Clinical and Laboratory Predictors of Mortality in Patients with Advanced Heart Failure (Stage D), Data Derived from Rajaie Acute Systolic Heart Failure (RASHF) Data Registry

AUTHORS

Rabeah Zamani 1 , Maryam Chenaghlou 1 , * , Zeinab Norouzi 1 , Mohammad Mostafa Ansari Ramandi 2 , Sepideh Taghavi 1 , Ahmad Amin 1 , Nasim Naderi 1

1 Rajaie Cardiovascular, Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran

2 Seyed Mostafa Khomeini Hospital, Birjand University of Medical Sciences, Birjand, Iran

How to Cite: Zamani R, Chenaghlou M, Norouzi Z, Ansari Ramandi M M, Taghavi S, et al. Clinical and Laboratory Predictors of Mortality in Patients with Advanced Heart Failure (Stage D), Data Derived from Rajaie Acute Systolic Heart Failure (RASHF) Data Registry, Multidiscip Cardio Annal. 2020 ; 11(1):e98039. doi: 10.5812/mca.98039.

ARTICLE INFORMATION

Multidisciplinary Cardiovascular Annals: 11 (1); e98039
Published Online: January 19, 2020
Article Type: Research Article
Received: September 12, 2019
Revised: October 28, 2019
Accepted: December 12, 2019
Crossmark
Crossmark
CHECKING
READ FULL TEXT

Abstract

Background: Mortality, morbidity and the burden of the advanced heart failure and also the cost of frequent admissions is high. Several registries were done all over the world to manage the patients with heart failure; however studies about the advanced stage are limited.

Objectives: The present study aimed to determine the prognostic predictors of patients with advanced heart failure.

Methods: In this study 178 (74.2% male) patients with advanced heart failure (stage D) from 2011 to 2016 were selected according to the following inclusion criteria; highly symptomatic heart failure patients with severe left ventricular (LV) systolic dysfunction (LV ejection fraction less than 30%) who have been admitted for at least two times in the recent year because of decompensation. The data regarding the clinical findings, readmissions, mortality, laboratory tests, electrocardiography, echocardiography, etc. of patients were all derived from Rajaie Acute Systolic Heart Failure (RASHF) data registry.

Results: In a 5-year follow-up, we realized that more than 70% of the patients died. The rate of mortality were significantly higher in females (P value = 0.006) and there was a significant correlation between anemia and the mortality (P value = 0.002). There was no remarkable association between the serum creatinine, sodium and uric acid levels with the mortality of the patients.

Conclusions: Data about stage D of heart failure are limited. The mortality rate for such patients is relatively high and there’s no clear best treatment approach. Large registries and data acquisition of these patients could be helpful for better management approaches.

Copyright © 2020, Multidisciplinary Cardiovascular Annals. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

1. Background

The prevalence of heart failure is increasing and the rate of admission due to decompensated heart failure (DHF) is high. Many studies were done to evaluate the reasons of frequent admissions in these patients. Inappropriate treatment, limited capacity of hospitals for patients to be admitted, and worsening of the patients’ condition were some of the reasons for readmissions due to DHF morbidity of the patients. In addition the cost of treatment is high. Many guidelines have been written for diagnosis and management of patients with DHF. Registry studies are valuable tools to guide diagnosis and management of heart failure (1).

Stage D or advanced heart failure is the end stage of the disease. According to the American Heart Failure society, advanced or stage D heart failure was defined as persistent and/or progressive severe heart failure signs and symptoms despite optimal medical, surgical, and device therapy. Patients in this phase are symptomatic most of the time (NYHA function class IV) and many of them are resistant to the treatments. Fluid retention, arrhythmias, and heart failure complications including renal failure, electrolyte abnormalities, side effects of the drugs and pulmonary thromboembolism are some of the reasons for readmission (2-4).

