Prognosis

The natural history of heart failure shows a general decline in function and quality of life, marked by ‘troughs’ representing decompensation into acute exacerbations of heart failure (Figure 9). It should be noted that a sudden decompensation due to a new insult is possible at any point in established heart failure, however the general pattern is that following an episode of acute decompensation, some function will be regained. Over time, these exacerbations are likely to become more frequent and cause more severe symptoms, as the baseline becomes lower (Figure 9) (Allen et al., 2012; Chaudhry & Stewart, 2016). 

Natural history of heart failure.

Figure 9. Natural history of heart failure (adapted from Allen et al., 2012).
CHF, chronic heart failure; MCS, mechanical circulatory support.

The New York Heart Association (NYHA) has a classification system for the stages of heart failure which is discussed in more detail in the diagnosis of advanced heart failure section. Although it was created in 1928, it remains one of the most important functional scores in the ‘staging’ of heart failure.

In general, the prognosis of an individual is difficult to estimate due to the variable nature of heart failure. Allen et al., (2012) suggest that over 100 variables have been found to be independently associated with mortality and admission to hospital. The most important of these include:

  • demographic information: age, sex, ethnic background
  • functional status
  • exercise capacity
  • cardiac structure and function
  • assessments of filling pressures
  • biomarkers
  • comorbid disease
  • renal and liver dysfunction
  • clinical events
  • psychological factors
  • social factors.

Scoring systems have been established, looking both at outpatient prognosis and outcomes following admission for acute decompensation (Allen et al., 2011).

As there is such a variable course and prognosis, it is difficult to apply generalities to the individual patient. However, heart failure in general terms has a worse prognosis than most forms of cancer, with 5-year mortality following diagnosis consistently over 75% (Avellino et al., 2011; McMurray & Stewart, 2000). A study published in 2011 found some improvement in outcomes following admission with heart failure between 1995 and 2000, but still noted that of 2,587 patients admitted in 2000, the 3-month, 1-year and 5-year mortality rates were 18.8%, 39.7%, and 82.9% respectively (Park et al., 2011). Other, older studies have had similar findings; the Rochester Epidemiology Project found the 1-year and 5-year mortality rates were 23% and 67% in a relatively small population of 141 patients. A larger prospective study (n = 14,407) evaluated non-hospitalised people who self-reported symptoms, finding a 10-year mortality of 42.8% in the general population, much lower than other studies based on diagnosis following hospital admission; the 10-year mortality in subjects aged 65–74 was more reflective of previously established statistics with a mortality of 65.4% (Allen et al., 2011). Meanwhile, data from the Atherosclerosis Risk in Communities (ARIC) Study Heart Failure Community Surveillance observed a one-year mortality rate of 34% in patients with acute decompensated heart failure with preserved ejection fraction. Predictors of mortality included a higher heart rate, being underweight (BMI <18.5) and higher natriuretic peptide levels (Thorvaldsen et al., 2017).

The clinical category that a patient presents with may also influence the patient’s outcomes. The 1-year mortality rate differed substantially between classifications (Chioncel et al., 2017):

Table 1. 1-year mortality rate associated with different acute heart failure classification categories (Chioncel et al., 2017).

Classification category

Percentage of patients in classification category

1-year mortality rate

Decompensated heart failure

61.1%

27.2%

Associated acute coronary syndromes

14.4%

20.6%

Pulmonary oedema

13.2%

28.1%

Hypertensive heart failure

4.8%

12.8%

Right heart failure

3.5%

34.0%

Cardiogenic shock

2.9%

54.0%

A recent small-scale study sought to determine what other factors were predictive of mortality in patients admitted with acute heart failure. Of the 322 patients investigated, they noted three characteristics that were the most indicative of mortality rate – age >85 years (OR=1.5; 95% CI 0.8–2.7; p=0.01), creatinine clearance <30 mL/min (OR=2.6; 95% CI 1.5–5.0; p<0.001) and Nt-proBNP (N-terminal pro- B-type natriuretic peptide) >5000 pg/mL (OR=2.2; 95% CI 1.2–4.0; p<0.001) (Marchetti et al., 2017). A similar study in 287 patients with acute heart failure identified Nt-proBNP, serum sodium and soluble ST2 as potential predictors of 1-year mortality (Jin et al., 2017). Further evidence for the predictive value of low urinary sodium concentrations (UNa) has been observed in 669 Japanese patients with acute heart failure. In this prospective registry study, patients with lower UNa at admission were more likely to have a history of prior heart failure admission, β-blockers and diuretics use, and lower blood pressure and serum sodium levels but higher blood urea nitrogen, estimated glomerular filtration rate, blood glucose and troponin T levels than patients with higher UNa. Furthermore, lower UNa was associated with worse long-term outcomes including significantly higher incidence of worsening renal function (Honda et al., 2018). Meanwhile, hyperkalaemia may also be an indicator for increased 90-day mortality with β-blockers potentially having a protective effect in these patients (Legrand et al., 2018).

