1.967, {chi}2 5.02, P = 0.03; group 2: HR 1.604, 95% CI 1.203–2.138, {chi}2 10.36, P = 0.001; group 3: HR 1.735, 95% CI 1.302–2.313, {chi}2 14.12, P = 0.0002) (P = NS, all). An NTproBNP correction factor was calculated.

Conclusion: Even matched for NYHA, age, sex, and renal function, BMI exerts a significant and independent inverse influence on NTproBNP in patients with stable CHF. NTproBNP retained equal statistical power in all three BMI groups.

Key Words: Chronic heart failure • NTproBNP • Obesity • Body mass index • Prognosis


   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 Conclusion
 Funding
 References
 
Over the past, both chronic heart failure (CHF) and obesity exhibited an almost epidemic increase1,2 and will probably continue to do so. Furthermore, there is increasing data on a higher prevalence of heart failure in obese patients.3 As natriuretic peptides are elevated in heart failure,4 they are commonly used to screen for heart failure,5 stratify the risk,6 and guide medical therapy in such patients.7,8

An inverse relationship of blood levels of natriuretic peptides with body mass index (BMI) has been described9,10 in healthy individuals, but this notion has already been questioned by recent data.11 Not only could these peptides be more related to lean mass rather than fat mass,10 but there appears to be a difference between brain natriuretic peptide (BNP) and the aminoterminal cleavage product (NTproBNP, N-terminal pro-brain natriuretic peptide)12 as to the influence of BMI on the respective hormone.

With respect to heart failure, only few studies focused on this problem. As for BNP, an inverse relation with BMI has recently been described in both the acute13,14 and chronic15,16 setting. But again, this has already been contradicted.17 And although reports on NTproBNP in acute heart failure confirmed the inverse relation to BMI,13,14,18 only few studies have19,20 addressed this issue in CHF.

Given the growing importance of both CHF and adiposity as well as the widespread use of NTproBNP, it is crucial to understand the possible confounding influence of BMI on the validity of NTproBNP to allow correct and adequate application of this valuable tool in CHF. Furthermore, some of the above controversies might in part be due to heterogeneous cohorts examined. We therefore adopted a matched approach for the major influencing factors (NYHA, age, sex, and renal function) in patients with stable CHF from a university hospital outpatient’s department.


   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 Conclusion
 Funding
 References
 
Study population
The registry of the specialized heart failure clinic of the University Hospital Heidelberg, Germany, formed the basis for this study. All patients attending the clinic for the evaluation of heart failure were asked to participate in the registry and provide written informed consent for data storage and evaluation. The decline rate was <1% of patients asked. The proceedings were approved by the local Ethics Committee and conformed to the principles outlined in the Declaration of Helsinki. The diagnosis of heart failure was based on the ESC criteria of symptoms compatible with the diagnosis in the presence of objective abnormalities of cardiac function21 on echocardiography or left heart catheter.

For inclusion into the present study, all patients with stable chronic systolic dysfunction and the assessment of NTproBNP during initial presentation were selected. The aetiology of heart failure was either ischaemic or idiopathic dilated cardiomyopathy and patients were on stable medication for at least 1 month prior to inclusion. Patients with a history of primary pulmonary disease, valvular heart disease, and decompensation of heart failure requiring inotropic support within the last 3 months prior to study inclusion were not included. If multiple visits were present, only the first visit was chosen (n = 1743). These patients were separated according to BMI into three groups [group 1 (BMI 20–24.9 kg/m2; n = 522); group 2 (BMI 25–29.9 kg/m2; n = 774); group 3 (BMI >30 kg/m2; n = 447)] and matched according to the following strategies.

Measurements of N-terminal pro-brain natriuretic peptide
Blood samples were taken from a peripheral venous catheter using EDTA vacutainers, immediately centrifuged for 10 min at 4000 r.p.m. at 4°C, subdivided and frozen at –30°C. Testing was performed for plasma NTproBNP levels (Elecsys®, Roche Diagnostics, Mannheim, Germany). NTproBNP results are presented in pg/mL. To convert to pmol/L, results need to be multiplied by 0.118.