The estimated proportion of patients with stage D heart failure is about 5 - 10% of all heart failure population (5) and the studies regarding these patients, their clinical characteristics, prognosis and para-clinical evaluations are limited. Heart transplantation, mechanical circulatory devices and chronic palliative therapies such as intermittent inotropic therapy are the main managing programs in these patients (5-7) so identifying the course of disease for referring the patient for these end stage treatments plays the main role in the management of these patients.

The prediction of disease severity and mortality in heart failure patients could be performed by two widely used models, including, Heart Failure Survival Score (HFSS) and Seattle Heart Failure Model (SHFM). HFSS is mainly based on exercise tolerance of patients besides other factors, regarding inability of stage D patients for performing exercise; this model seems to be inappropriate for these patients. In contrast, SHFM seems to be more practical in these circumstances. One of the important aspects of this mortality prediction by these models is considering patients for advance treatments like Left Ventricular Assisted devices (LVAD) or heart transplant. For example, if one and two-year mortality are more than 38% and 61% respectively, LVAD could be considered for patient (8). However, these models have been validated in a specific population like American people, so generalization of these results may be impractical, and this issue implies necessitation of native studies.

2. Objectives

The present study aimed to characterize Iranian people with advanced heart failure and determine the prognostic predictors of these patients.

3. Methods

3.1. Patient Selection

In this study the patients with advanced heart failure (Stage D) who were admitted in our hospital, were selected from January 2012 to October 2016 among patients registered in Rajaie Acute Systolic Heart Failure (RASHF) data registry (9) according to the following inclusion and exclusion criteria:

3.2. Inclusion Criteria

• Age ≥16 years,

• Highly symptomatic patients with severe left ventricle (LV) systolic dysfunction with LV ejection fraction of 30% or less,

• At least two times of admission during the recent year for acute heart failure (AHF).

3.3. Exclusion Criteria

• Hospitalized patients waiting for a long time for heart transplantation.

• The patients who were discharged in less than a day in any index hospitalization.

• The patients who were admitted for other reasons except AHF.

3.4. Data Acquisition

Rajaie Acute Systolic Heart Failure Registry (9), is a prospective study based on the data of hospitalized acute heart failure patients in this center starting from 2012 in Rajaie Cardiovascular, Medical and Research Center (RHC), a tertiary center for cardiovascular medicine and is ongoing.

The data including clinical and past medical history, para-clinical tests (complete blood counts, liver function tests, thyroid function tests, renal function tests, uric acid and electrolytes), electrocardiogram, and echocardiography are collected from patients’ medical records and gathered in a questionnaire and then are recorded in the software designed by the medical Information Technology (IT) team of RHC. The recorded data are controlled by trained general practitioner and an expert cardiologist every day. This study was approved by the Institutional Research and Ethics Committee of RHC and written informed consents were obtained from all participants.

The endpoint of study was mortality and included patients who were followed for 2 years to report any in-hospital or outpatient mortality till October 2018.

The patients with unknown follow-up in our registry system were followed on the phone.

3.5. Statistical Analysis

For statistical analysis IBM SPSS statistics 19 for Windows (IBM Corp, Armonk, NY, USA) was used. Data are presented as frequencies, mean (standard deviation, SD) or median (interquartile range, IQR) as appropriate. One-sample Kolmogorov-Smirnov test was used to assess the normal distribution of variables. Students’ t-test, paired t test or Mann-Whitney U-test and χ2 test or Kruskal-Wallis tests or Wilcoxon signed rank test were used for comparisons and associations as appropriate. Binary multivariable regression analysis with step-wise selection method was used to define the independent predictors. P value of less than 0.05 was regarded as significant.

4. Results

This study is the first registry to evaluate the patients with advanced heart failure in Iran. Out of the 621 medical records in RASHF registry that were evaluated, only 178 patients met our inclusion criteria, from which we only had access to the follow-up of 143 patients (23 patients were not reachable and 12 patients who underwent transplant entered the transplant registry). Table 1 depicts the patient demographic and clinical characteristics at the time of the enrollment. Most patients were male and the most common etiology for heart failure was ischemic heart disease with or without valvular heart disease.

