The interaction between N-terminal pro-brain natriuretic peptide and fluid status in adverse clinical outcomes of late stages of chronic kidney disease

Abstract

Introduction

Fluid overload is one of the major characteristics and complications in patients with chronic kidney disease (CKD). N-terminal pro-brain natriuretic peptide (NT-proBNP) is related to fluid status and fluid distribution. The aim of this study is to investigate the interaction between NT-proBNP and fluid status in adverse clinical outcomes of late stages of CKD.

Methods

We enrolled 239 patients with CKD stages 4–5 from January 2011 to December 2011 and followed up until June 2017. Fluid status was presented as hydration status (HS) value measured by body composition monitor, while HS>7% was defined as fluid overload. Clinical outcomes included renal outcomes (commencing dialysis and estimated glomerular filtration rate decline>3 ml/min/1.73 m2/year), all-cause mortality and major adverse cardiovascular events (MACEs).

Results

During a mean follow-up of 3.3±2.0 years, 129(54.7%) patients commenced dialysis, 88(37.3%) patients presented rapid renal function decline, and 48(20.3%) had MACEs or died. All patients were stratified by HS of 7% and the median of plasma NT-proBNP. The adjusted risks for commencing dialysis was significantly higher in patients with high plasma NT-proBNP and HS>7% compared to those with low plasma NT-proBNP and HS≦7%. There was a significant interaction between plasma NT-proBNP and HS in commencing dialysis (P-interaction = 0.047). Besides, patients with high plasma NT-proBNP and HS>7% had greater risks for MACEs or all-cause mortality than others with either high plasma NT-proBNP or HS>7%.

Conclusion

NT-proBNP and fluid overload might have a synergistic association of adverse clinical outcomes in patients with late stages of CKD.

About the Authors:

Yi-Chun Tsai

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

Affiliations Division of General Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

ORCID logo http://orcid.org/0000-0003-4923-3342

Hui-Ju Tsai

Roles Formal analysis, Software

Affiliation: Department of Family Medicine, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan

Chee-Siong Lee

Roles Methodology, Resources

Affiliations Division of General Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Division of Cardiology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan

Yi-Wen Chiu

Roles Resources

Affiliations Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

Hung-Tien Kuo

Roles Resources

Affiliations Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

Su-Chu Lee

Roles Investigation

Affiliation: Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan

Tzu-Hui Chen

Roles Data curation, Investigation

Affiliation: Department of Nursing, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan

Mei-Chuan Kuo

Roles Conceptualization, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

Affiliations Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan, Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan

Introduction

Brain natriuretic peptide (BNP) is a cardiac neurohormone synthesized in the cardiac myocytes in response to increased left ventricular (LV) wall stress and stretch [1, 2]. Pre-proBNP is released from BNP and subsequently cleaved into proBNP, that is further cleaved to biologically active BNP and inactive N-terminal proBNP (NT-proBNP) [3, 4]. NT-proBNP has been considered as not only a biomarker of LV dysfunction [5] but also a predictor of major adverse cardiovascular events (MACEs) and all-cause mortality in dialysis patients as well [6, 7]. In chronic kidney disease (CKD) patients not on dialysis, accumulating evidence presents a significant association between plasma NT-proBNP level and all-cause mortality and MACEs [8–10]. Besides, elevated plasma NT-proBNP level indicates an increased risk for initial dialysis [11, 12]. NT-proBNP has been a potential biomarker of adverse clinical outcomes in CKD patients both on dialysis or not.

Fluid overload is one of the major characteristics and complications in CKD patients. Fluid overload is significantly associated with faster decline of renal function and increased risks for cardiovascular events or all-cause mortality [13, 14]. Plasma BNP is related to fluid status [15] and fluid distribution between the intracellular water (ICW) and extracellular water (ECW) [16]. The interaction between NT-proBNP and fluid status may be associated with adverse clinical outcomes. NT-proBNP and fluid status may have a synergistic effect on prognostic implications in CKD patients. Thus, the aim of this study is to assess whether the interaction between NT-proBNP and fluid status is associated with adverse clinical outcomes, including commencing dialysis, MACEs and all-cause mortality in patients with CKD stages 4–5 not on dialysis.