Matching
Each patient of group 3 was individually matched using calliper matching according to renal function (as estimated through the simplified modification of diet in renal disease (MDRD) formula,22 age, sex, and NYHA functional class to two individual patients, one from group 1 and one from group 2. For age and MDRD, calliper was defined as 0.25 x standard deviation of the respective variable. For each patient, the matching routine first identified sex and NYHA class matches. From this cohort, all patients within age-calliper were selected, and from this cohort the first patient within MDRD-calliper.

In a first step, individual pairs from groups 3 and 1 were obtained. Then, to each patient of group 3, an individual, matched patient was identified from group 2. This patient was retained as a match only if the patient represented a match to the corresponding patient of group 1 within this triplet of patients. If not, the next available matched patient from group 2 was tested. After the first matching step, 232 pairs of patients from groups 3 and 1 were retained. After the second step, 206 nested triplets were retained for final analysis.

Follow-up and endpoint
The determination of survival status and follow-up were performed—in hierarchical order—by scheduled visits to the outpatient clinic, telephone calls either to the patient’s home or to their physician, or hospital electronic records. The predefined endpoint for the purpose of this analysis was all-cause mortality. Patients receiving cardiac transplantation during follow-up were followed until their surgical procedure and censored thereafter. All survivors were followed up for a minimum of 1 year. No patient underwent implantation of left ventricular assist devices during follow-up.

Statistics
To compare frequencies, {chi}2 analysis was performed. To test for significant differences between means, two-sample Wilcoxon test, Kruskal–Wallis test and one-way analysis of variance were used where appropriate. All tests are two-tailed and a P-value <5% was regarded statistically significant. For multiple pairwise testing, this P-value was adjusted to <1.7% according to the Bonferoni correction for the testing of the three groups. The data are presented as mean ± SD, except where specified otherwise. Univariable and multivariable linear regressions were performed using transformed NTproBNP values23 as dependent variables. All baseline variables were entered into the univariable analysis. Covariates that were strongly associated with NTproBNP levels (P < 0.10) were included in the multivariable analysis. Baseline model assumptions were proportionality of hazard, linearity, and non-influential observations. Assumptions of proportional hazards were assessed by visual judgement of the logarithm of minus logarithm of the survival estimates, obtained from stratified Cox regression. To check the proportional hazards assumption, the score process (which is a transformed partial sum process of the Martingale residuals) is compared with the simulated processes under the null hypothesis that the proportional hazards assumption holds.24 Proportionality was not rejected for any variable included in the final model other than NTproBNP. Therefore, trans-NTproBNP values23 were used. Martingale residuals from the full Cox model were plotted against covariates of interest. No violation of linearity was detected. In addition, cumulative Martingale residuals were compared with simulated residual patterns under the null hypothesis that linearity holds.24 Influential observations were assessed by plotting the deviance residual against the linear predictor.25 To test for differences between Cox regression coefficients of NTproBNP and trans-NTproBNP of the BMI strata, z-test was performed as described previously.26 Finally, we directly obtained a correction factor for NTproBNP of obese patients by using the ratio of β-coefficients from separately stratified Cox analysis.


   Results
Top
 Abstract
 Introduction
 Methods
 Results
Discussion
 Conclusion
 Funding
 References
 
Surviving patients were followed for a median of 37 (21–58) months, with no significant differences between the BMI groups [35 (21–49) vs. 38 (21–61) vs. 37 (23–66) months for groups I, II, III, with P = 0.27, P = 0.63, and P = 0.12 for group I vs. II, II vs. III, and III vs. I, respectively].

Between groups, differences were seen for left ventricular ejection fraction, prevalence of diabetes, mean blood pressure, the distance walked during 6 min walk test, and the use of β-blockers (Table 1). With respect to the aetiology of heart failure, patients with ischaemic heart disease were older (66.5 ± 10.5 vs. 58.1±10.0; P < 0.001), had slightly higher ejection fraction (28.4 ± 5.0 vs. 27.6 ± 4.4; P < 0.05), and BMI (32 ± 9 vs. 29 ± 12; P < 0.01) with no difference as to NYHA class distribution (P = 0.65) and sex (P = 0.13).