Table 1. The Demographic and Clinical Characteristics of Study Populationa
VariablesValues
Age, y, mean ± SD56.9 ± 18.2
Male gender, No. (%)132 (74.2)
Heart failure duration, years, median (IQR)5 (3 - 7)
Underlying heart disease, No. (%)
Ischemic cardiomyopathy34 (19.1)b
Dilated cardiomyopathy36 (20.2)
Hypertensive cardiomyopathy2 (1.1)
Valvular cardiomyopathy14 (7.9)
Chemotherapy induced cardiomyopathy2 (1,1)
Peri partum cardiomyopathy4 (2.2)
Muscular dystrophy2 (1.1)
History of myocarditis1 (0.6)
Ischemic cardiomyopathy and valvular heart disease80 (44.9)
Hypertension and valvular heart disease3 (1.7)
Morbidities, accompanying conditions, No. (%)
Hypertension71 (39.9)
Diabetes mellitus69 (38.8)
Coronary artery disease105 (59)c
Dyslipidemia66 (37.1)
Smoking56 (31.5)
Drug abuse21 (11,8)
Chronic kidney disease72 (40.4)
Valvular heart diseases132 (74.2)d
Atrial fibrillation44 (24.7)d
Transient ischemic attack14 (7.9)
Peripheral artery disease17 (9.6)
Alcohol abuse2 (1.1)
Devices67 (37.9)

Abbreviations: SD, standard deviation; y, years.

a n = 143.

b P value of 0.008 (in relation to mortality).

c P value of 0.005 (in relation to mortality).

d P value of 0.02 (in relation to mortality).

Table 2 shows some clinical, echocardiographic and laboratory characteristics of study population at the time of the diagnosis of heart failure (stage C) compared to findings at the time of the enrollment (Stage D). The progression of the disease is obvious by comparing these variables. For example, LVEF and right ventricular (RV) function have significantly decreased and the patients have developed symptoms and signs of RV failure, hyponatremia and diminished kidney function.

Table 2. Comparison Between Some Clinical, Echocardiographic and Laboratory Findings at Baseline and Follow-upa
CharacteristicsAt Baseline (Stage C)At Follow-up (Stage D)P Value
LVEF %, mean ± SD19.2 ± 9.414.4 ± 5.6< 0.001
Severe RV dysfunction, No. (%)39 (20.8)79 (43.3)< 0.001
Symptoms and signs of RV failure, No. (%)43 (23)81 (44.4)< 0.001
Serum sodium level, mg/dL, median (IQR)136 (133 - 140)136 (132 - 139)b0.02
Serum Uric acid level, mg/dL, median (IQR)8 (7 - 9)8 (6 - 10)0.1
Serum BUN, mg/dL, median (IQR)19 (16 - 21)21 (16 - 31)0.006
Serum creatinine, mg/dL, median (IQR)0.9 (0.8 - 1.1)1 (0.8 - 1.2)0.003

Abbreviations: BUN; blood urea nitrogen , EF, ejection fraction; RV, right ventricular; SD, standard deviation.

a n = 143.

b P value of 0.07 (in relation to mortality).

Table 3 shows the medications of the study population at enrollment. As shown in table 3 most of the patients received guideline directed medical therapies (GDMT).

Table 3. Heart Failure Medications of Study Populationa
VariablesNo. (%)
Furosemide169 (94.9)
Metolazone59 (33.1)
Beta blockers148 (84.6)
Angiotensin-converting enzyme inhibitors111 (63.4)
Angiotensin receptor blockers24 (13.7)
Mineralocorticoid receptor antagonists134 (76.6)
Digoxin48 (27.4)
Calcium channel blockers7 (4)
Hydralazine67 (38.3)
Isosorbide dinitrate40 (22.9)
Aspirin69 (39.4)
Clopidogrel17 (9.7)
Warfarin66 (37.7)
Antiarrhythmic drugs22 (12.6)
Ivabradine6 (3.4)
Statins47 (26.9)
GDMT168 (96)
Intermittent inotrope therapy36 (20.6)b
Combined diuretic therapy39 (22.3)
Intermittent diuretic therapy155 (88.6)

Abbreviation: GDMT, guideline directed medical therapy.

a n = 143.

b P value of 0.04 (in relation to mortality).