Materials and methods

Study participants

Two hundred and thirty-nine patients with CKD stages 4–5 were invited to participate in the study from January 2011 to December 2011 at one hospital in Southern Taiwan. CKD was staged according to Kidney Disease Outcomes Quality Initiative (K/DOQI) definition and the estimated glomerular filtration rate (eGFR) was calculated using the equation of the 4-variable Modification of Diet in Renal Disease (MDRD) Study (CKD stage 4, eGFR: 15–29 ml/min/1.73m2; CKD stage 5, eGFR<15 ml/min/1.73m2) [17]. The exclusion criteria of this study included patients with eGFR ≥30 ml/min/1.73m2 and patients having underline disease with malignancy. We also excluded three patients with less than three eGFR measurements during follow-up period because of minimal requirement of eGFR slope calculation. The study protocol was approved by the Institutional Review Board of the Kaohsiung Medical University Hospital (KMUH-IRB-990125). The methods were carried out in accordance with the relevant guidelines, including any relevant details, such as low risk for study design, private protection, and safe management. Informed consents were obtained in written form from patients and all clinical investigations were conducted according to the principles expressed in the Declaration of Helsinki.

Quantification of circulating NT-proBNP

Blood samples were collected at enrollment. All blood samples were aliquoted and stored in a -80°C freezer for the analysis of NT-proBNP after finishing recruitment. Plasma NT-proBNP was measured in duplicate using commercial enzyme-linked immunosorbent assays (Elecsys® Roche) based on the instructions of the manufacturer. The reportable range of NT-proBNP assay was 5–35000 pg/mL Intraassay and interassay coefficients of variation of NT-proBNP were 1.03% and 2.56% respectively.

Measurement of fluid status

Fluid status was measured once at enrollment by Body Composition Monitor (BCM, Fresenius Medical Care), a bioimpedance spectroscopy method as in our previous study [13, 14]. BCM provides the data of normohydrated lean tissue, normohydrated adipose tissue, and excess fluid mass in whole body based on the difference of impedance in each tissue through 3-component tissue-based model [18, 19]. Overhydration (OH) value, as an absolute fluid status, can be calculated from the difference between the normal expected and measured ECW [19]. The BCM can detect more precise body fluid compartment, and has been validated in the general population and CKD patients on dialysis [20–22]. The fluid status was also validated in CKD patients not on dialysis, and Hung et al. defined fluid overload as hydration status (HS, OH/ECW) value over 7% [20]. Therefore, we defined fluid overload as HS>7% in the present study.

Data collection

Participants were asked to fast for at least 12 hours before blood sample collection for the biochemistry study and protein in urine was measured by urine protein-creatinine ratio (PCR). Demographic and clinical data were obtained from medical records and interviews with patients at enrollment. Information regarding patient medications including diuretics, β-blockers, calcium channel blockers, angiotensin converting enzyme inhibitors (ACEI), angiotensin II receptor blockers (ARB), and statin within 3 months before enrollment was obtained from medical records. Patients were classified as diabetic by history and blood glucose values using the American Diabetes Association criteria, oral hypoglycemia agent use, or insulin use. Cardiovascular disease was defined as a history of acute or chronic ischemic heart disease, myocardial infarction, and heart failure. Cerebrovascular disease was defined as a history of cerebral infarction or hemorrhage.

Clinical outcomes

Participants were contacted at outpatient clinics at 3-month intervals to evaluate the clinical status. The renal outcomes consisted of commencing dialysis (hemodialysis or peritoneal dialysis) and rapid renal function decline. Commencing dialysis was confirmed by reviewing catastrophic illness certificate (issued by the Bureau of National Health Insurance in Taiwan) and medical charts. Rapid renal function decline was defined as the eGFR decline > 3 ml/min/1.73 m2 per year (eGFR slope). The eGFR slope was calculated by the regression coefficient between eGFR and time in units of ml/min per 1.73 m2 per year based on all eGFR values available from enrollment to the end of the observation period. At least three eGFR values were required to estimate the eGFR slope. Rapid eGFR decline was defined as the lowest quartile (the eGFR decline more than 3 ml/min/1.73m2 per year, an integer near the cutoff point between the lowest two quartiles of the eGFR slope) [13]. MACEs were defined as new onset of myocardial infarction, unstable angina, acute hemorrhagic or ischemic stroke, hospitalizations related to acute phase of congestive heart failure or arrhythmia. The information of death obtained by direct contact with patients and families was further supplemented by reviewing medical records and screening the data bank of the National Mortality File. We excluded MACEs or death after commencing dialysis. Patients were censored at last contact or the end of observation in June 2017.

