Literature DB >> 30202087

Role of blood urea nitrogen in predicting the post-discharge prognosis in elderly patients with acute decompensated heart failure.

Xiaohong Ren1, Wei Qu1, Lijuan Zhang1, Miao Liu1, Xuling Gao1, Yuting Gao1, Xiaodan Cheng1, Weiwei Xu1, Youhong Liu2.   

Abstract

Blood urea nitrogen (BUN) is a surrogate marker for neurohormonal activation, but the association between BUN and the post-discharge prognosis in elderly patients with acute decompensated heart failure (ADHF) is not well defined. We explored the association between BUN and post-discharge all-cause mortality in 652 elderly patients (73.9 ± 7.8 yr) with ADHF. All patients were followed for a mean duration of 32 months (12-69 months). BUN was analyzed both as a continuous variable and according to two categories: low BUN group (BUN < 15.35 mmol/L, N = 361) and high BUN group (BUN ≥ 15.35 mmol/L, N = 291). The risk of all-cause mortality increased by 1.6% per 1 mmol/L increase in BUN concentration when BUN was used as a continuous variable [hazard ratio (HR): 1.016, 95% confidence interval (CI): 1.006-1.026, p = 0.002]. BUN maintained an independent and significant positive correlation with all-cause mortality as a categorical variable (HR: 1.355, 95% CI: 1.023-1.794, p = 0.034 for the high BUN group). The BUN C-statistic for predicting all-cause mortality was 0.624 (95% CI: 0.585-0.661). The cut-off value for BUN was 15.35 mmol/L with sensitivity of 0.58 and specificity of 0.63. The prognostic performance of BUN was similar to brain natriuretic peptide (BNP) for predicting all-cause mortality (C-statistic: z = 0.044, p = 0.965). These results suggest that BUN is an independent predictor of post-discharge all-cause mortality in elderly patients with ADHF and its prognostic performance was similar to that of BNP.

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Year:  2018        PMID: 30202087      PMCID: PMC6131513          DOI: 10.1038/s41598-018-31059-4

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Morbidity due to heart failure (HF) is increasing gradually[1], and the incidence rate of newly occurring HF is far higher in the elderly population than in the young and middle-aged population[2]. Elderly patients with HF also have a worse prognosis than young and middle-aged patients[1,2]. Patients with acute decompensated heart failure (ADHF) usually suffer from high mortality after discharge[3,4]. Studies have shown that activation of the sympathetic nervous system (SNS), renin-angiotensin-aldosterone system (RAS), arginine vasopressin (AVP) and neurohumors are major pathophysiological changes in patients with HF[5,6]. The increased activities of the SNS and RAS enhance reabsorption of urea nitrogen by the proximal and distal renal tubules, and the increased secretion of AVP facilitates distribution of the urea transporter in the collecting ducts[5,6]. Therefore, blood urea nitrogen (BUN) is not only an indicator reflecting renal function, but also an effective marker indicating neurohormonal activation[5-7]. Previous studies have reported a significant correlation between an increase in BUN and a poor prognosis in patients with acute[8-14] and chronic[15-17] HF. However, no study has focused on the relationship between BUN and the post-discharge prognosis in elderly patients with ADHF. This study explored the effects of BUN on the post-discharge prognosis in elderly patients with ADHF.

Results

Baseline Characteristics of the Study Population by Clinical Outcome

The final study cohort consisted of 652 elderly patients with ADHF. The cohort was divided into a surviving group [418 patients (64.1%)] and a death group [234 patients (35.9%)]. The clinical characteristics of the two groups are shown in Table 1. The death group had significantly lower percentages of males, New York Heart Association (NYHA) class III, and discharge prescriptions of a β-receptor blocker and spironolactone, compared with the surviving group. Age, creatinine, uric acid, BUN, fasting blood glucose, brain natriuretic peptide (BNP), and heart rate were higher in the death group than those in the surviving group. Lower levels of red blood cells, hemoglobin, albumin, prealbumin, cholesterol, low density lipoprotein, serum sodium and ejection fraction were observed in the death group.
Table 1

Baseline Characteristics of the population by clinical outcome, median (IQR), or N (%), or means ± SD.

Variablesurvival group (n = 418)death group (n = 234)Overall (n = 652)p-value
Demographics
   Age, yrs72.4 ± 7.376.5 ± 8.073.9 ± 7.8<0.001
   male169 (40.4)126 (53.8)295 (45.2)0.001
Medical history
   Ischemia cardiomyopathy99 (23.7)57 (24.7)156 (23.9)0.966
   Diabetes Mellitus98 (23.4)60 (25.6)158 (24.2)0.530
   Hypertension250 (59.8)134 (57.3)384 (58.9)0.527
   Current smoking113 (27.0)64 (27.4)177 (27.1)0.930
   Atrial fibrillation59 (14.1)32 (13.7)91 (14.0)0.877
   Dilated cardiomyopathy19 (4.5)11 (4.7)30 (4.6)0.928
   Valvular disease29 (6.9)14 (6.0)0.2220.637
Clinical Presentation
   NYHA class<0.001
   III141 (33.7)28 (12.0)169 (25.9)
   IV277 (66.3)206 (88.0)483 (74.1)
   SBP on admission, mm Hg138.3 ± 25.3138.9 ± 26.9138.5 ± 25.90.783
   DBP on admission, mm Hg81.5 ± 14.580.2 ± 14.781.1 ± 14.60.262
   Heart rate on admission, bpm82.2 ± 22.388.2 ± 20.884.4 ± 21.90.001
Laboratory results on admission
   Leukocyte count (×109/L)7.09 ± 2.607.64 ± 3.137.29 ± 2.820.074
   Hemoglobin, g/L125.7 ± 20.2119.2 ± 22.7123.4 ± 21.30.001
   Albumin, g/L38.0 ± 4.135.9 ± 4.337.2 ± 4.3<0.001
   SGOT, U/L18 (12, 29)18 (11, 36)18 (12, 32)0.663
   SGPT, U/L22 (16, 37)23 (15, 43)22 (16, 38)0.858
   Creatinine, umol/L81 (69, 100)93 (74, 119)84 (70, 106)<0.001
   Uric acid, umol/L335 (257, 425)370 (272, 488)345 (259, 444)0.001
   BUN, mmol/L13.92 (11.04, 17.82)16.36 (12.72, 23.10)14.64 (11.58, 19.46)<0.001
   Total cholesterol, mmol/L4.45 ± 1.214.14 ± 1.184.34 ± 1.210.001
   Low density lipoprotein, mmol/L2.67 ± 0.932.40 ± 0.952.57 ± 0.940.001
   High density lipoprotein, mmol/L1.17 ± 0.371.14 ± 0.481.16 ± 0.410.304
   Triglyceride, mmol/L1.42 ± 1.001.30 ± 1.101.37 ± 1.030.177
   fasting blood glucose, mmol/L6.17 ± 1.846.56 ± 2.206.31 ± 1.980.005
   serum potassium, mmol/L4.07 ± 0.534.12 ± 0.634.09 ± 0.570.381
   serum sodium, mmol/L140.1 ± 3.9138.0 ± 5.1139.3 ± 4.5<0.001
   Troponin-I, ng/mL0.04 (0.01, 0.47)0.07 (0.02, 2.47)0.05 (0.01, 0.83)0.548
   BNP, ng/L752 (291, 1576)1167 (607, 2345)891 (363, 1759)<0.001
   Ejection fraction on admission%52.3 ± 12.448.1 ± 13.250.8 ± 12.8<0.001
Medical treatment at discharge
   ACEI/ARB330 (78.9)183 (78.4)513 (78.7)0.890
   Beta-blockers273 (65.3)129 (55.1)402 (61.7)0.010
   Spironolactone276 (66.0)129 (55.1)405 (62.1)0.006

NYHA, New York Heart Association; SBP, systolic blood pressure; DBP, diastolic blood pressure; bpm, beats per minute; SGOT, serum glutamic oxaloacetic transaminase; SGPT, serum glutamate-pyruvate transaminase; BUN, blood urea nitrogen; BNP, brain natriuretic peptide; ACEI/ARB, Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers.

Baseline Characteristics of the population by clinical outcome, median (IQR), or N (%), or means ± SD. NYHA, New York Heart Association; SBP, systolic blood pressure; DBP, diastolic blood pressure; bpm, beats per minute; SGOT, serum glutamic oxaloacetic transaminase; SGPT, serum glutamate-pyruvate transaminase; BUN, blood urea nitrogen; BNP, brain natriuretic peptide; ACEI/ARB, Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers.

Prognostic Performance of BUN and BNP for the Prognosis Prediction

The C-statistics of BUN and BNP for predicting all-cause mortality were 0.624 [95% confidence interval (CI): 0.585–0.661] and 0.625 (95% CI: 0.587–0.662). The cut-off values for BUN and BNP for predicting all-cause mortality were 15.35 mmol/L with sensitivity of 0.58 and specificity of 0.63 and 805 ng/L with sensitivity of 0.67 and specificity of 0.53, respectively (Table 2, Fig. 1). The prognostic performance of BUN was similar to that of BNP (C-statistic: z = 0.044, p = 0.965) (Table 2).
Table 2

Prognostic performance of BUN and BNP for the prognosis prediction.

C-statisticStandard errorp-Value95% CIDifferenceZp-Value
BUN0.6240.0231<0.0010.585–0.661
BNP0.6250.0226<0.0010.587–0.662
BUN vs. BNP0.0010.0440.965
Figure 1

ROC curve analysis of BUN and BNP on the long-term prognosis of elderly patients with ADHF.

Prognostic performance of BUN and BNP for the prognosis prediction. ROC curve analysis of BUN and BNP on the long-term prognosis of elderly patients with ADHF.

Clinical Characteristics of the Study Population Based on BUN

According to the BUN cut-off value, 652 patients were divided into the low BUN group (BUN < 15.35 mmol/L, N = 361, 55.4%) and the high BUN group (BUN ≥ 15.35 mmol/L, N = 291, 44.6%). The clinical characteristics of the two groups are shown in Table 3. A higher proportion of males, NYHA class IV, and dilated cardiomyopathy were detected in the high BUN group but a lower proportion of hypertension and discharge prescriptions for β-receptor blockers and spironolactone was detected in the high BUN group than in the low BUN group. The high BUN group had lower diastolic and systolic blood pressure at admission and lower hemoglobin, albumin, total cholesterol, low density lipoprotein, high density lipoprotein, triglycerides, serum sodium, and ejection fraction, but had a higher age, creatinine, uric acid, potassium, and BNP than those in the low BUN group. The mortality rate in the high BUN group was significantly higher than that in the low BUN group during the follow-up (46.4% vs 27.4%, p < 0.001).
Table 3

Clinical Characteristics of the population by BUN, median (IQR), or N (%), or means ± SD.

VariableLow BUN group (n = 361)High BUN group (n = 291)p-value
Demographics
   Age, yrs72.7 ± 7.775.3 ± 7.7<0.001
   male137 (38.0)158 (54.3)<0.001
Medical history
   Ischemia cardiomyopathy171 (47.4)139 (47.8)0.919
   Diabetes Mellitus85 (23.5)73 (25.1)0.648
   Hypertension229 (63.4)155 (53.3)0.009
   Current smoking99 (27.4)78 (26.8)0.860
   Atrial fibrillation47 (13.0)44 (15.1)0.442
   Dilated cardiomyopathy11 (3.0)19 (6.5)0.035
   Valvular disease24 (6.6)19 (6.5)0.951
Clinical Presentation
   NYHA class<0.001
   III120 (33.2)49 (16.9)
   IV241 (66.8)242 (83.1)
   SBP on admission, mm Hg141.2 ± 25.5135.2 ± 26.00.003
   DBP on admission, mm Hg82.5 ± 13.979.3 ± 15.30.006
   Heart rate on admission, bpm83.0 ± 21.486.0 ± 22.50.090
Laboratory results on admission
   Leukocyte count (×109/L)7.11 ± 2.597.51 ± 3.070.148
   Hemoglobin, g/L126.0 ± 18.7120.0 ± 23.80.001
   Albumin, g/L38.1 ± 4.236.1 ± 4.1<0.001
   SGOT, U/L18 (12, 30)18 (12, 33)0.790
   SGPT, U/L21 (16, 37)24 (16, 43)0.058
   Creatinine, umol/L76 (66, 90)101 (82, 131)<0.001
   Uric acid, umol/L308 (237, 398)405 (295, 507)0.001
   Total cholesterol, mmol/L4.54 ± 1.124.09 ± 1.26<0.001
   Low density lipoprotein, mmol/L2.73 ± 0.962.37 ± 0.89<0.001
   High density lipoprotein, mmol/L1.20 ± 0.411.10 ± 0.410.002
   Triglyceride, mmol/L1.48 ± 1.111.24 ± 0.910.003
   fasting blood glucose, mmol/L6.33 ± 1.956.28 ± 2.020.741
   serum potassium, mmol/L3.95 ± 0.454.26 ± 0.65<0.001
   serum sodium, mmol/L140.2 ± 3.9138.3 ± 4.9<0.001
   Troponin-I, ng/mL0.04 (0.01, 0.71)0.06 (0.02, 0.98)0.897
   BNP, ng/L732 (290, 1455)1168 (506, 2319)<0.001
   Ejection fraction on admission%53.3 ± 12.147.7 ± 13.1<0.001
Medical treatment at discharge
   ACEI/ARB288 (79.8)225 (77.3)0.312
   Beta-blockers247 (68.4)155 (53.3)<0.001
   Spironolactone242 (67.0)163 (56.0)0.004
Clinical Outcome
   all-cause mortality,%99 (27.4)135 (46.4)<0.001

NYHA, New York Heart Association; SBP, systolic blood pressure; DBP, diastolic blood pressure; bpm, beats per minute; SGOT, serum glutamic oxaloacetic transaminase; SGPT, serum glutamate-pyruvate transaminase; BUN, blood urea nitrogen; BNP, brain natriuretic peptide; ACEI/ARB, Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers.

Clinical Characteristics of the population by BUN, median (IQR), or N (%), or means ± SD. NYHA, New York Heart Association; SBP, systolic blood pressure; DBP, diastolic blood pressure; bpm, beats per minute; SGOT, serum glutamic oxaloacetic transaminase; SGPT, serum glutamate-pyruvate transaminase; BUN, blood urea nitrogen; BNP, brain natriuretic peptide; ACEI/ARB, Angiotensin-converting enzyme inhibitors/Angiotensin receptor blockers.

Prognostic Value of BUN for Determining Clinical Outcome

BUN was significantly predictive of all-cause mortality when used as a continuous variable [hazard ratio (HR): 1.029, 95% CI: 1.020–1.037, p < 0.001 for per 1 mmol/L increase] in the univariate Cox regression analysis (Table 4). After adjusting for covariates, BUN remained associated with all-cause mortality, with an increased all-cause mortality risk of 1.6% per 1 mmol/L increase in BUN concentration (HR: 1.016, 95% CI: 1.006–1.026, p = 0.002) (Table 4).
Table 4

Effects of multiple variables on Clinical Outcomes in COX regression analysis.

Univariate AnalysisMultivariate Analysis
HR95% CIp valueHR95% CIp value
BNP per 1 ng/L increase1.0001.000–1.000<0.0011.0001.000–1.0000.001
Creatinine per 1 umol/L increase1.0000.997–1.0030.997
BUN as a continuous variable
   BUN per 1 mmol/L increase1.0291.020–1.037<0.0011.0161.006–1.0260.002a
BUN as a categories variable
   Low BUN groupReferenceReference
   High BUN group1.9591.511–2.541<0.0011.3551.023–1.7940.034a

aAdjusted for age, gender, heart rate on admission, NYHA class, hemoglobin, albumin, uric acid, creatinine, total cholesterol, low density lipoprotein, fasting blood glucose, serum sodium, BNP, ejection fraction on admission, use of of β-receptor blockers and spironolactone.