Regarding the palliative care of advanced heart failure 89%, 21% and 22% of patients were on intermittent intravenous diuretic therapy, intermittent inotrope therapy and combined diuretic therapy respectively

4.1. The Study Outcome and Its Correlates

The total mortality was 100 patients (69.9%) at the end of the study. Figure 1 shows the Kaplan Meier curve of survival analysis in our study population. As shown in this curve, about 50% of patients died after 5 years of diagnosis of their heart failure.

Kaplan Meier curve of survival analysis in study population, n=143
Figure 1. Kaplan Meier curve of survival analysis in study population, n=143

Among the study variables, presence of ischemic etiology for heart failure, valvular heart disease, wide QRS, atrial fibrillation, anemia and history of intermittent inotrope therapy were significantly correlated with mortality in univariate analysis (as shown in tables 1-3 all P values were < 0.005).

Binary logistic regression multivariate analysis showed that female gender, anemia and ischemic cardiomyopathy as underlying heart disease have a significant relationship with mortality (Table 4).

Table 4. Independent Predictors of Mortality in Advanced Heart Failure
VariablesBetaP ValueOdd Ratio (95% CI)
History of valvular heart disease-1.2320.10.292 (0.07 - 1.3)
Ischemic cardiomyopathy-1.2370.050.290 (0.08 - 1)
Anemia-2.0260.0040.132 (0.03 - 0.5)
History of intermittent inotrope therapy-1.4680.1230.230 (0.04 - 1.5)

5. Discussion

The present study showed the clinical characteristics and predictors of death in patients with stage D heart failure in Iranian population. Definition of stage D heart failure is somewhat challenging and investigators have different opinions regarding the best tool for defining these patients. For example, in Hedley et al. study, the Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) profile was superior than the European heart failure association criteria in distinguishing stage D heart failure patients in ambulatory heart failure patients with reduced ejection fraction (10). In another study the physician judgment was stronger than existing criteria for defining the prognosis in stage D heart failure (11).

The importance of stage D definition is due to distinct management of these patients in statement of guidelines. According to the American heart failure society, advanced or stage D heart failure was defined as persistent and/or progressive severe heart failure signs and symptoms despite optimal medical, surgical, and device therapy (4, 10, 11).

Transition to stage D or advanced heart failure is the time when the patient is considered for advance heart failure therapies like heart transplant, mechanical circulatory support (MCS) devices or frequent inotrope therapy (3). The MCS are not only important for supportive care in end stage heart failure but also it has been shown that, with optimal guideline directed medical therapy along with the LVAD, some patients could experience remission from stage D (12-14). As MCS devices are not readily available for all patients in our country, we decided to investigate the clinical and para-clinical variables in patients who were on medical and palliative therapies for advanced heart failure such as intermittent intravenous diuretic and inotrope therapy and show the natural history of these patients from the beginning of their heart failure to death. For this purpose, we also excluded the patients who were transplanted or waiting to be admitted for heart transplantation.

It has been shown that heart failure classification from A to D has perceptual, bio-hormonal and prognostic importance (15).

In this study, we could show, besides significant reduction in LVEF, many patients developed signs and symptoms of RV failure and significant deterioration in their renal function and electrolyte balance as indicated in Kalogeropoulos et al. study (3). They showed that variables such as non-ischemic cardiomyopathy, lower initial systolic pressure and LVEF, liver or renal dysfunction, presence of chronic lung disease and blood urea nitrogen may be correlated with early progression to stage D.

Although the proportion of stage D heart failure patients has not been well determined but the estimated rate is 5 to 10% (5).