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  		Table 1 Baseline clinical characteristics according to body mass index group

 
Body mass index and N-terminal pro-brain natriuretic peptide
Plasma levels of NTproBNP differed significantly between the matched BMI groups (Table 1 and Figure 1). NTproBNP was moderately inversely correlated with BMI both as uncorrected (r= –0.22; 95% CI –0.30 to –0.15; P < 0.001) and as log-transformed value (r = –0.29; 95% CI –0.36 to –0.22; P < 0.001), with BMI considered as a continuous variable (Figure 2). The same results were obtained for uncorrected and log-transformed NTproBNP values, with BMI considered as a categorical variable (r = –0.30; 95% CI –0.37 to –0.23; P < 0.001 and r = –0.30; 95% CI –0.37 to –0.23; P < 0.001).


Figure 1
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  		Figure 1 Box-plot of levels of N-terminal pro-brain natriuretic peptide (NTproBNP) according to body mass index (BMI) as a categorical measure. The horizontal line in the middle of each box indicates the median; the top and bottom borders of the box mark the 75th and 25th percentiles, respectively, and the whiskers mark the 90th and 10th percentiles. *P < 0.001.

 

Figure 2
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  		Figure 2 Correlation analysis of log10(NTproBNP) vs. body mass index (BMI) as a continuous measure. Circles represent individual values of N-terminal pro-brain natriuretic peptide. The black line represents the linear regression curve fit and the dotted line its 95% confidence interval. A moderate inverse correlation (r = –0.29, 95% CI –0.36 to –0.22, P < 0.001) was found between log10(NTproBNP) and body mass index.

 
Determinants of N-terminal pro-brain natriuretic peptide
When considered as a continuous variable, BMI was a significant univariable predictor of NTproBNP levels, with a 4% decrease in NTproBNP per unit increase of BMI. When considered as a categorical variable, BMI category, too, was a significant univariable predictor of NTproBNP levels, with a 52.2 and 38.2% decrease in NTproBNP for BMI groups 2 and 3, respectively. Further significant predictors of NTproBNP levels were age (P < 0.001), renal function (P < 0.001), left ventricular ejection fraction (P < 0.001), NYHA functional class (P < 0.001), rhythm (P < 0.001), heart rate (P < 0.001), mean blood pressure (P < 0.001), 6 min walk test distance (P < 0.01), and the aetiology of heart failure (P < 0.05). Diabetic status (P = 0.29) or sex (P = 0.14) were not significant predictors of NTproBNP levels in this analysis.

When entered into a common multivariable regression analysis with the above significant variables, BMI—both as a continuous and a categorical variable—remained an independent predictor of NTproBNP levels (Tables 2 and 3).


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  		Table 2 Multivariable linear regression for N-terminal pro-brain natriuretic peptide as dependent variable using body mass index as a categorical variable

 

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  		Table 3 Multivariable linear regression for trans-N-terminal pro-brain natriuretic peptide as dependent variable using body mass index as a continuous variable

 
Prognostic significance of N-terminal pro-brain natriuretic peptide and body mass index
Although BMI as a continuous variable was not a significant univariable predictor of adverse outcome, it was, however, significant when considered as a categorical variable. In contrast, NTproBNP was a strong univariable predictor of adverse outcome (Table 4). When comparing the prognostic power of NTproBNP between BMI groups (trans-NTproBNP; group 1: HR 1.435, 95% CI 1.046–1.967, {chi}2 5.02, P = 0.03; group 2: HR 1.604, 95% CI 1.203–2.138, {chi}2 10.36, P = 0.001; group 3: HR 1.735, 95% CI 1.302–2.313, {chi}2 14.12, P = 0.0002), no significant difference was noted (P = 0.30 group 1 vs. 2; P = 0.19 group 1 vs. 3; P = 0.35 group 2 vs. 3). NTproBNP remained and independent predictor (HR 1.000, 95% CI 1.000–1.000, {chi}2 5.24, P < 0.05) after correcting for age, sex, BMI (as a continuous variable), NYHA class, MDRD, and LVEF in a common multivariable Cox model. The correction factor for NTproBNP levels of obese patients from the ratio of β-coefficients was 1.11.