Statistical analysis

The study population was further classified into four groups according to HS value of 7% and the median of circulating NT-proBNP. Continuous variables were expressed as mean±SD or median (25th, 75th percentile), as appropriate, and categorical variables were expressed as percentages. Skewed distribution continuous variables were log-transformed to attain normal distribution. The significance of differences in continuous variables between groups was tested using the one-way analysis of variance (ANOVA) followed by the post hoc test adjusted with a Bonferroni correction or the Kruskal-Wallis H test, as appropriate. The difference in the distribution of categorical variables was tested using the Chi-square test. The association between fluid status and NT-proBNP was examined by linear regression. Time-to-event survival analysis by Kaplan-Meier survival curve was used to test fluid status or circulating NT-proBNP level as a predictor of the risk of commencing dialysis and composite outcomes either MACEs or all-cause mortality. Cox regression models were utilized to evaluate the interaction between fluid status and circulating NT-proBNP level in commencing dialysis. Multivariable logistic regression models were also utilized to examine the association of rapid renal function decline with the interaction between fluid status and circulating NT-proBNP level. Age, gender, diabetes mellitus, cardiovascular disease, diuretics usage, ACEI/ARB usages, eGFR, and urine PCR were selected in multivariate analysis for renal outcomes. In addition to above parameters, statin usage and low-density lipoprotein were put in multivariate analysis for MACEs or all-cause mortality. P-value for interaction was utilized to analyze whether a synergistic effect between fluid status and circulating NT-proBNP on clinical outcomes existed in all patients. Statistical analyses were conducted using SPSS 18.0 for Windows (SPSS Inc., Chicago, Illinois). Statistical significance was set at a two-sided p-value of less than 0.05.

Results

Characteristics of entire cohort

The comparison of clinical characteristics between groups based on HS value at 7% and the median of circulating NT-proBNP level (261.8pg/ml) is shown in Table 1. Of all patients, the mean age was 64.9±11.8 years, 53.0% were male, and the mean of HS was 7.8%. Ninety-three (39.4%) and 39 (16.5%) had diabetes and cardiovascular disease respectively. The patients with HS>7% and high circulating NT-proBNP level had the highest proportion of cerebral vascular disease and treatment with calcium channel blocker, β-blocker and diuretics than other groups. Systolic blood pressure, blood urea nitrogen and urine PCR were higher, and diastolic blood pressure, eGFR, serum albumin, hemoglobin and calcium levels were lower in patients with both HS>7% and high circulating NT-proBNP level than other groups (Table 1).

[Figure omitted. See PDF.]

Table 1. The clinical characteristics of study subjects stratified by plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.t001

The correlation between NT-proBNP and fluid status

The positive correlation between circulating NT-proBNP and fluid status is shown in Fig 1. Elevated NT-proBNP level was significantly correlated with high HS (unstandardized β: 4.24, 95% Confidence Interval (CI): 2.44–6.05, P<0.001) in multivariate linear regression (Table 2). The highest tertile of circulating NT-proBNP level was significantly associated with HS as compared with the lowest tertile of circulating NT-proBNP level (unstandardized β: 3.96, 95%Cl: 1.25–6.66, P = 0.004) after age, sex, diabetes mellitus, cardiovascular disease, diuretics usage, eGFR, urine PCR, and serum albumin and hemoglobin levels. There was a dose dependent correlation between circulating NT-proBNP level and fluid status.

[Figure omitted. See PDF.]

Fig 1. The correlation between plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.g001

[Figure omitted. See PDF.]

Table 2. The association of plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) with fluid status.

https://doi.org/10.1371/journal.pone.0202733.t002

Fluid status, NT-proBNP and renal outcomes

One hundred and twenty-nine patients (54.7%) commenced dialysis during a mean follow-up of 3.3±2.0 years (Table 3). Patients with both HS>7% and high circulating NT-proBNP level had the highest proportion of commencing dialysis among 4 groups (P = 0.043, Table 3). Kaplan-Meier curves showed patients with both HS>7% and high circulating NT-proBNP level were more likely to commence dialysis compared to others (Fig 2A). We further analyzed the interaction between fluid status and circulating NT-proBNP level in commencing dialysis (Table 4). The unadjusted and adjusted HRs for commencing dialysis in patients with both HS>7% and high circulating NT-proBNP level compared with those with HS≦7% and low circulating NT-proBNP level was 3.32 (95% CI: 2.14–5.16) and 1.71 (95% CI: 1.03–2.85). There was a significant synergic association of fluid status and circulating NT-proBNP with commencing dialysis in patients with CKD stages 4–5 (HR: 2.09, 95%CI: 1.01–4.30, P-interaction = 0.047).

[Figure omitted. See PDF.]

Fig 2.

Kaplan-Meier survival curve for (A) commencing dialysis and (B) major adverse cardiovascular events or all-cause mortality in study subjects stratified by plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.g002

[Figure omitted. See PDF.]

Table 3. Events of study subjects stratified by plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.t003

[Figure omitted. See PDF.]