Patients’ characteristics of this stage have been evaluated in some studies. In Acute Decompensated Heart Failure National Registry Longitudinal Module (ADHERE LM), stage D patients were younger, majority of them were male and had a history of coronary artery disease (CAD), chronic kidney disease (CKD) and dyslipidemia (2). In our study, majority of patients were male (74.2%) and had a history of CAD (59%). The prevalence of CKD was high (40.4%) and the prevalence of other known comorbidities such as hypertension (39.9%), diabetes mellitus (38.8%) and dyslipidemia (37.1%), were also prominent.

Some laboratory findings have been shown to have predictive values in stage D heart failure, elevated levels of brain natriuretic peptide (BNP) at admission or follow-up, hyponatremia and elevated blood urea nitrogen (BUN) level are among them (16-19).

In the present study, although there were significant changes in BUN, serum sodium level and ventricular function from baseline to the end of the follow-up, these variables were not correlated with mortality in uni- and multi-variable analyses. The significant predictors of mortality in univariate analyses were the presence of ischemic etiology for heart failure, valvular heart disease, wide QRS, atrial fibrillation, anemia and history of intermittent inotrope therapy, whereas multivariable analysis showed female gender, anemia and ischemic cardiomyopathy may be the independent predictors of death in this group of patients.

The estimated median life expectancy of patients in stage D is about 6 to 12 months, in this phase palliative care for these patients is another issue particularly for patients who are not eligible for mechanical assist devices or heart transplant (6).

Previous mega trials on heart failure patients with New York Heart association (NYHA) function class IV, like Cooperative North Scandinavian Enalapril Survival Study( CONSENSUS), randomized Aldactone evaluation study (RALES), Beta Blocker Evaluation in Survival Trial (BEST), Carvedilol Prospective Randomized Cumulative Survival (COPERNICUS), Randomized Evaluation of Mechanical Assistance for the Treatment of Congestive Heart Failure (REMATCH) and Comparison of Medical Therapy, Pacing and Defibrillation in Heart Failure (COMPANION), showed high one-year mortality , ranging from 11.4% to 45%, even in the intervention groups (8).

Survival rate of inotrope dependent patients was approximately 10% at 1 year in INTREPID trail (20). In Olmstead county study, stage D heart failure patients had 20% 5-year survival (15).

In our study, 5-year survival rates of patients were less than 50%. These differences in survival rates of stage D patients may be due to various stages in these patients that lead to various survival rates. It might be more practical that stage D patients be divided to more categories based on their clinical, laboratory and other useful findings for precise estimation of their outcomes.

In this regard, some risk prediction models have been designed for survival estimation such as SHFM (Seattle Heart Failure Model), HFSS (Heart Failure Survival Score) which uses peak VO2 in addition to other clinical parameters, ESCAPE risk model and also risk model derived from EFFECT study (21-24).

Prognosis estimation models like SHFM (Seattle Heart Failure Model) are unable to predict exact prognosis of stage D patients, because these patients were not included in most data deriving studies for designing these models and as a result these models underestimate actual prognosis of these patients.

5.1. Study Limitation

Although the uniform nature or study population would be the strength of this study, we could not have the data regarding the pro-BNP level which is one of the most important variables in heart failure studies in our study. The reason was the presence of numerous missing data regarding the pro BNP test results in our documents which was due to unavailability of this test before 2015 in our center.

5.2. Conclusions

Data about stage D heart failure patients are limited. The mortality rate for such patients is relatively high and there’s no clear best treatment approach. Large registries and data acquisition of these patients could be helpful in better management approaches.

Footnotes

References

  • 1.

    Crespo-Leiro MG, Anker SD, Maggioni AP, Coats AJ, Filippatos G, Ruschitzka F, et al. European Society of Cardiology Heart Failure Long-Term Registry (ESC-HF-LT): 1-year follow-up outcomes and differences across regions. Eur J Heart Fail. 2016;18(6):613-25. doi: 10.1002/ejhf.566. [PubMed: 27324686].

  • 2.