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  		Table 4 Univariable Cox proportional hazard models

 

   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
Conclusion
 Funding
 References
 
This study addresses the question as to what extent plasma levels of NTproBNP are influenced by BMI in patients with stable chronic systolic heart failure in the setting of a university hospital outpatient’s department with patients matched for known influencing factors (NYHA, age, sex, and renal function). The following are its main findings.
  1. Both as an uncorrected and as a log-transformed parameter, significant inverse correlations were found between NTproBNP and increasing BMI.
  2. Even when matched for NYHA, age, sex, and renal function, BMI conveys a 4% drop in NTproBNP per unit increase of BMI.
  3. The influence of BMI on NTproBNP levels retained statistical significance when adjusted for other known factors influencing NTproBNP levels.
  4. NTproBNP retained its statistical power in all three BMI groups examined, with no significant differences across BMI groups.
Even though both CHF and obesity are common problems of increasing importance, only few studies have addressed the interaction of BMI and NTproBNP. The inverse relationship between BMI and natriuretic peptides in general and NTproBNP in specific can be demonstrated even in the absence of heart failure.9,10 It therefore does not appear plausible to simply assume that clinical disease severity of obese patients with CHF is overestimated, as exercise intolerance will be more pronounced in obese patients, and that for that reason lower levels of NTproBNP are found in these patients. Alternatively, modulation of clearance receptor density27 or composition,28 impaired hormone synthesis29 or release30 have been proposed. As some of these mechanisms have already been contradicted,10 the exact pathway of influence of obesity on NTproBNP remains yet to be clarified. More recently, O-glycosylation of NTproBNP has been shown.31 As this may compromise the detection of the NTproBNP essay32 and as prevalence of diabetes increased with BMI, the above inverse relation might reflect false-negative test results rather than true lowering of NTproBNP with obesity. Even though we did not find a significant influence of diabetes on NTproBNP, this still appears conceivable, as besides glycosylation, alternate circulating forms of NTproBNP have been found.33

We chose NTproBNP for this study not only as it is more stable than BNP, but also as at least parts of the proposed mechanisms for a possible natriuretic peptide handicap9 in BNP do not apply to NTproBNP. So far, only two studies19,20 have addressed the possible interaction of NTproBNP and BMI in chronic stable heart failure. The present analysis significantly supplements their results. Not only did we include about twice the number of patients as the aforementioned studies combined, but also we do consider matching superior to controlling during statistical analysis. Furthermore, already at inclusion, obese patients differed from non-obese patients with regard to age and sex distribution in one of these studies.19

In order to eliminate the possibly confounding influence of cardiac cachexia, patients with a BMI <20 kg/m2 were not included in the present study. Also, we formed three distinct groups of patients—normal weight, overweight, and obese—to account for a possible categorical (class) effect of BMI. We consider it as a strong point of the present analysis that matching was performed with respect to all known anthropometric influences on NTproBNP (age, sex, and renal function) and in addition to NYHA to account for subjective disease severity. As we were still able to reproduce the above-described independent influence of BMI on NTproBNP levels in this matched setting, the present study strongly supports the notion of an intrinsic influence of adipose tissue on NTproBNP levels rather than confounding co-morbid conditions.

The influence of BMI on survival is still controversial. Though BMI is a risk factor towards the evolution of heart failure,34 in CHF a paradoxical survival benefit has been described,35 which apparently was replicated in our study. A recent sub-analysis of the CHARM programme showed a U-shaped mortality curve for BMI,36 and others found the influence of BMI on mortality to be complex and dependent on co-variates.37 As for previous studies,35 there were differences in baseline clinical variables in our study, too, possibly explaining certain aspects of this survival benefit.

As far as the validity of natriuretic peptides as a prognostic marker is concerned, only a few studies have focused on this issue.16,18 Since Bayes-Genis et al.18 addressed this question for NTproBNP in the setting of acute heart failure and Horwich et al.16 for BNP in the setting of CHF, this study significantly extends their findings. Our results do not support the notion brought about by Horwich et al.16 that the prognostic value of NTproBNP appears to change with respect to BMI group. It must, however, be emphasized that this study was primarily designed to investigate a possible independent influence of BMI on NTproBNP levels, and less, in order to compare the individual prognostic performance within each BMI class or across the BMI continuum. To do so, an alternative matching strategy would have to include NTproBNP itself to account for its intrinsic prognostic information. This, however, would render the analysis of influence of BMI on NTproBNP levels—the goal of the present study—impossible. Consequently, we urge caution as to any correction factor. The variables of our matching strategy explained ~47% of total variance of NTproBNP, and the BNP promoter is responsive not only to wall stretch but also to neuroendocrine activation, as well as to growth signals and pro-inflammatory signal transduction.38 Therefore, this would need to be taken into account for such a factor—which unfortunately goes beyond our study.

