Enter patient details
Example data table
| Scenario | Sex | Age | SBP | HR | LVH | CHD | Valve | Diabetes | Model | Estimated 4-year risk |
|---|---|---|---|---|---|---|---|---|---|---|
| Example A | Male | 55 | 150 | 80 | No | No | No | No | Simplified | 0.0% |
| Example B | Female | 65 | 160 | 88 | No | No | No | Yes | Simplified | 0.1% |
| Example C | Male | 72 | 180 | 96 | Yes | Yes | No | Yes | Simplified | 0.3% |
| Example D | Female | 70 | 150 | 78 | Yes | No | Yes | Yes | Simplified | 0.4% |
| Example E | Male | 60 | 140 | 72 | No | No | No | No | Extended | 0.1% |
Formula used
This tool implements a Framingham Heart Study congestive heart failure risk function using a pooled logistic regression. Predicted probability is computed as: p = 1 / (1 + e−xβ).
- Age is entered in years and scaled per 10 years.
- SBP is entered in mmHg and scaled per 20 mmHg.
- Heart rate is entered in bpm and scaled per 10 bpm.
- Vital capacity uses liters (1 L = 100 cL).
- Binary findings use 0 = No/Unknown, 1 = Yes.
- Estimated probability of heart failure within 4 years.
- A qualitative band (low, moderate, elevated, high).
- Largest term contributions from your entered inputs.
Coefficients summary
| Model | Sex | Intercept | Age/10y | LVH | HR/10 | SBP/20 | CHD | Valve | Diabetes | BMI | Vital cap (L) | Cardiomegaly | Valve×Diabetes |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Simplified | Male | -9.2087 | 0.0412 | 0.9026 | 0.0166 | 0.00804 | 1.6079 | 0.9714 | 0.2244 | — | — | — | — |
| Simplified | Female | -10.7988 | 0.0503 | 1.3402 | 0.0105 | 0.00337 | 1.5549 | 1.3929 | 1.3857 | 0.0578 | — | — | -0.9860 |
| Extended | Male | -7.3611 | 0.0313 | 0.8428 | 0.0144 | 0.0067 | 1.5333 | 0.8868 | 0.2383 | — | -0.0030 | 0.7968 | — |
| Extended | Female | -5.4997 | 0.0216 | 1.0072 | 0.0092 | 0.0032 | 1.5358 | 1.2454 | 1.4275 | — | -0.0087 | 0.4792 | -0.9293 |
Source: Framingham Heart Study risk functions for congestive heart failure (coefficients and logistic probability formula).
How to use this calculator
- Enter sex, age, systolic blood pressure, and resting heart rate.
- Add clinical findings (LVH, coronary disease, valve disease, diabetes).
- For women on the simplified model, provide BMI or height and weight.
- Optionally choose the extended model if spirometry and imaging are known.
- Press Calculate risk to see the estimate above the form.
- Export the result as CSV or PDF for sharing.
Population context and why risk scoring matters
Heart failure (HF) is a leading cause of hospitalization and long-term disability. This calculator estimates the probability of developing congestive HF within four years using risk-function coefficients derived from community cohorts. Quantifying risk supports structured conversations, helps prioritize follow-up, and allows “what-if” comparisons (for example, the impact of a lower systolic blood pressure). The output is a percentage, not a diagnosis. It supports consistent documentation.
Key inputs captured by the form
The model combines continuous vitals with yes/no clinical findings. Age is scaled per 10 years, systolic blood pressure per 20 mmHg, and resting heart rate per 10 beats/min to reflect how risk increases across clinical ranges. Left ventricular hypertrophy (LVH), coronary heart disease, valve disease, and diabetes are entered as binary indicators. In the simplified pathway, BMI is used for women when available from direct entry or computed from height and weight.
How the percentage result should be interpreted
The reported value is a modeled probability over four years. To improve readability, the calculator assigns bands: Low (<5%), Moderate (5–<10%), Elevated (10–<20%), and High (≥20%). Use bands to compare scenarios rather than to make treatment decisions in isolation. The “top drivers” list highlights the variables that contributed the largest absolute change to the risk score for your entry.
Limitations and appropriate use
Risk equations are population averages; they may under- or over-estimate risk in groups not well represented in the cohorts. The calculator does not incorporate echocardiography, natriuretic peptides, kidney function, smoking, medications, or prior HF admissions. It is not intended for emergency symptoms such as chest pain, severe breathlessness, syncope, or rapidly worsening edema—seek urgent care instead. Always interpret results with a clinician.
Improving input quality and documentation
Accurate inputs improve consistency. Measure blood pressure after five minutes seated, use the average of two readings, and record resting heart rate when the person is calm. Confirm diagnoses (LVH, coronary disease, valve disease, diabetes) from medical records when possible. If using the extended model, enter vital capacity from spirometry in liters and cardiomegaly from imaging reports. Export CSV/PDF to document assumptions and repeat calculations over time.
FAQs
1) What does “4-year risk” mean?
“4-year risk” is the estimated probability that congestive heart failure will occur within the next four years, based on the inputs you entered. It summarizes population-level risk, not certainty for an individual.
2) Is this the same as ASCVD risk?
No. ASCVD tools focus on heart attack and stroke risk. This calculator targets congestive heart failure using different predictors, coefficients, and a different outcome definition.
3) Why does BMI appear only for women in simplified mode?
In the published simplified equation, BMI was included for women to improve calibration. Men use an alternate coefficient set without BMI. If BMI is unknown, use height and weight to compute it.
4) Should I use extended mode without spirometry?
Extended mode should be used only when vital capacity (spirometry) and cardiomegaly status are known. Otherwise, stay with the simplified model to avoid guesses that can distort the estimate.
5) Can I use this calculator for people with existing heart failure?
No. It is designed for people without established heart failure to estimate incident risk. If heart failure is already diagnosed, clinical staging and guideline-directed therapy decisions require clinician evaluation.
6) How should I act on a higher result?
Use the result to guide a discussion with a clinician. Common levers include blood pressure control, diabetes management, treating valve or coronary disease, improving fitness, limiting excess salt, and adhering to prescribed medications.