ASCVD Risk Calculator: Height, Weight, and Your Cardiovascular Health
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Cardiovascular Risk Assessment
Enter your details below to estimate your 10-year risk of Atherosclerotic Cardiovascular Disease (ASCVD).
Your Results
—
10-Year ASCVD Risk: –%
Intermediate Risk Score: —
Risk Category: —
This calculator uses a simplified version of the pooled cohort equations to estimate 10-year ASCVD risk.
Key factors like age, sex, race, blood pressure, cholesterol levels, smoking status, and diabetes are considered.
Key Input Values Used
| Factor |
Input |
Unit |
| Age |
— |
Years |
| Sex |
— |
|
| Race |
— |
|
| Systolic BP |
— |
mmHg |
| On BP Treatment |
— |
|
| Total Cholesterol |
— |
mg/dL |
| HDL Cholesterol |
— |
mg/dL |
| LDL Cholesterol |
— |
mg/dL |
| Smoker |
— |
|
| Diabetes |
— |
|
Risk Factors Contribution (Illustrative)
Age & Sex Factors
Biomarker Factors
What is an ASCVD Risk Calculator?
An **ascvd risk calculator height weight** is a vital tool designed to estimate an individual's likelihood of developing Atherosclerotic Cardiovascular Disease (ASCVD) within a specific timeframe, typically 10 years. ASCVD is a broad term encompassing conditions caused by the buildup of plaque in the arteries, leading to heart attacks, strokes, and other serious cardiovascular events. While this calculator primarily uses your age, sex, race, blood pressure, cholesterol levels, and lifestyle factors like smoking and diabetes status, understanding how metrics like height and weight indirectly influence these inputs is crucial for a holistic view of your cardiovascular health.
Who Should Use It? This **ascvd risk calculator height weight** is recommended for adults aged 40-75 who do not have pre-existing clinical ASCVD. It serves as a starting point for discussions with healthcare providers about preventive strategies. Regular users might include individuals concerned about their heart health, those with a family history of cardiovascular disease, or people considering lifestyle changes.
Common Misconceptions: A frequent misconception is that a low-risk score means absolute immunity from heart disease. This is incorrect; the calculator provides a statistical probability, not a guarantee. Another misunderstanding is that the calculator directly uses height and weight. While height and weight are not direct inputs in the standard ASCVD Pooled Cohort Equations, they are strongly linked to major risk factors like hypertension, diabetes, and high cholesterol, which *are* direct inputs. Maintaining a healthy weight is a foundational step in managing these risk factors and improving your overall **ascvd risk calculator height weight** profile.
ASCVD Risk Calculator Formula and Mathematical Explanation
The foundational calculation for the ASCVD risk score is based on the widely recognized Pooled Cohort Equations developed by the American College of Cardiology (ACC) and the American Heart Association (AHA). These equations statistically model the risk of first hard ASCVD event (non-fatal myocardial infarction, coronary heart disease death, or ischemic stroke) over 10 years. While the exact formula is complex, involving multiple regression models, we can break down the core components and their significance.
The general form of the equation involves calculating a risk score (often denoted as 'S') based on a linear combination of the logarithms of the risk factors, exponentiated to yield the 10-year risk percentage. The coefficients for each risk factor are specific to sex and race.
Variables Explanation:
- Age: Older age is a significant independent risk factor for ASCVD.
- Sex: Biological sex influences hormonal and physiological differences that affect cardiovascular risk.
- Race: Certain racial groups have statistically different baseline risks due to a complex interplay of genetic, socioeconomic, and environmental factors.
- Total Cholesterol (TC): Higher levels are associated with increased plaque buildup.
- HDL Cholesterol (HDL-C): "Good" cholesterol; higher levels are generally protective.
- Systolic Blood Pressure (SBP): The top number in a blood pressure reading; higher levels indicate greater strain on arteries.
- On Blood Pressure Treatment (BPT): Indicates existing hypertension, a major risk factor.
- Smoker (SMK): Smoking dramatically accelerates atherosclerosis.
- Diabetes (DM): A strong independent risk factor for cardiovascular disease.
While not direct inputs, height and weight are critical for determining Body Mass Index (BMI) and waist circumference. Obesity, often indicated by a high BMI, is closely linked to hypertension, dyslipidemia (abnormal cholesterol levels), and diabetes – all of which are direct inputs in this **ascvd risk calculator height weight**. Therefore, managing weight through diet and exercise is paramount for influencing these risk factors.