Effects of multiple variables on Clinical Outcomes in COX regression analysis. aAdjusted for age, gender, heart rate on admission, NYHA class, hemoglobin, albumin, uric acid, creatinine, total cholesterol, low density lipoprotein, fasting blood glucose, serum sodium, BNP, ejection fraction on admission, use of of β-receptor blockers and spironolactone. When categorized into two groups (low BUN group: BUN < 15.35 mmol/L; high BUN group: BUN ≥ 15.35 mmol/L), BUN remained significantly predictive of all-cause mortality (Table 4). In the univariate Cox regression analysis, the high BUN group had a substantially higher risk of all-cause death compared with the low BUN group (HR: 1.959, 95% CI: 1.511–2.541, p < 0.001) (Table 4). In the multivariate Cox regression analysis, the high BUN group still conferred a significantly higher all-cause mortality than the low BUN group (HR: 1.355, 95% CI: 1.023–1.794, p = 0.034) (Table 4). BNP independently predicted all-cause mortality in the univariate and multivariate Cox regression analyses (Table 4). However, creatinine was not an independent prognostic factor (Table 4). Pearson’s correlation analysis revealed that time of death was significantly and negatively correlated with BUN level (r = −0.243, p < 0.001) (Fig. 2).
Figure 2

The correlation between BUN level and time of death.

The correlation between BUN level and time of death.

Discussion

The present study tested the association between BUN and post-discharge all-cause mortality in elderly patients with ADHF. The main findings were as follows: (1) BUN was an independent predictor of post-discharge all-cause mortality in elderly patients with ADHF; (2) the prognostic performance of BUN was similar to that of BNP for predicting post-discharge all-cause mortality in elderly patients with ADHF. BUN is a protein metabolic product of the human body that is synthesized in the liver and excreted by the kidneys. Thus, the BUN level represents the balance between urea production and renal excretion and is an important marker of renal damage. In the past, BUN has only been used to reflect renal function. For the first time, Aronson et al. studied the value of BUN for prognosing patients admitted for ADHF[8]. They found that BUN was an independent predictor of long-term all-cause mortality in patients admitted for ADHF[8]. This observation was verified and extended by other researchers who found that elevated BUN was an independent predictor of adverse outcomes in patients with acute[8-14] and chronic[15-17] HF. In addition, BUN was confirmed to be a stronger predictor of adverse outcomes than serum creatinine or estimated glomerular filtration rate (eGFR)[8,15,16]. However, no study has focused on the relationship between BUN and the post-discharge prognosis in elderly patients with ADHF. Our study confirmed that a high BUN was an independent predictor of all-cause mortality in elderly patients with ADHF. The risk of all-cause mortality increased by 1.6% per 1 mmol/L increase in BUN concentration when BUN was considered a continuous variable (HR: 1.016, 95% CI: 1.006–1.026, p = 0.002). BUN still maintained an independent and significant positive correlation with all-cause mortality as a categorical variable (HR: 1.355, 95% CI: 1.023–1.794, p = 0.034 for the high BUN group). The pathophysiological association between BUN and adverse outcomes in patients with HF has been evaluated. First, HF activates the SNS and RAS, which can decrease eGFR and increase tubular urea reabsorption[5,6]. The RAS can increase the concentration-dependent reabsorption of urea by the proximal renal tubules, while the SNS can increase flow-dependent reabsorption of urea by the distal renal tubules. Previous studies have reported that BUN levels are correlated with the neurohumoral response[7,18,19]. Secondly, more AVP is secreted by patients suffering from HF, resulting in an increased distribution of the urea transporter in the collecting ducts, further causing an increase in urea reabsorption[5,6]. Thus, BUN may be a surrogate marker for activation of the SNS, RAS, and AVP. BNP is a very important biomarker in patients with HF. It is widely recommended for the diagnosis, treatment, and the prognostic prediction of patients with HF[20,21]. In this study, both BUN and BNP independently predicted all-cause mortality. BUN was also proven to have the same discriminatory performance as BNP for predicting all-cause mortality (C-statistic: z = 0.044, p = 0.965). Taken together, BUN is a very useful clinical parameter to predict the long-term prognosis in elderly patients with ADHF, and can help us identify those patients at high risk for post-discharge all-cause death. These results emphasize the prognostic impact of BUN for post-discharge prognosis in elderly patients with ADHF. This study had several limitations. First, this study was retrospective and observational, so potential confounders and selection bias could not be completely ruled out. Second, this study did not include all factors that influence BUN level, such as blood volume, nutritional state, gastrointestinal bleeding, and muscle wasting. Third, BUN was measured only at a single time-point (at admission), as studies have reported that patients with HF and a high BUN during hospitalization have a worse long-term prognosis[11,14,17]. Last, this study did not explore the effects of eGFR on the long-term prognosis in elderly patients with ADHF, because body weight data were lacking. However, this study confirmed that it was BUN, not eGFR or creatinine that independently predicted adverse outcomes in patients with ADHF[8]. Particularly, neurohormonal activation and hemodynamic abnormalities may play a prominent role in patients with ADHF[5,6]. BUN may increase because of activation of the SNS, RAS and AVP[5,6], independently of changes in eGFR.

Conclusions

BUN was an independent predictor of post-discharge all-cause mortality in elderly patients with ADHF. The prognostic performance of BUN was similar to that of BNP.

Methods

Study Design and Setting

This study was based on a retrospective cohort. In total, 670 consecutive elderly patients (age ≥ 60 years, average 73.9 ± 7.8 yr, 59.6% females), who were hospitalized for ADHF at a large hospital in Northeast China (Fourth People’s Hospital of Shenyang, Shenyang, China), were included in the cohort from January 2012 to January 2016. ADHF was defined according to guidelines[20,21]. All patients received standardized HF treatment according to the guidelines[20,21]. Patients who were receiving regular hemodialysis were excluded (n = 18). The final study cohort consisted of 652 patients. Clinical data of all cases were collected from the electronic medical records. Left ventricular ejection fraction was determined by echocardiography during hospitalization. In all cases, venous blood samples were drawn on admission into standard tubes and measured for BUN using a completely automated biochemistry-immunity analyzer (Ci 16200, Abbott, Abbott Park, IL, USA) in the core laboratory of the hospital. Clinical follow-up was assessed in January 2017 by a hospital visit or a phone interview of the patient’s general practitioner/cardiologist, the patient himself, or their family. All patients were followed for a mean duration of 32 months (12–69 months). The clinical endpoint of the study was all-cause mortality, which was identified from the patients’ medical records or the patient’s referring hospital physician. All events were validated by two independent event-judge physicians. This study complied with the Declaration of Helsinki, and the Fourth People’s Hospital of Shenyang Research Ethics Committee approved this research protocol. Written informed consent was formally obtained from all participants.

Statistical Analysis

Quantitative variables are presented as mean ± standard deviation or median (interquartile range), and categorical variables are presented as counts and proportions (%). The Cox proportional-hazards regression model was used to analyze the effect of the variables on event-free survival. Variables showing significance in the univariate analysis (Table 1, p < 0.05) were entered into the final model, including age, gender, heart rate on admission, NYHA class, hemoglobin, albumin, uric acid, creatinine, total cholesterol, low density lipoprotein, fasting blood glucose, serum sodium, BNP, ejection fraction on admission, and use of β-receptor blockers and spironolactone. BUN was analyzed as a continuous and categorical variable. The results are reported as HRs with associated 95% CIs. The predictive performance of BUN and BNP was assessed by an index of discrimination (C-statistic). The C-statistic, which is defined by the area under the receiver operating characteristic curve in relation to all-cause mortality, was compared using a nonparametric test developed by DeLong et al.[22] and MedCalc software for Windows, version 11.4.2.0 (MedCalc Software, Mariakerke, Belgium). Pearson’s correlation analysis was conducted to analyze the relationship between BUN level and time of death. All tests were two-sided, and a p-value < 0.05 was considered significant. All statistical analyses were performed with SPSS version 19 software (SPSS Inc., Chicago, IL, USA).
  22 in total

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4.  Serum blood urea nitrogen and plasma brain natriuretic Peptide and low diastolic blood pressure predict cardiovascular morbidity and mortality following discharge in acute decompensated heart failure patients.