Limitations
Our patients reflect the average population at a tertiary reference centre which accounts for the low proportion of women and ischaemic cardiomyopathy in this study. Therefore, our results might not be fully transferable to all patients. Though only 10% of the cohort, a total of 60 women were included. We would therefore be inclined to assume that even though generalizability is limited, this number is important enough to allow a sample-specific statement. Furthermore, we cannot completely exclude a certain pre-selection bias. Recruitment depends on referring physicians deeming their patients appropriate for attendance at our university hospital clinic. Also, the number of patients included might still represent a handicap. This might have precluded more detailed analyses, e.g. separate for sex or age groups.


   Conclusion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
Funding
 References
 
Even when matched for NYHA, age, sex, and renal function, BMI exerts a significant and independent inverse influence on NTproBNP in patients with chronic stable CHF. NTproBNP retained equal statistical power in all three BMI groups.


   Funding
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Funding
References
 
This study was supported by a grant from the Carl-Baresel-Foundation, Stuttgart, Germany.

Conflict of interest: none declared.


   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 Conclusion
 Funding
 References
 

  1. Lloyd-Jones DM, Larson MG, Leip EP, Beiser A, D’Agostino RB, Kannel WB, Murabito JM, Vasan RS, Benjamin EJ, Levy D, Framingham Heart Study. Lifetime risk for developing congestive heart failure—The Framingham Heart Study. Circulation (2002) 106:3068–3072.[Abstract/Free Full Text]
  2. Ogden CL, Flegal KM, Carroll MD, Johnson CL. Prevalence and trends in overweight among US children and adolescents, 1999–2000. JAMA (2002) 288:1728–1732.[Abstract/Free Full Text]
  3. Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, Kannel WB, Vasan RS. Obesity and the risk of heart failure. N Engl J Med (2002) 347:305–313.[Abstract/Free Full Text]
  4. Bettencourt P. NT-proBNP and BNP: biomarkers for heart failure management. Eur J Heart Fail (2004) 6:359–363.[Abstract/Free Full Text]
  5. Doust JA, Glasziou PP, Pietrzak E, Dobson AJ. A systematic review of the diagnostic accuracy of natriuretic peptides for heart failure. Arch Intern Med (2004) 164:1978–1984.[Abstract/Free Full Text]
  6. Doust JA, Pietrzak E, Dobson A, Glasziou P. How well does B-type natriuretic peptide predict death and cardiac events in patients with heart failure: systematic review. BMJ (2005) 330:625.[Abstract/Free Full Text]
  7. Troughton RW, Frampton CM, Yandle TG, Espiner EA, Nicholls MG, Richards AM. Treatment of heart failure guided by plasma aminoterminal brain natriuretic peptide (N-BNP) concentrations. Lancet (2000) 355:1126–1130.[CrossRef][Web of Science][Medline]
  8. Jourdain P, Jondeau G, Funck F, Gueffet P, Le Helloco A, Donal E, Aupetit JF, Aumont MC, Galinier M, Eicher JC, Cohen-Solal A, Juillière Y. Plasma brain natriuretic peptide-guided therapy to improve outcome in heart failure: the STARS-BNP Multicenter Study. J Am Coll Cardiol (2007) 49:1733–1739.[Abstract/Free Full Text]
  9. Wang TJ, Larson MG, Levy D, Benjamin EJ, Leip EP, Wilson PW, Vasan RS. Impact of obesity on plasma natriuretic peptide levels. Circulation (2004) 109:594–600.[Abstract/Free Full Text]
  10. Das SR, Drazner MH, Dries DL, Vega GL, Stanek HG, Abdullah SM, Canham RM, Chung AK, Leonard D, Wians FH Jr, de Lemos JA. Impact of body mass and body composition on circulating levels of natriuretic peptides: results from the Dallas Heart Study. Circulation (2005) 112:2163–2168.[Abstract/Free Full Text]