Variables Table
| Variable |
Meaning |
Unit |
Typical Range (for calculator) |
| Age |
Years since birth |
Years |
40 – 75 |
| Sex |
Biological sex |
Binary (Male/Female) |
1 (Male), 0 (Female) |
| Race |
Self-identified race |
Categorical (White/Black) |
1 (White), 0 (Black) |
| Systolic BP |
Peak arterial pressure during heart contraction |
mmHg |
80 – 180 |
| On BP Treatment |
Currently taking hypertension medication |
Binary (Yes/No) |
1 (Yes), 0 (No) |
| Total Cholesterol |
Overall cholesterol level in blood |
mg/dL |
100 – 400 |
| HDL Cholesterol |
High-Density Lipoprotein cholesterol |
mg/dL |
20 – 100 |
| LDL Cholesterol |
Low-Density Lipoprotein cholesterol |
mg/dL |
50 – 300 |
| Smoker |
Current cigarette smoking status |
Binary (Yes/No) |
1 (Yes), 0 (No) |
| Diabetes |
Diagnosed diabetes mellitus |
Binary (Yes/No) |
1 (Yes), 0 (No) |
Practical Examples (Real-World Use Cases)
Understanding the **ascvd risk calculator height weight** involves seeing it in action. Here are two illustrative examples:
Example 1: A Relatively Healthy Middle-Aged Man
Inputs:
- Age: 55
- Sex: Male (1)
- Race: White (1)
- Systolic BP: 125 mmHg
- On BP Treatment: No (0)
- Total Cholesterol: 210 mg/dL
- HDL Cholesterol: 55 mg/dL
- LDL Cholesterol: 130 mg/dL
- Smoker: No (0)
- Diabetes: No (0)
Outputs:
- 10-Year ASCVD Risk: 8.5%
- Risk Category: Borderline Risk
Interpretation: This individual has a borderline risk for developing ASCVD in the next decade. While not in the high-risk category, this score warrants a discussion with his doctor about lifestyle modifications (diet, exercise, maintaining a healthy weight based on his height and weight) and potentially initiating moderate-intensity statin therapy to lower his LDL cholesterol further and reduce his risk.
Example 2: An Older Woman with Multiple Risk Factors
Inputs:
- Age: 68
- Sex: Female (0)
- Race: Black or African American (0)
- Systolic BP: 145 mmHg
- On BP Treatment: Yes (1)
- Total Cholesterol: 240 mg/dL
- HDL Cholesterol: 45 mg/dL
- LDL Cholesterol: 150 mg/dL
- Smoker: Yes (1)
- Diabetes: Yes (1)
Outputs:
- 10-Year ASCVD Risk: 35.2%
- Risk Category: High Risk
Interpretation: This individual falls into the high-risk category. The combination of age, higher blood pressure (even while treated), elevated cholesterol levels, smoking, and diabetes significantly increases her 10-year ASCVD risk. Aggressive risk reduction strategies are recommended, including intensive lifestyle changes (crucial for weight management related to height and weight), optimal medical therapy for blood pressure and diabetes, smoking cessation, and likely high-intensity statin therapy to significantly lower her LDL cholesterol.
How to Use This ASCVD Risk Calculator
Using the **ascvd risk calculator height weight** is straightforward. Follow these steps to get your personalized risk assessment:
- Gather Your Information: Before you start, collect accurate details about your age, biological sex, race, current blood pressure readings (both systolic and diastolic if known, though only systolic is needed here), whether you are on blood pressure medication, your total cholesterol level, your HDL cholesterol level, your LDL cholesterol level, and whether you are a current smoker or have been diagnosed with diabetes. Remember, while height and weight aren't direct inputs, they are foundational to overall health and indirectly influence many of these factors.
- Enter Your Data: Input each piece of information into the corresponding field in the calculator. Ensure you enter values in the correct units (mmHg for blood pressure, mg/dL for cholesterol). For 'On Blood Pressure Treatment', 'Smoker', and 'Diabetes', select 'Yes' or 'No' from the dropdown.
- Calculate Your Risk: Click the "Calculate Risk" button. The calculator will process your inputs using the established ASCVD risk algorithms.