Interestingly, malnutrition is common among patients hospitalised for acute heart failure and in a study of 145 patients, ProBNP levels directly correlated with nutritional status. In this patient population, malnutrition was observed to be a mediator of disease progression and offers a poor prognosis (Agra Bermejo et al., 2017).

A study examining 15,828 patients with acute heart failure determined that the precipitating factor also plays a role in determining 90-day mortality, and more than half (8,784) had an identifiable precipitating cause. Investigators suspected that part of the reason behind persistently high mortality in acute heart failure is that the condition is clinically heterogeneous. To that end they tested whether the precipitating pathology independently predicted 90-day mortality. They determined that acute heart failure precipitated by acute coronary syndrome (ACS) or infection was associated with a higher mortality versus those with undetermined precipitating factors (ACS: HR=1.69; 95% CI 1.44–1.97; p<0.001, infection: HR=1.51; 95% CI 1.18–1.92; p<0.001). Heart failure precipitated by atrial fibrillation (AF) and uncontrolled hypertension was associated with a significantly lower 90-day mortality (hypertension: HR=0.72; 95% CI 0.60–0.86, AF: HR=0.56; 95% CI 0.42–0.75) (Figure 10) (Arrigo et al., 2017). While this is perhaps an unsurprising finding, it does emphasise the importance of not viewing heart failure as a single clinical entity.

A graph showing ninety-day survival depending on the identified precipitating factors of acute heart failure.

Figure 10. Ninety-day survival depending on the identified precipitating factors of acute heart failure (adapted from Arrigo et al., 2017).

Similarly, the presence of functional mitral regurgitation (FMR) in patients with acute heart failure and reduced left ventricular ejection fraction has been assessed as a predictor of adverse outcomes. In a prospective study of 938 consecutive patients, FMR was assessed at 120 ± 24 hours post-admission with 56.8% having none or mild (grade 0 or 1), 26.9% having moderate (grade 2) and 16.2% having severe (grade 3 or 4) FMR. After multivariable adjustment, patients with moderate or severe FMR had a significantly increased risk of short-term adverse clinical outcomes (De la Espriella et al., 2017).

In patients with acute heart failure, an inverse relationship has been described between frequency of cardiovascular events and BMI. In 808 acute heart failure patients, it was recently shown that severely thin (BMI <16 kg/m2) patients were more likely to have valvular disease and be at an increased risk of 910-day mortality (HR=3.372, 95% CI 1.362–8.351) than normal/underweight (BMI ≥16–<25 kg/m2) patients. Meanwhile, overweight patients (BMI ≥25–<30 kg/m2) were younger and more likely to have hypertensive heart disease than the normal/underweight group. They also had a significantly better prognosis than severely thin, normal/underweight and obese (BMI ≥30 kg/m2) patients with a 910-day mortality HR of 0.615 (95% CI 0.391–0.966) patients that were of normal weight or underweight (Matsushita et al., 2017). A recent study explored whether this effect persisted in patients with co-morbid type-II diabetes. A multicentre observational study was carried out, examining 2,492 patients with acute heart failure and type-II diabetes – they found that underweight patients (BMI <20.0 kg/m2) had a higher 3-month mortality risk (OR=2.04; 95% CI 1.02–4.08), while obese patients (BMI 30.0–34.9 kg/m2) had a lower mortality over the same time period (OR=0.53; 95% CI 0.34–0.83). There was no significant effect for those of normal and overweight patients (Abi Khalil et al., 2017).

While several studies have investigated factors that are predictive of mortality, a small study of 71 hospitalised acute heart failure patients recently demonstrated that assessing six-minute walking distance prior to discharge could predict 30-day readmission. It was shown that for every additional 100 feet (30.48 meters) walked, the odds of readmission within 30 days were reduced by 16% (McCabe et al., 2017). 

An important distinction to be aware of is the need to manage any intervention against the corresponding expected change in quality of life. This is discussed in greater detail in the advanced heart failure prognosis and quality of life section.