  11. Grandi AM, Laurita E, Selva E, Piantanida E, Imperiale D, Giovanella L, Guasti L, Venco A. Natriuretic peptides as markers of preclinical cardiac disease in obesity. Eur J Clin Invest (2004) 34:342–348.[CrossRef][Web of Science][Medline]
  12. Fernandes F, Ramires FJ, Buck PC, Almeida IJ, Rabelo R, Dantas SA, Salemi VM, Halpern A, Mady C. N-terminal-pro-brain natriuretic peptide, but not brain natriuretic peptide, is increased in patients with severe obesity. Braz J Med Biol Res (2007) 40:153–158.[Web of Science][Medline]
  13. Krauser DG, Lloyd-Jones DM, Chae CU, Cameron R, Anwaruddin S, Baggish AL, Chen A, Tung R, Januzzi JL Jr. Effect of body mass index on natriuretic peptide levels in patients with acute congestive heart failure: a ProBNP Investigation of Dyspnea in the Emergency Department (PRIDE) substudy. Am Heart J (2005) 149:744–750.[CrossRef][Web of Science][Medline]
  14. Daniels LB, Clopton P, Bhalla V, Krishnaswamy P, Nowak RM, McCord J, Hollander JE, Duc P, Omland T, Storrow AB, Abraham WT, Wu AH, Steg PG, Westheim A, Knudsen CW, Perez A, Kazanegra R, Herrmann HC, McCullough PA, Maisel AS. How obesity affects the cut-points for B-type natriuretic peptide in the diagnosis of acute heart failure. Results from the Breathing Not Properly Multinational Study. Am Heart J (2006) 151:999–1005.[CrossRef][Web of Science][Medline]
  15. Mehra MR, Uber PA, Park MH, Scott RL, Ventura HO, Harris BC, Frohlich ED. Obesity and suppressed B-type natriuretic peptide levels in heart failure. J Am Coll Cardiol (2004) 43:1590–1595.[Abstract/Free Full Text]
  16. Horwich TB, Hamilton MA, Fonarow GC. B-type natriuretic peptide levels in obese patients with advanced heart failure. J Am Coll Cardiol (2006) 47:85–90.[Abstract/Free Full Text]
  17. McCord J, Mundy BJ, Hudson MP, Maisel AS, Hollander JE, Abraham WT, Steg PG, Omland T, Knudsen CW, Sandberg KR, McCullough PA, Breathing Not Properly Multinational Study Investigators. Relationship between obesity and B-type natriuretic peptide levels. Arch Intern Med (2004) 164:2247–2252.[Abstract/Free Full Text]
  18. Bayes-Genis A, Lloyd-Jones DM, van Kimmenade RR, Lainchbury JG, Richards AM, Ordoñez-Llanos J, Santaló M, Pinto YM, Januzzi JL Jr. Effect of body mass index on diagnostic and prognostic usefulness of amino-terminal pro-brain natriuretic peptide in patients with acute dyspnea. Arch Intern Med (2007) 167:400–407.[Abstract/Free Full Text]
  19. Taylor JA, Christenson RH, Rao K, Jorge M, Gottlieb SS. B-type natriuretic peptide and N-terminal pro B-type natriuretic peptide are depressed in obesity despite higher left ventricular end diastolic pressures. Am Heart J (2006) 152:1071–1076.[CrossRef][Web of Science][Medline]
  20. Rivera M, Cortés R, Salvador A, Bertomeu V, de Burgos FG, Payá R, Portolés M, Taléns-Visconti R, Martinez-Dolz L, Valero R, Sevilla B, Climent V. Obese subjects with heart failure have lower N-terminal pro-brain natriuretic peptide plasma levels irrespective of aetiology. Eur J Heart Fail (2005) 7:1168–1170.[Abstract/Free Full Text]
  21. Remme WJ, Swedberg K. Comprehensive guidelines for the diagnosis and treatment of chronic heart failure task force for the diagnosis and treatment of chronic heart failure of the European Society of Cardiology. Eur J Heart Fail (2002) 4:11–22.[CrossRef][Web of Science][Medline]
  22. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine A new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med (1999) 130:461–470.[Abstract/Free Full Text]
  23. Hess G, Moecks J, Zdunek D. N-Terminal-proBNP (NT-proBNP) as an indicator of cardiac dysfunction. A study in patients presenting with suspected cardiac disorders. Z Kardiol (2005) 94:247–254.[CrossRef][Web of Science][Medline]