Table 4. The risks for commencing dialysis and rapid eGFR decline according to plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.t004

Eighty-eight (37.3%) patients had rapid eGFR decline during the follow-up period. Fig 3 reveal the negative association of eGFR decline with HS or NT-proBNP. Patients with both HS>7% and high circulating NT-proBNP level had the greatest renal function decline (eGFR slope: -3.1(-6.1,-1.4) mL/min/1.73 m2/year, Table 3) among the four groups. Both HS>7% and high circulating NT-proBNP were synergistically associated with rapid eGFR decline in unadjusted model (2.40, 95% CI: 1.25–4.63), but not in adjusted analysis (Table 4). There was no significant interaction between HS and circulating NT-proBNP level in rapid renal function decline (P-interaction = 0.527).

[Figure omitted. See PDF.]

Fig 3.

The association of eGFR decline with (A) fluid status and (B) plasma N-terminal pro-brain natriuretic peptide (NT-proBNP).

https://doi.org/10.1371/journal.pone.0202733.g003

Fluid status, NT-proBNP, MACEs and all-cause mortality

Of all patients, forty-eight patients (20.3%) reached MACEs or all-cause mortality (Table 3) before commencing dialysis. Thirty-one had MACEs, 23 died, and 6 had both MACEs and mortality during the follow-up period. The causes of mortality included three cardiovascular events, 11 sepsis, three malignancy, three refusing dialysis and the rest were a mixture of other causes. The causes of MACEs were events of nine acute myocardial infarction, nine acute hemorrhagic or ischemic stroke, 12 hospitalizations due to congestive heart failure, one sick sinus syndrome and one aortic dissection. There were no significant differences in the proportion of MACEs and all-cause mortality between the four groups.

Patients with both HS>7% and high circulating NT-proBNP level had higher risk for reaching MACEs or all-cause mortality than others (Fig 2B). Not only HS (HR: 1.08, 95%CI: 1.03–1.13) but also log-transformed NT-proBNP (HR: 2.51, 95%CI: 1.27–4.95) was significantly associated with composite outcomes either MACEs or all-cause mortality (Table 5). The consistent significance was also in cox-proportional and multivariate analysis for MACEs or all-cause mortality alone. The adjusted HR of composite outcomes either MACEs or all-cause mortality was 2.41 (95% CI: 1.01–5.77) for patients of both HS>7% and high circulating NT-proBNP level compared with those with HS≦7% and low circulating NT-proBNP level. However, there was no significant result in analysis for only MACEs or all-cause mortality. No significant interaction between HS and circulating NT-proBNP level in MACEs or all-cause mortality was found.

[Figure omitted. See PDF.]

Table 5. The adjusted risks for major adverse cardiovascular events (MACEs) and all-cause mortality according to plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.t005

We also used urine PCR cut 1mg/mg in multivariable model of adverse outcomes for sensitivity analysis (S1 and S2 Tables).

Discussion

This study evaluated the interaction between plasma NT-proBNP level and fluid status in adverse clinical outcomes in patients with CKD stages 4–5 over an observation period of 3.3 years. CKD patients with both fluid overload and high plasma NT-proBNP level had more increased risk for commencing dialysis and composite outcomes either MACEs or all-cause mortality than others with only fluid overload or high plasma NT-proBNP level. NT-proBNP and fluid overload had a synergistic activity of prediction of adverse clinical outcomes in late stage of CKD.

Fluid overload causes cardiomyocyte elongation and leads to LV remodeling and decompensation [23,24]. Then, BNP will be synthesized from cardiomyocyte in response to increased stress and stretch of LV wall [1,2]. Therefore, NT-proBNP level has been considered as an indicator of intravascular fluid status [25, 26]. NT-proBNP was also correlated with fluid volume imbalance between ICW and ECW [16]. Our results found patients with both high HS and high NT-proBNP had higher NT-proBNP level than those with only high NT-proBNP without high HS, meaning that fluid status has an impact on the increase in NT-proBNP. Accumulating evidences show renal function affects circulating NT-proBNP level [27]. Deterioration of renal function increased NT-proBNP/BNP ratio [27]. Besides, underlying cardiovascular disease also has an impact on NT-proBNP level. Thus, we add baseline renal function and cardiovascular disease in adjusted model for analysis, and the results reveal a close correlation between fluid overload and NT-proBNP. NT-proBNP is positively associated with fluid status independent of renal function and underlying cardiovascular disease in late stages of CKD.