    Costanzo MR, Mills RM, Wynne J. Characteristics of "Stage D" heart failure: Insights from the Acute Decompensated Heart Failure National Registry Longitudinal Module (ADHERE LM). Am Heart J. 2008;155(2):339-47. doi: 10.1016/j.ahj.2007.10.020. [PubMed: 18215606].

  • 3.

    Kalogeropoulos AP, Samman-Tahhan A, Hedley JS, McCue AA, Bjork JB, Markham DW, et al. Progression to stage D heart failure among outpatients with stage C heart failure and reduced ejection fraction. JACC Heart Fail. 2017;5(7):528-37. doi: 10.1016/j.jchf.2017.02.020. [PubMed: 28624484].

  • 4.

    Fang JC, Ewald GA, Allen LA, Butler J, Westlake Canary CA, Colvin-Adams M, et al. Advanced (stage D) heart failure: A statement from the Heart Failure Society of America Guidelines Committee. J Card Fail. 2015;21(6):519-34. doi: 10.1016/j.cardfail.2015.04.013. [PubMed: 25953697].

  • 5.

    Whellan DJ, Goodlin SJ, Dickinson MG, Heidenreich PA, Jaenicke C, Stough WG, et al. End-of-life care in patients with heart failure. J Card Fail. 2014;20(2):121-34. doi: 10.1016/j.cardfail.2013.12.003. [PubMed: 24556532].

  • 6.

    Maciver J, Ross HJ. A palliative approach for heart failure end-of-life care. Curr Opin Cardiol. 2018;33(2):202-7. doi: 10.1097/HCO.0000000000000484. [PubMed: 29135524]. [PubMed Central: PMC5811237].

  • 7.

    La Franca E, Iacona R, Ajello L, Sansone A, Caruso M, Assennato P. Heart failure and mechanical circulatory assist devices. Glob J Health Sci. 2013;5(5):11-9. doi: 10.5539/gjhs.v5n5p11. [PubMed: 23985102]. [PubMed Central: PMC4776846].

  • 8.

    Kinugawa K. How to treat stage D heart failure? - When to implant left ventricular assist devices in the era of continuous flow pumps? Circ J. 2011;75(9):2038-45. doi: 10.1253/circj.cj-11-0621. [PubMed: 21817817].

  • 9.

    Soltani MH, Alemzadeh-Ansari MJ, Taghavi S, Ghadrdoost B, Maleki M, Amin A, et al. Worsening renal function in acute decompensated systolic heart failure; observations from RASHF registry, an Iranian heart failure registry. Int Cardiovasc Res J. 2017;11(1):18-24.

  • 10.

    Hedley JS, Samman-Tahhan A, McCue AA, Bjork JB, Butler J, Georgiopoulou VV, et al. Definitions of Stage D heart failure and outcomes among outpatients with heart failure and reduced ejection fraction. Int J Cardiol. 2018;272:250-4. doi: 10.1016/j.ijcard.2018.08.046. [PubMed: 30122504].

  • 11.

    Yazdani M, Hedley JS, Tahhan AS, McCue AA, Al-Anbari R, Morris AA, et al. Identification of stage D heart failure patients: Clinical assessment versus ESC Heart Failure Association criteria. J Card Fail. 2015;21(8). S8. doi: 10.1016/j.cardfail.2015.06.063.

  • 12.

    Ghotra A, Hussain Z, Spayd S, Cheng A, Lenneman A, Slaughter M, et al. Explantation of left ventricular assist devices after myocardial recovery: A single center study. J Heart Lung Transplant. 2015;34(4). S41. doi: 10.1016/j.healun.2015.01.098.

  • 13.

    Pan S, Wever-Pinzon O, Rao S, Levin A, Garan A, Takeda K, et al. Myocardial recovery from short- and long-term cardiac support devices: Results from the UNOS registry. J Heart Lung Transplant. 2015;34(4). S41. doi: 10.1016/j.healun.2015.01.097.

  • 14.