  24. Lin D, Wei L, Ying Z. Checking the Cox model with cumulative sums of Martingale-based residuals. Biometrika (1993) 80:557–572.[Abstract/Free Full Text]
  25. Therneau TM, Grambsch PM, Fleming TR. Martingale-based residuals for survival models. Biometrika (1990) 77:147–160.[Abstract/Free Full Text]
  26. D’Agostino RB Sr, Grundy S, Sullivan LM, Wilson P, CHD Risk Prediction Group. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA (2001) 286:180–187.[Abstract/Free Full Text]
  27. Sarzani R, Dessi-Fulgheri P, Paci VM, Espinosa E, Rappelli A. Expression of natriuretic peptide receptors in human adipose and other tissues. J Endocrinol Invest (1996) 19:581–585.[Web of Science][Medline]
  28. Sengenes C, Berlan M, De Glisezinski I, Lafontan M, Galitzky J. Natriuretic peptides: a new lipolytic pathway in human adipocytes. FASEB J (2000) 14:1345–1351.[Abstract/Free Full Text]
  29. Morabito D, Vallotton MB, Lang U. Obesity is associated with impaired ventricular protein kinase C-MAP kinase signaling and altered ANP mRNA expression in the heart of adult Zucker rats. J Investig Med (2001) 49:310–318.[Web of Science][Medline]
  30. Licata G, Volpe M, Scaglione R, Rubattu S. Salt-regulating hormones in young normotensive obese subjects. Effects of saline load. Hypertension (1994) 23:I20–I24.[Web of Science][Medline]
  31. Hammerer-Lercher A, Halfinger B, Sarg B, Mair J, Puschendorf B, Griesmacher A, Guzman NA, Lindner HH. Analysis of circulating forms of proBNP and NT-proBNP in patients with severe heart failure. Clin Chem (2008) 54:858–865.[Abstract/Free Full Text]
  32. Seferian KR, Tamm NN, Semenov AG, Tolstaya AA, Koshkina EV, Krasnoselsky MI, Postnikov AB, Serebryanaya DV, Apple FS, Murakami MM, Katrukha AG. Immunodetection of glycosylated NT-proBNP circulating in human blood. Clin Chem (2008) 54:866–873.[Abstract/Free Full Text]
  33. Lam CS, Burnett JC Jr, Costello-Boerrigter L, Rodeheffer RJ, Redfield MM. Alternate circulating pro-B-type natriuretic peptide and B-type natriuretic peptide forms in the general population. J Am Coll Cardiol (2007) 49:1193–1202.[Abstract/Free Full Text]
  34. Kenchaiah S, Evans JC, Levy D, Wilson PW, Benjamin EJ, Larson MG, Kannel WB, Vasan RS. Obesity and the risk of heart failure. N Engl J Med (2002) 347:305–313.[Abstract/Free Full Text]
  35. Habbu A, Lakkis NM, Dokainish H. The obesity paradox: fact or fiction? Am J Cardiol (2006) 98:944–948.[CrossRef][Web of Science][Medline]
  36. Kenchaiah S, Pocock SJ, Wang D, Finn PV, Zornoff LA, Skali H, Pfeffer MA, Yusuf S, Swedberg K, Michelson EL, Granger CB, McMurray JJ, Solomon SD, CHARM Investigators. Body mass index and prognosis in patients with chronic heart failure: insights from the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) program. Circulation (2007) 116:627–636.[Abstract/Free Full Text]
  37. Gustafsson F, Kragelund CB, Torp-Pedersen C, Seibaek M, Burchardt H, Akkan D, Thune JJ, Køber L, DIAMOND study group. Effect of obesity and being overweight on long-term mortality in congestive heart failure: influence of left ventricular systolic function. Eur Heart J (2005) 26:58–64.[Abstract/Free Full Text]
  38. LaPointe MC. Molecular regulation of the brain natriuretic peptide gene. Peptides (2005) 26:944–956.[CrossRef][Web of Science][Medline]

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 Eur J Heart FailHome page
L. Frankenstein, C. Zugck, M. Nelles, D. Schellberg, H. A. Katus, and B. A. Remppis
The obesity paradox in stable chronic heart failure does not persist after matching for indicators of disease severity and confounders
Eur J Heart Fail, December 1, 2009; 11(12): 1189 - 1194.
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