NT-proBNP and fluid overload share many pathophysiologic mechanisms of cardiorenal syndrome, such as excess activation of renin-angiotensin-aldosterone system (RAAS), impaired immunologic system and inflammation and [20, 28–31]. Activation of RAAS is involved in the impairment of LV function resulting in elevation of NT-proBNP [28], and RAAS also modulates hemodynamic stability by regulating blood pressure and fluid status [30]. The pro-inflammatory cytokines interleukin-1beta and tumor necrosis factor-alpha leads to a selective increase of BNP gene expression and secretion [31], and NT-proBNP is associated with inflammatory markers, such as interleukin-6 and CRP [32,33]. Otherwise, inflammation has a close link with fluid status [20]. Fluid overload increases gut permeability, further destroying protective barriers and causing overgrowth of pathogenic species [34]. Therefore, the interaction between NT-proBNP and fluid overload might be correlated with poor clinical prognosis. We demonstrated a synergistic association of NT-proBNP and fluid overload with adverse clinical outcomes. Both NT-proBNP and fluid status could provide greater predictive activity of adverse clinical outcomes in CKD population.

Besides, baseline renal function and proteinuria are traditional predictors of adverse clinical outcomes in CKD patients. Fluid status and plasma NT-proBNP both increase progressively with the decline in renal function and the increase in proteinuria [13, 35]. Based on this close correlation, we adjusted baseline renal function and the severity of proteinuria in the analysis model, and fluid status and NT-proBNP could predict disease progression. Besides, after adjusting well-known risk factors of poor clinical outcomes, such as aging, sex, underlying cardiovascular disease and diabetes mellitus, CKD patients with both high plasma NT-proBNP and fluid overload still had increased risks for commencing dialysis, MACEs or all-cause mortality. NT-proBNP and fluid status could be utilized to monitor cardiac-renal axis in clinical CKD practice.

NT-proBNP has been considered as a tool of the diagnostic and prognostic activities in patients with heart failure or CKD on dialysis or not [36–39]. Furthermore, numerous studies report NT-proBNP can be utilized to monitor the efficiency of heart failure [40, 41]. A NT-proBNP-guided management strategy can reduce mortality in patients with heart failure [40]. Besides, BNP also has a clinical utility to evaluate the effect of Beta-blocker on LV diastolic function in patients on dialysis [42]. Because of the close correlation between NT-proBNP and fluid status, NT-proBNP may help clinical physicians to evaluate the current fluid status and the effect of diuretics usage on fluid overload in CKD patients. Fluid status may be controlled by a NT-proBNP-driven management strategy, further ameliorating cardiovascular burdens in patients on dialysis. Similarly, fluid status assessed by BCM has been reported to assist in regression of left ventricular mass index and arterial stiffness, as well as decrease in blood pressure in hemodialysis patients [43]. However, the effect of a NT-proBNP or BCM-guided management strategy on adverse clinical outcomes remains to be determined in CKD patients not on dialysis. Further study is necessary to identify the influence of NT-proBNP and BCM-driven intervention on cardiovascular consequence, all-cause mortality and poor renal progression.

NT-proBNP and fluid overload have been considered as a biomarker of MACEs and all-cause mortality [14, 44, 45]. The consistent results are also shown in the present study, but we did not find the significant synergistic association of NT-proBNP and fluid overload with MACEs or all-cause mortality. The relatively small number of cohort and events of this study is one of the reasons why the statistical power is diminished. Beyond NT-proBNP and fluid status, uncertain mechanisms might participate in increased risks for MACEs and all-cause mortality in CKD patients. Besides, this study also has some limitations. Fluid status, NT-proBNP, and diuretics usage were measured once at enrollment. The association of time-varying fluid status and NT-proBNP with clinical outcomes could not be estimated. Additionally, urine sodium and sodium intake were not examined or recorded in the study, whereas positive sodium balance might affect fluid status, vascular pressure and NT-proBNP level [44]. The effect of sodium retention on fluid status and clinical outcomes might be underestimated.

Conclusions

Our study demonstrates that fluid overload and NT-proBNP are synergistically associated with commencing dialysis in patients with CKD stages 4–5. Patients with both fluid overload and high circulating NT-proBNP level had greater risks for MACEs or all-cause mortality than those with either fluid overload or high circulating NT-proBNP level. The interaction between NT-proBNP and fluid status in adverse outcomes should be considered in clinical care of late stages of CKD, and could be utilized in prediction of clinical outcomes more precisely.

Supporting information

[Figure omitted. See PDF.]

S1 Table. Sensitivity analysis of the risks for commencing dialysis and rapid eGFR decline according to plamsa N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.s001

(DOCX)

S2 Table. Sensitivity analysis of the adjusted risks for major adverse cardiovascular events (MACEs) and all-cause mortality according to plasma N-terminal pro-brain natriuretic peptide (NT-proBNP) and fluid status.

https://doi.org/10.1371/journal.pone.0202733.s002

(DOCX)

Acknowledgments

The authors thank the staff of the Statistical Analysis Laboratory, Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University for their help.

Citation: Tsai Y-C, Tsai H-J, Lee C-S, Chiu Y-W, Kuo H-T, Lee S-C, et al. (2018) The interaction between N-terminal pro-brain natriuretic peptide and fluid status in adverse clinical outcomes of late stages of chronic kidney disease. PLoS ONE 13(8): e0202733. https://doi.org/10.1371/journal.pone.0202733

References

1. Takami Y, Horio T, Iwashima Y, Takiuchi S, Kamide K, Yoshihara F, et al. Diagnostic and prognostic value of plasma brain natriuretic peptide in non-dialysis-dependent CRF. Am J Kidney Dis. 2004; 44(3): 420–428. pmid:15332214

2. Panteghini M, Clerico A. Understanding the clinical biochemistry of N-terminal pro-B-type natriuretic peptide: The prerequisite for its optimal clinical use. Clin Lab. 2004; 50(5–6): 325–331. pmid:15209441

3. Kamano C, Osawa H, Hashimoto K, Nishimura S, Saito SK, Kashiwagi T, et al. N-Terminal pro-brain natriuretic peptide as a predictor of heart failure with preserved ejection fraction in hemodialysis patients without fluid overload. Blood Purif. 2012; 33(1–3): 37–43. pmid:22143056

4. Sudoh T, Kangawa K, Minamino N, Matsuo H. A new natriuretic peptide in porcine brain. Nature. 1988; 332(6159): 78–81. pmid:2964562

5. Khan I, AFink J, Nass C, Chen H, Christenson R, deFilippi CR. N-terminal pro-B-type natriuretic peptide and B-type natriuretic peptide for identifying coronary artery disease and left ventricular hypertrophy in ambulatory chronic kidney disease patients. Am J Cardiol. 2006; 97(10): 1530–1534. pmid:16679099

6. Wang AY, Lam CW, Yu CM, Wang M, Chan IH, Zhang Y. N-terminal pro-brain natriuretic peptide: an independent risk predictor of cardiovascular congestion, mortality, and adverse cardiovascular outcomes in chronic peritoneal dialysis patients. J Am Soc Nephrol. 2007; 18(1): 321–330. pmid:17167121

7. Paniagua R, Ventura MD, Avila-Díaz M, Hinojosa-Heredia H, Méndez-Durán A, Cueto-Manzano A, et al. NT-proBNP, fluid volume overload and dialysis modality are independent predictors of mortality in ESRD patients. Nephrol Dial Transplant. 2010; 25(2): 551–557. pmid:19679559

8. Roberts MA, Hare DL, Sikaris K, Ierino FL. Temporal trajectory of B-type natriuretic peptide in patients with CKD stages 3 and 4, dialysis, and kidney transplant. Clin J Am Soc Nephrol. 2014; 9(6): 1024–1032. pmid:24721887

9. Kim SE, Park S, Kim JK, Kim SG, Kim HJ, Song YR. B-type natriuretic peptide predicts an ischemic etiology of acute heart failure in patients with stage 4–5 chronic kidney disease. Clin Biochem. 2014; 47(6): 344–348. pmid:24486650

10. Fu S, Luo L, Ye P, Yi S, Liu Y, Zhu B, et al. The ability of NT-proBNP to detect chronic heart failure and predict all-cause mortality is higher in elderly Chinese coronary artery disease patients with chronic kidney disease. Clin Interv Aging. 2013; 8: 409–417. pmid:23723693

11. Spanaus KS, Kronenberg F, Ritz E, Schlapbach R, Fliser D, Hersberger M, et al. B-type natriuretic peptide concentrations predict the progression of nondiabetic chronic kidney disease: the Mild-to-Moderate Kidney Disease Study. Clin Chem. 2007; 53(7): 1264–1272. pmid:17478561

12. Sundqvist S, Larson T, Cauliez B, Bauer F, Dumont A, Le Roy F, et al. Clinical Value of Natriuretic Peptides in Predicting Time to Dialysis in Stage 4 and 5 Chronic Kidney Disease Patients. PLoS One. 2016;11(8): e0159914. pmid:27548064

13. Tsai YC, Tsai JC, Chen SC, Chiu YW, Hwang SJ, Hung CC, et al. Association of fluid overload with kidney disease progression in advanced CKD: a prospective cohort study. Am J Kidney Dis. 2014; 63(1): 68–75. pmid:23896483

14. Tsai YC, Chiu YW, Tsai JC, Kuo HT, Hung CC, Hwang SJ, et al. Association of fluid overload with cardiovascular morbidity and all-cause mortality in stages 4 and 5 CKD. Clin J Am Soc Nephrol. 2015; 10(1): 39–46. pmid:25512646

15. Lee SW, Song JH, Kim GA, Lim HJ, Kim MJ. Plasma brain natriuretic peptide concentration on assessment of hydration status in hemodialysis patient. Am J Kidney Dis. 2003; 41(6): 1257–1266. pmid:12776279

16. Ohashi Y, Saito A, Yamazaki K, Tai R, Matsukiyo T, Aikawa A, et al. Brain Natriuretic Peptide and Body Fluid Composition in Patients with Chronic Kidney Disease: A Cross-Sectional Study to Evaluate the Relationship between Volume Overload and Malnutrition. Cardiorenal Med. 2016; 6(4): 337–346. pmid:27648015

17. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D, et al. 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 Inter Med. 1999; 130(6): 461–470.

18. Moissl UM, Wabel P, Chamney PW, Bosaeus I, Levin NW, Bosy-Westphal A, et al. Body fluid volume determination via body composition spectroscopy in health and disease. Physiol Meas. 2006; 27(9): 921–933. pmid:16868355

19. Chamney PW, Wabel P, Moissl UM, Müller MJ, Bosy-Westphal A, Korth O, et al. A whole-body model to distinguish excess fluid from the hydration of major body tissues. Am J Clin Nutr. 2007; 85(1): 80–89. pmid:17209181

20. Hung SC, Kuo KL, Peng CH, Wu CH, Lien YC, Wang YC, et al. Volume overload correlates with cardiovascular risk factors in patients with chronic kidney disease. Kidney Int. 2014; 85(3): 703–709. pmid:24025647

21. Wizemann V, Rode C, Wabel P. Whole-body spectroscopy (BCM) in the assessment of normovolemia in hemodialysis patients. Contrib Nephrol. 2008; 161: 115–118. pmid:18451666

22. Crepaldi C, Soni S, Chionh CY, Wabel P, Cruz DN, Ronco C, et al. Application of body composition monitoring to peritoneal dialysis patients. Contrib Nephrol. 2009; 163: 1–6. pmid:19494588

23. Ryan TD, Rothstein EC, Aban I, Tallaj JA, Husain A, Lucchesi PA, et al. Left ventricular eccentric remodeling and matrix loss are mediated by bradykinin and precede cardiomyocyte elongation in rats with volume overload. J Am Coll Cardiol. 2007; 49(7): 811–821. pmid:17306712

24. Grossman W, Jones D, McLaurin LP. Wall stress and patterns of hypertrophy in the human left ventricle. J Clin Invest. 1975; 56(1): 56–64. pmid:124746

25. Goldfarb-Rumyantzev AS, Chelamcharla M, Bray BE, Leypoldt JK, Lavasani I, Nelson N, et al. Volume indicators and left ventricular mass during aggressive volume management in patients on thrice weekly haemodialysis. Nephron Clin Pract. 2009; 113(4): 270–280.

26. Booth J, Pinney J, Davenport A. N-terminal proBNP—marker of cardiac dysfunction, fluid overload, or malnutrition in hemodialysis patients? Clin J Am Soc Nephrol. 2010; 5(6): 1036–1040. pmid:20507952

27. Takase H, Dohi Y.Kidney function crucially affects B-type natriuretic peptide (BNP), N-terminal proBNP and their relationship. Eur J Clin Invest. 2014; 44 (3):303–308. pmid:24372567

28. Ikonomidis I, Tzortzis S, Tsantes A, Ntai K, Triantafyllidi H, Trivilou P, et al. The interplay between renin-angiotensin system activation, abnormal myocardial deformation and neurohumoral activation in hypertensive heart disease: a speckle tracking echocardiography study. Int J Cardiovasc Imaging. 2017; 33(3): 323–329. pmid:27787699

29. Shaw SM, Fildes JE, Puchałka CM, Basith M, Yonan N, Williams SG. BNP directly immunoregulates the innate immune system of cardiac transplant recipients in vitro. Transpl Immunol. 2009; 20(3): 199–202. pmid:18812222

30. Muñoz-Durango N, Fuentes CA, Castillo AE, González-Gómez LM, Vecchiola A, Fardella CE, et al. Role of the Renin-Angiotensin-Aldosterone System beyond Blood Pressure Regulation: Molecular and Cellular Mechanisms Involved in End-Organ Damage during Arterial Hypertension. Int J Mol Sci. 2016; 17(7): E797. pmid:27347925

31. Meirovich YF, Veinot JP, de Bold ML, Haddad H, Davies RA, Masters RG, et al. Relationship between natriuretic peptides and inflammation: proteomic evidence obtained during acute cellular cardiac allograft rejection in humans. J Heart Lung Transplant. 2008; 27(1): 31–37. pmid:18187084

32. Provan SA, Angel K, Odegard S, Mowinckel P, Atar D, Kvien TK. The association between disease activity and NT-proBNP in 238 patients with rheumatoid arthritis: a 10 year longitudinal study. Arthritis Res Ther. 2008; 10(3): R70. pmid:18573197

33. Bradham WS, Ormseth MJ, Oeser A, et al. Insulin resistance is associated with increased concentrations of NT-proBNP in rheumatoid arthritis: IL-6 as a potential mediator. Inflammation. 2014; 37(3): 801–808. pmid:24402421

34. McIntyre CW, Harrison LE, Eldehni MT, Jefferies HJ, Szeto CC, John SG, et al. Circulating endotoxemia: a novel factor in systemic inflammation and cardiovascular disease in chronic kidney disease. Clin J Am Soc Nephrol. 2011; 6(1): 133–141. pmid:20876680

35. Desai AS, Toto R, Jarolim P, Uno H, Eckardt KU, Kewalramani R, et al. Association between cardiac biomarkers and the development of ESRD in patients with type 2 diabetes mellitus, anemia, and CKD. Am J Kidney Dis. 2011; 58(5): 717–728. pmid:21820220

36. Worster A, Balion CM, Hill SA, Santaguida P, Ismaila A, McKelvie R, et al. Diagnostic accuracy of BNP and NT-proBNP in patients presenting to acute care settings with dyspnea: a systematic review. Clin Biochem. 2008; 41(4–5): 250–259. pmid:17915204

37. Wang AY, Lai KN. Use of cardiac biomarkers in end-stage renal disease. J Am Soc Nephrol. 2008; 19(9): 1643–1652. pmid:18322158

38. Wang AY. Clinical utility of natriuretic peptides in dialysis patients. Semin Dial. 2012; 25(3): 326–33. pmid:22607214

39. Yasuda K, Kimura T, Sasaki K, Obi Y, Iio K, Yamato M, et al. Plasma B-type natriuretic peptide level predicts kidney prognosis in patients with predialysis chronic kidney disease. Nephrol Dial Transplant. 2012; 27(10): 3885–3891. pmid:23114906

40. Felker GM, Hasselblad V, Hernandez AF, O’Connor CM. Biomarker guided therapy in chronic heart failure: A meta-analysis of randomized controlled trials. Am Heart J. 2009; 158(3): 422–430. pmid:19699866

41. Eurlings LW, van Pol PE, Kok WE, van Wijk S, Lodewijks-van der Bolt C, Balk AH,et al. Management of chronic heart failure guided by individual N-terminal pro-B-type natriuretic peptide targets: results of the PRIMA (Can PRo-brain-natriuretic peptide guided therapy of chronic heart failure IMprove heart fAilure morbidity and mortality?) study. J Am Coll Cardiol. 2010; 56(25): 2090–100 pmid:21144969

42. Kojima M, Sato K, Kimura G, Ueda R, Dohi Y. Carvedilol reduces elevated B-type natriuretic peptide in dialyzed patients without heart failure: Cardioprotective effect of the beta-blocker. J Cardiovasc Pharmacol. 2007; 49(4): 191–196. pmid:17438403

43. Hur E, Usta M, Toz H, Asci G, Wabel P, Kahvecioglu S, et al. Effect of fluid management guided by bioimpedance spectroscopy on cardiovascular parameters in hemodialysis patients: a randomized controlled trial. Am J Kidney Dis. 2013; 61(6): 957–965. pmid:23415416

44. Cheng YJ, Yao FJ, Liu LJ, Tang K, Lin XX, Li WJ, et al. B-type natriuretic peptide and prognosis of end-stage renal disease: a meta-analysis. PLoS One. 2013; 8(11): e7930

45. Vickery S, Price CP, John RI, Abbas NA, Webb MC, Kempson ME, et al. B-type natriuretic peptide (BNP) and amino-terminal proBNP in patients with CKD: relationship to renal function and left ventricular hypertrophy. Am J Kidney Dis. 2005; 46(4): 610–620 pmid:16183415