    Baldwin AC, Sandoval E, Singh SK, Cohn WE, Mallidi HR, Frazier O. Ventricular reconditioning enables de-escalation of therapy in young patients supported by continuous flow left ventricular assist devices. J Heart Lung Transplant. 2015;34(4):S41-2. doi: 10.1016/j.healun.2015.01.099.

  • 15.

    Ammar KA, Jacobsen SJ, Mahoney DW, Kors JA, Redfield MM, Burnett JC, Jr, et al. Prevalence and prognostic significance of heart failure stages: Application of the American College of Cardiology/American Heart Association heart failure staging criteria in the community. Circulation. 2007;115(12):1563-70. doi: 10.1161/CIRCULATIONAHA.106.666818. [PubMed: 17353436].

  • 16.

    Fonarow GC, Peacock WF, Phillips CO, Givertz MM, Lopatin M; Adhere Scientific Advisory Committee, et al. Admission B-type natriuretic peptide levels and in-hospital mortality in acute decompensated heart failure. J Am Coll Cardiol. 2007;49(19):1943-50. doi: 10.1016/j.jacc.2007.02.037. [PubMed: 17498579].

  • 17.

    Velibey Y, Golcuk Y, Golcuk B, Oray D, Atilla OD, Colak A, et al. Determination of a predictive cutoff value of NT-proBNP testing for long-term survival in ED patients with acute heart failure. Am J Emerg Med. 2013;31(12):1634-7. doi: 10.1016/j.ajem.2013.08.033. [PubMed: 24055249].

  • 18.

    Gheorghiade M, Rossi JS, Cotts W, Shin DD, Hellkamp AS, Pina IL, et al. Characterization and prognostic value of persistent hyponatremia in patients with severe heart failure in the ESCAPE Trial. Arch Intern Med. 2007;167(18):1998-2005. doi: 10.1001/archinte.167.18.1998. [PubMed: 17923601].

  • 19.

    Singh G, Peterson EL, Wells K, Williams LK, Lanfear DE. Comparison of renal predictors for in-hospital and postdischarge mortality after hospitalized heart failure. J Cardiovasc Med (Hagerstown). 2012;13(4):246-53. doi: 10.2459/JCM.0b013e3283516767. [PubMed: 22343264]. [PubMed Central: PMC3725607].

  • 20.

    Rogers JG, Butler J, Lansman SL, Gass A, Portner PM, Pasque MK, et al. Chronic mechanical circulatory support for inotrope-dependent heart failure patients who are not transplant candidates: results of the INTrEPID Trial. J Am Coll Cardiol. 2007;50(8):741-7. doi: 10.1016/j.jacc.2007.03.063. [PubMed: 17707178].

  • 21.

    Goda A, Lund LH, Mancini D. The heart failure survival score outperforms the peak oxygen consumption for heart transplantation selection in the era of device therapy. J Heart Lung Transplant. 2011;30(3):315-25. doi: 10.1016/j.healun.2010.09.007. [PubMed: 21093299].

  • 22.

    Goda A, Williams P, Mancini D, Lund LH. Selecting patients for heart transplantation: comparison of the Heart Failure Survival Score (HFSS) and the Seattle heart failure model (SHFM). J Heart Lung Transplant. 2011;30(11):1236-43. doi: 10.1016/j.healun.2011.05.012. [PubMed: 21764604].

  • 23.

    O'Connor CM, Hasselblad V, Mehta RH, Tasissa G, Califf RM, Fiuzat M, et al. Triage after hospitalization with advanced heart failure: The ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) risk model and discharge score. J Am Coll Cardiol. 2010;55(9):872-8. doi: 10.1016/j.jacc.2009.08.083. [PubMed: 20185037]. [PubMed Central: PMC3835158].

  • 24.

    Lee DS, Austin PC, Rouleau JL, Liu PP, Naimark D, Tu JV. Predicting mortality among patients hospitalized for heart failure: Derivation and validation of a clinical model. JAMA. 2003;290(19):2581-7. doi: 10.1001/jama.290.19.2581. [PubMed: 14625335].

  • COMMENTS

    LEAVE A COMMENT HERE: