Tom Wade MD

Today, I review, link to, and embed Palliative Care Of Wisconsin‘s “Prognostication in Heart Failure“.

All that follows is from the above resource.

Fast Fact Number: 143

By: Gary M Reisfield MD, George R Wilson MD

Categories: Age Friendly Care: The 4 Ms of Geriatric Care, Cardiovascular, Fast Facts By Specialty, Prognostication, What Matters

Published On: February 2, 2026

Background     This Fast Fact reviews prognostication data in Heart Failure (HF).  Although the 5-year mortality rate for newly identified cases of HF cases is around 40%, providing accurate prognostic data for 6-12 month mortality in HF has been challenging.  Reasons cited include: 1) an unpredictable disease trajectory with high incidence (25-50%) of sudden death; 2) disparities in the application of evidence-based treatment guidelines; 3) inter-observer differences in New York Heart Association (NYHA) classification; 4) heterogeneous study populations; 5) improvements in HF therapies including the wider adoption of advanced therapies like heart transplantation and ventricular assist devices.

NYHA Classification    The NYHA classification remains the major gauge of disease severity.   

• Class I (asymptomatic):  1-year mortality 5%; 4-year mortality 19%.
• Class II or III (symptoms with exertion):  1-year mortality 15%; 4-year mortality 40%.
• Class IV (inability to carry out any physical activity):  6-month mortality 44%; 1-year mortality 64%.

General predictors of a shorter prognosis: 

• Cardiac hospitalization (triples 1-year mortality; nearly 1 in 10 die within 30 days of admission).
• Intolerance to neurohormonal therapy (i.e. beta-blockers or ACE-inhibitors).
• Elevated BUN (defined by upper limit of normal) and/or creatinine ≥1.4 mg/dl (120 μmol/l).
• Systolic blood pressure <100 mm Hg and/or pulse >100 bpm (each doubles 1-year mortality).
• Decreased left ventricular ejection fraction (linearly correlated with survival at LVEF ≤ 45%).
• Elevated plasma levels of B-type natriuretic peptide (BNP).
• Concomitant right ventricular dysfunction, ventricular tachycardia, left bundle branch block, QRS prolongation, or diastolic dysfunction.
• Cachexia, reduced functional capacity, or orthopnea.
• Low albumin, hyponatremia, elevated CRP, and anemia.
• HF caused by infiltrative myocardial disease like amyloidosis or hemochromatosis.
• Age – patients >65 have an independently increased 1-year mortality risk.
• Co-morbidities: diabetes, depression, cirrhosis, COPD, cerebrovascular disease, and cancer.

Hospice eligibility guidelines     The National Hospice and Palliative Care Organization’s guidelines for HF admission essentially are symptoms of recurrent HF at rest (NYHA class IV) despite optimal medical management. Other supporting evidence for hospice eligibility include: 

• Multiple hospitalizations in the last 6 months.
• Low ejection fraction (e.g., 20% or less).
• History of sentinel events – arrhythmias, cardiac arrest, persistent hypotension, syncope.
• Documented clinical deterioration (e.g., declining functional status, persistent fatigue).
• Significant comorbidities.

Prognostic models     Several models have been developed for predicting short- and/or long-term mortality among HF patients, however, their clinical role and effectiveness is not entirely clear.   

• EFFECT model – designed and validated in patients who are hospitalized for acute HF, it provides a 30-day mortality risk based on risk categories derived from HF-related factors like respiratory rate, systolic blood pressure, BUN, and sodium levels along with comorbidities.
• Heart Failure Survival Score – designed and validated for patients with NYHA class 3 or 4, it provides 1-year survival probability if heart transplant is not pursued.  It predominantly utilizes the following factors – presence of coronary artery disease, heart rate at rest, left ventricular ejection fraction, blood pressure, sodium levels, peak oxygen consumption levels, ECG findings.
• Seattle Heart Failure Model – derived and validate from data investigation both outpatients with advanced HF and earlier stages of HF.  The model utilizes a variety of factors in an online calculator that can also estimate the effect of adding new therapies on survival. 
• PREDICT-HFpEF – designed for patients with a preserved ejection fraction, it uses commonly assessed clinical variables (e.g., BNP, creatinine, duration of HF, comorbidities) to predict mortality risk at 1 and 2 years.

Bottom line    Meticulous application of medication and device therapies can and will change HF prognosis. HF follows an unpredictable disease trajectory, one which is highly mutable by application of evidence-based therapies yet still marked by a high incidence of sudden death.  Several models have recently been developed to aid in determining short- and long-term mortality in HF patients.  These models await further independent, prospective and will need periodic updating to control for continually evolving standards of HF care. In the meantime, generalist should closely collaborate with cardiologists and Heart Failure specialists when trying to most accurately formulate prognosis.