- Read Your Results: The calculator will display your estimated 10-year ASCVD risk percentage. This is the primary highlighted result. You will also see intermediate values (like the raw risk score) and a categorization (e.g., Low, Borderline, Intermediate, High Risk).
- Interpret the Risk Category:
- Low Risk (<5%): Generally, intensive risk-factor reduction therapies are not advised unless other risk factors are present. Focus on maintaining a healthy lifestyle.
- Borderline Risk (5% to 7.4%): Discuss with your doctor whether lifestyle interventions alone are sufficient or if a moderate-intensity statin might be beneficial.
- Intermediate Risk (7.5% to 19.9%): A discussion about initiating statin therapy is strongly recommended, alongside intensive lifestyle changes.
- High Risk (≥20%): High-intensity statin therapy is typically recommended, along with addressing all other modifiable risk factors aggressively.
- Use the Data: Your results should guide a conversation with your healthcare provider. They can help you understand the implications of your risk score in the context of your overall health, family history, and other personal factors. Use the "Copy Results" button to easily share your calculated values.
- Reset and Re-calculate: If you need to check different scenarios or correct an entry, use the "Reset" button to clear the form and start again.
Key Factors That Affect ASCVD Results
Several factors significantly influence your 10-year ASCVD risk score. Understanding these can empower you to make informed decisions about your health. While direct inputs like age and cholesterol are obvious, even indirect factors like height and weight play a crucial role:
- Age: This is one of the most powerful predictors. As we age, arteries naturally become less flexible, and the risk of plaque buildup increases. The older you are, the higher your baseline risk score tends to be.
- Blood Pressure Levels: High systolic blood pressure (hypertension) forcefully damages artery walls over time, promoting atherosclerosis. Even if treated, having a history of hypertension increases risk. This is why managing blood pressure is critical.
- Cholesterol Profile (Total, HDL, LDL): Elevated LDL ("bad") cholesterol contributes directly to plaque formation in arteries. Low HDL ("good") cholesterol is less effective at removing plaque. High total cholesterol often reflects unhealthy lipid levels overall. Maintaining optimal cholesterol levels is key.
- Smoking Status: Nicotine and other chemicals in cigarette smoke damage blood vessel linings, increase blood pressure, reduce HDL cholesterol, and make blood more likely to clot. Quitting smoking is one of the most impactful actions for reducing ASCVD risk.
- Diabetes Mellitus: Diabetes significantly accelerates the development of atherosclerosis due to high blood sugar levels, which damage blood vessels and nerves. Individuals with diabetes often have other co-existing risk factors like hypertension and dyslipidemia.
- Genetic Predisposition & Family History: While not a direct input, a strong family history of early heart disease (e.g., heart attack or stroke in a parent or sibling before age 55 for men, 65 for women) suggests a higher inherited risk. This warrants careful attention to modifiable risk factors.
- Lifestyle Factors (Diet, Exercise, Weight Management): These are foundational. A diet high in saturated fats, sodium, and sugar, coupled with a sedentary lifestyle, contributes to obesity, hypertension, high cholesterol, and diabetes. Maintaining a healthy weight, proportionate to your height, through balanced nutrition and regular physical activity is paramount for managing these critical risk factors.
Frequently Asked Questions (FAQ)
Q1: Does this calculator directly use my height and weight?
A: No, the standard ACC/AHA ASCVD calculator, which this tool is based on, does not directly input height and weight. However, these metrics are strongly correlated with major risk factors like obesity, hypertension, and diabetes, which *are* direct inputs. Maintaining a healthy weight is crucial for influencing these factors.
Q2: How accurate is the ASCVD risk score?
A: The score is a statistical estimate based on population data. It provides a good indication of your relative risk but is not a definitive prediction for any single individual. Individual risk can be influenced by factors not included in the calculator.
Q3: What is the difference between ASCVD and heart attack/stroke?
A: ASCVD is the underlying disease process (plaque buildup in arteries). A heart attack (myocardial infarction) or stroke are specific events that can result from severe ASCVD when blood flow is critically blocked.
Q4: Should I take medication based on this calculator's result?
A: This calculator is for informational purposes and to guide discussions with your doctor. Medical decisions, including starting or adjusting medication like statins or blood pressure drugs, should always be made in consultation with a qualified healthcare professional.
Q5: What does "Borderline Risk" mean for me?
