Free Heart Failure Life Expectancy Calculator

The Congestive Heart Failure Life Expectancy Calculator is a validated prediction tool that estimates 1‑year and 3‑year survival probabilities for individuals diagnosed with heart failure. It is rooted in the MAGGIC risk score developed by Pocock et al., which aggregates data from multiple international cohorts. This model incorporates demographic, clinical, and therapeutic variables to produce a personalized risk estimate. It is intended to support, not supersede, clinical judgment. Any health concerns should be evaluated by a qualified physician.

Required Input Variables

To compute the MAGGIC score, the following parameters are needed:

• Patient demographics: sex, age (years), height (cm/in), weight (kg/lb) — BMI (kg/m²) is derived automatically.
• Laboratory and physiologic measurements: serum creatinine (µmol/L or mg/dL), left ventricular ejection fraction (EF, %), and systolic blood pressure (sBP, mmHg).
• Medication history: current use of ACE inhibitors or angiotensin II receptor blockers (ACEi/ARB) and beta‑blockers.
• Heart failure history: whether the diagnosis was made 18 months or more ago.
• Symptom severity: NYHA functional class (I through IV).
• Comorbidities and lifestyle: presence of chronic obstructive pulmonary disease (COPD), current smoking status, and diabetes mellitus.

Each of these factors contributes a point value that is summed to obtain the total MAGGIC risk score.

Point Assignment Tables

The following tables list the points for each variable. The total score is the sum of all applicable points.

Demographics and Medical History

Variable	Condition	Points
Sex	Male	+1
	Female	0
ACEi/ARB use	Yes	0
	No	+1
Beta‑blocker use	Yes	0
	No	+3
HF history ≥18 months	Yes	+2
	No	0
NYHA class	I	0
	II	+2
	III	+6
	IV	+8
COPD	Yes	+2
	No	0
Current smoker	Yes	+1
	No	0
Diabetes	Yes	+3
	No	0

Age (points depend on ejection fraction)

Age (years)	EF <30%	EF 30–39%	EF ≥40%
<55	0	0	0
55–59	+1	+2	+3
60–64	+2	+4	+5
65–69	+4	+6	+7
70–74	+6	+8	+9
75–79	+8	+10	+12
≥80	+10	+13	+15

Body Mass Index

BMI (kg/m²)	Points
<15	+6
15–19	+5
20–24	+3
25–29	+2
≥30	0

Creatinine

Creatinine (µmol/L)	Points
<90	0
90–109	+1
110–129	+2
130–149	+3
150–169	+4
170–209	+5
210–249	+6
≥250	+8

Ejection Fraction

EF (%)	Points
<20	+7
20–24	+6
25–29	+5
30–34	+3
35–39	+2
≥40	0

Systolic Blood Pressure (points depend on EF)

sBP (mmHg)	EF <30%	EF 30–39%	EF ≥40%
<110	+5	+3	+2
110–119	+4	+2	+1
120–129	+3	+1	+1
130–139	+2	+1	0
140–149	+1	0	0
≥150	0	0	0

Interpreting the Results

The calculator outputs three metrics:

• Total MAGGIC risk score (sum of all points).
• 1‑year survival probability.
• 3‑year survival probability.

Higher scores indicate a worse prognosis. For reference, the general heart failure population has reported survival rates of approximately $81.3\%$ at 1 year, $51.5\%$ at 5 years, and $29.5\%$ at 10 years. This means that, over a 5‑year horizon, roughly half of CHF patients will survive. Heart transplantation, where appropriate, can substantially extend survival; data show that about $21\%$ of transplant recipients are still alive after 20 years.

Clinical Stages of Heart Failure

The ACC/AHA stages offer a complementary framework for understanding disease progression:

Stage	Description	Examples
A	High risk for heart failure without structural disease	Hypertension, diabetes, coronary artery disease
B	Structural heart disease but no symptoms	Prior myocardial infarction, valve abnormalities
C	Structural disease with current or previous symptoms	Fatigue, dyspnea; patient requires pharmacological therapy
D	Refractory heart failure requiring specialized interventions	Hospitalized, awaiting transplant, on mechanical support

Progression through these stages is accelerated by inadequate treatment, recurrent cardiac events, poor diet, advancing age, and unhealthy lifestyle habits. Conversely, controlling blood pressure, adhering to prescribed therapies, and maintaining good cardiovascular health can slow the decline.

Special Considerations for Systolic Heart Failure

Systolic heart failure, characterized by a reduced ejection fraction, is associated with a particularly guarded prognosis. Mortality increases as EF declines. For example, registry data indicate a 1‑year mortality of approximately $26\%$ for patients with low EF compared with $22\%$ for those with preserved EF. The MAGGIC score accounts for this by assigning higher points to lower EF values and by stratifying age and sBP points according to EF category.

Limitations

While this tool provides evidence‑based risk estimates, it does not capture all individual nuances. The MAGGIC model was derived from group averages, so the calculated probabilities should be interpreted as statistical projections rather than precise predictions. Clinical assessment by a cardiologist remains indispensable for personalized management.