References 

1. Jones NR, Roalfe AK, Adoki I, et al.  Survival of patients with chronic heart failure in the community: a systematic review and meta-analysis. Eur J Heart Failu 2019; 21(11):1306-1325.
2. Chaudhry S-P, Stewart GC.  Advanced heart failure: prevalence, natural history, and prognosis. Heart Failure Clinics. 2016; 12(3):323-33.
3. Anand I, McMurray JJV, Whitmore J. Anemia and its relationship to clinical outcome in heart failure. Circulation. 2004; 110:149-154.
4. Anker SD, Ponikowski P, Varney S, et al. Wasting as an independent risk factor for mortality in chronic heart failure. Lancet. 1997; 349:1050-1053.
5. Curtis JP, Sokol SI, Wang Y, et al. The association of left ventricular ejection fraction, mortality, and cause of death in stable outpatients with heart failure. J Am Coll Cardiol. 2003; 42(4):736-742.
6. Fonarow GC, Adams KF, Abraham WT, et al. Risk stratification for in-hospital mortality in acutely decompensated heart failure.  JAMA. 2005;2 93(5):572-580.
7. Horwich TB, Fonarow GC, Hamilton MA, et al. Anemia is associated with worse symptoms, greater impairment in functional capacity and a significant increase in mortality in patients with advanced heart failure. J Am Coll Cardiol. 2002; 39(11):1780-1786.
8. Kearney MT, Fox KAA, Lee AJ. Predicting death due to progressive heart failure in patients with mild-to-moderate chronic heart failure. J Am Coll Cardiol. 2002; 40(10):1801-1808.
9. Wang NC, Maggioni AP, Konstam MA, et al. Clinical implications of QRS duration in patients hospitalized with worsening heart failure and reduced left ventricular ejection fraction. JAMA 2008; 299:2656.
10. Lee DS, Austin PC, Rouleau JL, et al. Predicting mortality among patients hospitalized for heart failure.  JAMA. 2003; 290(19):2581-2587.
11. Levenson JW, McCarthy EP, Lynn J, et al. The last six months of life for patients with congestive heart failure. J Am Geriatr Soc. 2000; 48(Suppl 5):S101-S109.
12. Levy D, Kenchaiah S, Larson MG, et al. Long-term trends in the incidence of and survival with heart failure. NEJM. 2002; 347(18):1397-1402.
13. Levy WC, Mozaffarian D, Linker DT, et al. The Seattle Heart Failure Model. Prediction of Survival in Heart Failure. Circulation. 2006; 113:1424-1433.
14. Muntwyler J, Abetel G, Gruner C, et al. One-year mortality among unselected outpatients with heart failure. Eur Heart J. 2002; 23:1861-1866.
15. Warraich HJ, Xu H, DeVoreAD, et al.  Trends in hospice discharge and relative outcomes among Medicare patients in the get with the guidelines-heart failure registry. JAMA Cardiology 2018; 3(10):917-926.
16. Thorvaldsen T, Claggett BL, Shah A, et al.  Predicting risk in patients hospitalized for acute decompensated heart failure and preserved ejection fraction: the atherosclerosis risk in communities study heart failure community surveillance. Circ Heart Fail 2017; 10(12):e003992.
17. McDowell K, Kondo T, Talebi A, et al.  Prognostic models for mortality and morbidity in heart failure with preserved ejection fraction. JAMA Cardiol 2025.
18. Zannad F, Briancon S, Julliere Y. Incidence, clinical and etiologic features, and outcomes of advanced chronic heart failure: the EPICAL study. J Am Coll Cardiol. 1999; 33(3):734-742.
19. Desai AS, Stevenson LW. There must be a better way: piloting alternate routes around heart failure hospitalizations.  J of Am Coll of Card. 2013; 61(2):127-30.

Version History:  This Fast Fact was originally edited by David E Weissman MD and published in October 2005. It was updated in December 2006; reviewed and updated again in April 2009; then revised again July 2015 by Sean Marks MD; and again in February 2026.
Conflicts of Interest: None to report.

Fast Facts and Concepts are edited by Sean Marks MD (Medical College of Wisconsin) and associate editor Drew A Rosielle MD (University of Minnesota Medical School) with the generous support of a volunteer peer-review editorial board, and are made available online by the Palliative Care Network of Wisconsin (PCNOW). The authors of each individual Fast Fact and the Fast Fact and Concepts editors are solely responsible for that Fast Fact’s content. The full set of Fast Facts are available at Palliative Care Network of Wisconsin with contact information, and how to reference Fast Facts.

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