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Authors:  Katsuya Kajimoto; Yuichiro Minami; Naoki Sato; Teruo Takano
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7.  Relation of blood urea nitrogen to long-term mortality in patients with heart failure.

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8.  Admission or changes in renal function during hospitalization for worsening heart failure predict postdischarge survival: results from the Outcomes of a Prospective Trial of Intravenous Milrinone for Exacerbations of Chronic Heart Failure (OPTIME-CHF).

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9.  Elevated blood urea nitrogen level as a predictor of mortality in patients admitted for decompensated heart failure.

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Journal:  Am J Med       Date:  2004-04-01       Impact factor: 4.965

10.  2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.

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  7 in total

1.  Blood Urea Nitrogen for Short-Term Prognosis in Patients with Cardiogenic Shock Complicating Acute Myocardial Infarction.

Authors:  Yuansong Zhu; Bryan Richard Sasmita; Xiankang Hu; Yuzhou Xue; Hongbo Gan; Zhenxian Xiang; Yi Jiang; Bi Huang; Suxin Luo
Journal:  Int J Clin Pract       Date:  2022-03-15       Impact factor: 3.149

2.  Validation and derivation of short-term prognostic risk score in acute decompensated heart failure in China.

Authors:  Hong-Liang Zhao; Xiao-Li Gao; Ying-Hua Liu; Sen-Lin Li; Qi Zhang; Wei-Chao Shan; Qun Zheng; Jiang Zhou; Yong-Zheng Liu; Li Liu; Nan Guo; Hong-Sen Tian; Qing-Min Wei; Xi-Tian Hu; Ying-Kai Cui; Xue Geng; Qian Wang; Wei Cui
Journal:  BMC Cardiovasc Disord       Date:  2022-07-07       Impact factor: 2.174

3.  Urea level is an independent predictor of mortality in patients with severe aortic valve stenosis.

Authors:  Dan Haberman; Gil Chernin; Valery Meledin; Meital Zikry; Mony Shuvy; Gera Gandelman; Sorel Goland; Jacob George; Sara Shimoni
Journal:  PLoS One       Date:  2020-03-11       Impact factor: 3.240

4.  Blood Urea Nitrogen and In-Hospital Mortality in Critically Ill Patients with Cardiogenic Shock: Analysis of the MIMIC-III Database.

Authors:  En-Qian Liu; Chun-Lai Zeng
Journal:  Biomed Res Int       Date:  2021-02-01       Impact factor: 3.411

5.  The association of blood urea nitrogen levels upon emergency admission with mortality in acute exacerbation of chronic obstructive pulmonary disease.

Authors:  Lan Chen; Lijun Chen; Han Zheng; Sunying Wu; Saibin Wang
Journal:  Chron Respir Dis       Date:  2021 Jan-Dec       Impact factor: 2.444

6.  Development and validation of a prediction model for in-hospital mortality of patients with severe thrombocytopenia.

Authors:  Yan Lu; Qiaohong Zhang; Jinwen Jiang
Journal:  Sci Rep       Date:  2022-04-15       Impact factor: 4.996

7.  Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model.

Authors:  Chu Zheng; Jing Tian; Ke Wang; Linai Han; Hong Yang; Jia Ren; Chenhao Li; Qing Zhang; Qinghua Han; Yanbo Zhang
Journal:  BMC Cardiovasc Disord       Date:  2021-08-04       Impact factor: 2.298

  7 in total

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