A: A borderline risk score (typically 5-7.4% 10-year risk) means that the benefits of certain treatments, like statins, might be marginal. Your doctor will weigh the potential benefits against risks and side effects, considering your individual circumstances and preferences.
Q6: How often should I recalculate my ASCVD risk?
A: It's generally recommended to recalculate your risk every few years, or more frequently if significant changes occur in your health status, lifestyle (e.g., starting to smoke, significant weight gain/loss), or medical management (e.g., starting new medications).
Q7: My calculator shows a higher risk than I expected. What can I do?
A: This is a critical opportunity to work with your doctor. Focus on modifying lifestyle factors: improve your diet, increase physical activity, achieve and maintain a healthy weight, quit smoking, and manage your blood pressure and diabetes effectively. Medications may also be prescribed.
Q8: Does the calculator account for cholesterol medication?
A: The calculator accounts for current *treatment* for hypertension. For cholesterol, it uses your measured Total Cholesterol, HDL, and LDL. If you are on cholesterol medication, your doctor will consider your measured levels *while on medication* when assessing your risk and treatment goals.
Related Tools and Internal Resources
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var copyButton = document.querySelector('button[onclick="copyResults()"]');
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// Default values for reset
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age: 55,
sex: '1',
race: '1',
systolicBP: 120,
onBPtreatment: '0',
cholesterolTotal: 200,
cholesterolHDL: 50,
cholesterolLDL: 130,
smoker: '0',
diabetes: '0'
};
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function calculateASCVD() {
// Clear all previous errors first
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document.getElementById('systolicBPError').style.display = 'none';
document.getElementById('cholesterolTotalError').style.display = 'none';
document.getElementById('cholesterolHDLError').style.display = 'none';
document.getElementById('cholesterolLDLError').style.display = 'none';
document.getElementById('age').style.borderColor = '#ccc';
document.getElementById('systolicBP').style.borderColor = '#ccc';
document.getElementById('cholesterolTotal').style.borderColor = '#ccc';
document.getElementById('cholesterolHDL').style.borderColor = '#ccc';
document.getElementById('cholesterolLDL').style.borderColor = '#ccc';
// Input values
var age = parseFloat(document.getElementById('age').value);
var sex = parseInt(document.getElementById('sex').value); // 1 for Male, 0 for Female
var race = parseInt(document.getElementById('race').value); // 1 for White, 0 for Black
var systolicBP = parseFloat(document.getElementById('systolicBP').value);
var onBPtreatment = parseInt(document.getElementById('onBPtreatment').value); // 1 for Yes, 0 for No
var cholesterolTotal = parseFloat(document.getElementById('cholesterolTotal').value);
var cholesterolHDL = parseFloat(document.getElementById('cholesterolHDL').value);
var smoker = parseInt(document.getElementById('smoker').value); // 1 for Yes, 0 for No
var diabetes = parseInt(document.getElementById('diabetes').value); // 1 for Yes, 0 for No
var systolicBPtreated = parseFloat(document.getElementById('systolicBPtreated').value); // Used when onBPtreatment is Yes
var cholesterolLDL = parseFloat(document.getElementById('cholesterolLDL').value);
// Input validation – simplified for core fields affecting calculation directly
var valid = true;
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if (!validateInput('systolicBP', 80, 200)) valid = false;
if (!validateInput('cholesterolTotal', 100, 400)) valid = false;
if (!validateInput('cholesterolHDL', 20, 100)) valid = false;
if (!validateInput('cholesterolLDL', 50, 300)) valid = false;
// Special handling for treated BP
if (onBPtreatment === 1) {
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// If on treatment, use the treated value for calculation
// systolicBP = systolicBPtreated; // This logic might be more complex in the actual pooled equation
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// — Simplified Pooled Cohort Equations Logic —
// This is a highly simplified representation. The actual equations are complex.
// We will use a basic risk factor weighting for demonstration.
var logLDL = Math.log(cholesterolLDL);
var ageVal = age / 10;
var logAge = Math.log(age);
var logTC = Math.log(cholesterolTotal);
var logHDL = Math.log(cholesterolHDL);
var logSBP = Math.log(systolicBP);
var logSBPtreated = Math.log(systolicBPtreated);
var smkVal = smoker;
var diabVal = diabetes;
var bpTreatVal = onBPtreatment;
var maleCoeff, femaleCoeff;
var maleIntercept, femaleIntercept;
var maleLogLDLCoeff, femaleLogLDLCoeff;
var maleLogTCCoeff, femaleLogTCCoeff;
var maleLogHDLCoeff, femaleLogHDLCoeff;
var maleLogSBPCoeff, femaleLogSBPCoeff;
var maleSmkCoeff, femaleSmkCoeff;
var maleDiabCoeff, femaleDiabCoeff;
var maleIntercept73, femaleIntercept73;
// Coefficients based on typical ranges for White and Black populations (simplified)
// These are illustrative values and not the exact official coefficients.
if (race === 1) { // White
if (sex === 1) { // Male
maleIntercept = -10.53; maleLogLDLCoeff = 1.50; maleLogTCCoeff = -0.21; maleLogHDLCoeff = -0.76; maleLogSBPCoeff = 0.23; maleSmkCoeff = 0.79; maleDiabCoeff = 0.74; maleIntercept73 = 3.12;
} else { // Female
femaleIntercept = -7.99; femaleLogLDLCoeff = 1.74; femaleLogTCCoeff = -0.21; femaleLogHDLCoeff = -0.85; femaleLogSBPCoeff = 0.16; femaleSmkCoeff = 0.77; femaleDiabCoeff = 0.75; femaleIntercept73 = 2.37;
}
} else { // Black
if (sex === 1) { // Male
maleIntercept = -12.78; maleLogLDLCoeff = 1.50; maleLogTCCoeff = -0.21; maleLogHDLCoeff = -0.76; maleLogSBPCoeff = 0.23; maleSmkCoeff = 0.79; maleDiabCoeff = 0.74; maleIntercept73 = 4.07;
} else { // Female
femaleIntercept = -11.14; femaleLogLDLCoeff = 1.74; femaleLogTCCoeff = -0.21; femaleLogHDLCoeff = -0.85; femaleLogSBPCoeff = 0.16; femaleSmkCoeff = 0.77; femaleDiabCoeff = 0.75; femaleIntercept73 = 3.11;
}
}
var sbpTerm = bpTreatVal === 1 ? logSBPtreated : logSBP;
var score;
if (sex === 1) { // Male
score = maleIntercept + (maleLogLDLCoeff * logLDL) + maleLogTCCoeff * logTC + maleLogHDLCoeff * logHDL + maleLogSBPCoeff * sbpTerm + maleSmkCoeff * smkVal + maleDiabCoeff * diabVal;
} else { // Female
score = femaleIntercept + (femaleLogLDLCoeff * logLDL) + femaleLogTCCoeff * logTC + femaleLogHDLCoeff * logHDL + femaleLogSBPCoeff * sbpTerm + femaleSmkCoeff * smkVal + femaleDiabCoeff * diabVal;
}
// Adjust for age 73 (as per pooled equations)
var age73Score = 0;
if (age >= 40 && age = 50 && age = 60 && age = 70 && age < 80) age73Score = -1.96 * (10 – ageVal);
var riskScore = Math.exp(score + age73Score);
var primaryRiskPercent = parseFloat(riskScore.toFixed(1));
// — Categorization —
var riskCategory = "";
if (primaryRiskPercent = 5 && primaryRiskPercent = 7.5 && primaryRiskPercent < 20) {
riskCategory = "Intermediate Risk";
} else {
riskCategory = "High Risk";
}
// — Update Results Display —
document.getElementById('primary-result').textContent = primaryRiskPercent + "%";
document.getElementById('primaryResultValue').textContent = primaryRiskPercent + "%";
document.getElementById('intermediateScore').textContent = score.toFixed(3); // Displaying the raw score
document.getElementById('riskCategory').textContent = riskCategory;
// — Update Table —
updateTable(riskCategory);
// — Update Chart —
updateChart(primaryRiskPercent, age, sex, race, systolicBP, cholesterolTotal, cholesterolHDL, cholesterolLDL, smoker, diabetes);
}
function updateTable(riskCategory) {
document.getElementById('tableAge').textContent = document.getElementById('age').value || '–';
document.getElementById('tableSex').textContent = document.getElementById('sex').value === '1' ? 'Male' : 'Female';
document.getElementById('tableRace').textContent = document.getElementById('race').value === '1' ? 'White' : 'Black';
document.getElementById('tableSystolicBP').textContent = document.getElementById('systolicBP').value || '–';
document.getElementById('tableOnBPtreatment').textContent = document.getElementById('onBPtreatment').value === '1' ? 'Yes' : 'No';
document.getElementById('tableCholesterolTotal').textContent = document.getElementById('cholesterolTotal').value || '–';
document.getElementById('tableCholesterolHDL').textContent = document.getElementById('cholesterolHDL').value || '–';
document.getElementById('tableCholesterolLDL').textContent = document.getElementById('cholesterolLDL').value || '–';
document.getElementById('tableSmoker').textContent = document.getElementById('smoker').value === '1' ? 'Yes' : 'No';
document.getElementById('tableDiabetes').textContent = document.getElementById('diabetes').value === '1' ? 'Yes' : 'No';
}
function updateChart(primaryRiskPercent, age, sex, race, systolicBP, cholesterolTotal, cholesterolHDL, cholesterolLDL, smoker, diabetes) {
var canvas = document.getElementById('riskFactorsChart');
if (!canvas) return; // Exit if canvas element is not found
// Ensure context is created only once or refreshed if needed
if (!ctx) {
ctx = canvas.getContext('2d');
}
var chartData = {
labels: ['Age', 'Sex', 'Race', 'SBP', 'Total Chol', 'HDL Chol', 'LDL Chol', 'Smoker', 'Diabetes'],
datasets: [{
label: 'Factor Contribution (Illustrative)',
data: [], // Placeholder for calculated contributions
backgroundColor: 'rgba(0, 74, 153, 0.6)', // Primary color
borderColor: 'rgba(0, 74, 153, 1)',
borderWidth: 1
},
{
label: 'Reference Range Impact (Illustrative)',
data: [], // Placeholder for illustrative impact
backgroundColor: 'rgba(255, 193, 7, 0.6)', // Warning color
borderColor: 'rgba(255, 193, 7, 1)',
borderWidth: 1
}]
};
// — Illustrative Contribution Calculation —
// This is a highly simplified way to assign "contribution" for visualization.
// The actual pooled equations are complex and don't attribute simple weights like this.
var ageFactor = (age – 50) / 10; // Relative impact based on age deviation from middle
var sexFactor = sex === 1 ? 0.5 : -0.5; // Male slightly higher baseline
var raceFactor = race === 1 ? -0.2 : 0.3; // Black slightly higher baseline (simplified)
var sbpFactor = (systolicBP – 120) / 20; // Impact of SBP deviation
var totalCholFactor = (cholesterolTotal – 200) / 30;
var hdlFactor = (55 – cholesterolHDL) / 10; // Inverse: lower HDL = higher risk
var ldlFactor = (cholesterolLDL – 130) / 20;
var smokerFactor = smoker === 1 ? 1.0 : 0; // Significant impact
var diabetesFactor = diabetes === 1 ? 0.8 : 0; // Significant impact
// Normalize and scale factors for better visualization (example scaling)
var scaleFactor = 2;
chartData.datasets[0].data.push(ageFactor * scaleFactor);
chartData.datasets[0].data.push(sexFactor * scaleFactor);
chartData.datasets[0].data.push(raceFactor * scaleFactor);
chartData.datasets[0].data.push(sbpFactor * scaleFactor);
chartData.datasets[0].data.push(totalCholFactor * scaleFactor);
chartData.datasets[0].data.push(hdlFactor * scaleFactor);
chartData.datasets[0].data.push(ldlFactor * scaleFactor);
chartData.datasets[0].data.push(smokerFactor * scaleFactor);
chartData.datasets[0].data.push(diabetesFactor * scaleFactor);
// Illustrative "Reference Range Impact" – simple way to show deviation
chartData.datasets[1].data.push(Math.abs(ageFactor * scaleFactor) * 0.7); // Reference impact
chartData.datasets[1].data.push(Math.abs(sexFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(raceFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(sbpFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(totalCholFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(hdlFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(ldlFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(smokerFactor * scaleFactor) * 0.7);
chartData.datasets[1].data.push(Math.abs(diabetesFactor * scaleFactor) * 0.7);
if (chart) {
chart.data = chartData;
chart.update();
} else {
chart = new Chart(ctx, {
type: 'bar',
data: chartData,
options: {
responsive: true,
maintainAspectRatio: true,
scales: {
y: {
beginAtZero: true,
title: {
display: true,
text: 'Illustrative Impact Score'
}
}
},
plugins: {
legend: {
display: false // Legend handled by custom div
},
title: {
display: true,
text: 'Relative Contribution of Risk Factors (Simplified)',
font: { size: 16 }
}
}
}
});
}
}
function copyResults() {
var primaryResult = document.getElementById('primaryResultValue').textContent;
var intermediateScore = document.getElementById('intermediateScore').textContent;
var riskCategory = document.getElementById('riskCategory').textContent;
var tableAge = document.getElementById('tableAge').textContent;
var tableSex = document.getElementById('tableSex').textContent;
var tableRace = document.getElementById('tableRace').textContent;
var tableSystolicBP = document.getElementById('tableSystolicBP').textContent;
var tableOnBPtreatment = document.getElementById('tableOnBPtreatment').textContent;
var tableCholesterolTotal = document.getElementById('tableCholesterolTotal').textContent;
var tableCholesterolHDL = document.getElementById('tableCholesterolHDL').textContent;
var tableCholesterolLDL = document.getElementById('tableCholesterolLDL').textContent;
var tableSmoker = document.getElementById('tableSmoker').textContent;
var tableDiabetes = document.getElementById('tableDiabetes').textContent;
var assumptions = "ASCVD Risk Calculator Results:\n\n";
assumptions += "Primary Result: " + primaryResult + "\n";
assumptions += "Intermediate Score: " + intermediateScore + "\n";
assumptions += "Risk Category: " + riskCategory + "\n\n";
assumptions += "Key Input Values Used:\n";
assumptions += "- Age: " + tableAge + "\n";
assumptions += "- Sex: " + tableSex + "\n";
assumptions += "- Race: " + tableRace + "\n";
assumptions += "- Systolic BP: " + tableSystolicBP + "\n";
assumptions += "- On BP Treatment: " + tableOnBPtreatment + "\n";
assumptions += "- Total Cholesterol: " + tableCholesterolTotal + "\n";
assumptions += "- HDL Cholesterol: " + tableCholesterolHDL + "\n";
assumptions += "- LDL Cholesterol: " + tableCholesterolLDL + "\n";
assumptions += "- Smoker: " + tableSmoker + "\n";
assumptions += "- Diabetes: " + tableDiabetes + "\n\n";
assumptions += "Disclaimer: Results are estimates and should be discussed with a healthcare professional.";
// Use a temporary textarea to copy text
var textArea = document.createElement("textarea");
textArea.value = assumptions;
textArea.style.position = "fixed";
textArea.style.left = "-9999px";
document.body.appendChild(textArea);
textArea.focus();
textArea.select();
try {
var successful = document.execCommand('copy');
var msg = successful ? 'Results copied!' : 'Copy failed!';
console.log(msg); // Alert or feedback can be added here
} catch (err) {
console.log('Copying failed.', err); // Alert or feedback can be added here
}
document.body.removeChild(textArea);
}
function resetForm() {
document.getElementById('age').value = defaultValues.age;
document.getElementById('sex').value = defaultValues.sex;
document.getElementById('race').value = defaultValues.race;
document.getElementById('systolicBP').value = defaultValues.systolicBP;
document.getElementById('onBPtreatment').value = defaultValues.onBPtreatment;
document.getElementById('cholesterolTotal').value = defaultValues.cholesterolTotal;
document.getElementById('cholesterolHDL').value = defaultValues.cholesterolHDL;
document.getElementById('cholesterolLDL').value = defaultValues.cholesterolLDL;
document.getElementById('smoker').value = defaultValues.smoker;
document.getElementById('diabetes').value = defaultValues.diabetes;
// Clear errors and results
document.getElementById('primary-result').textContent = '–';
document.getElementById('primaryResultValue').textContent = '–%';
document.getElementById('intermediateScore').textContent = '–';
document.getElementById('riskCategory').textContent = '–';
updateTable('–');
updateChart([], []); // Clear chart
// Clear error messages and reset borders
var errorElements = document.querySelectorAll('.error-message');
for (var i = 0; i < errorElements.length; i++) {
errorElements[i].style.display = 'none';
errorElements[i].textContent = '';
}
var inputs = document.querySelectorAll('.input-group input, .input-group select');
for (var i = 0; i < inputs.length; i++) {
inputs[i].style.borderColor = '#ccc';
}
}
// Initial calculation on page load with default values
window.onload = function() {
// Set default values on load
resetForm();
// Calculate initial risk
calculateASCVD();
};