_id

683a160bc782e11e38d1b162

id

3398

title

ASCVD (Atherosclerotic Cardiovascular Disease) 2013 Risk Calculator from AHA/ACC

full_title

ASCVD (Atherosclerotic Cardiovascular Disease) 2013 Risk Calculator from AHA/ACC

short_title

2013 ASCVD Risk Calculator

med_description

Determine 10-year risk of hard ASCVD, i.e. myocardial infarction, stroke, or death due to coronary heart disease or stroke.

short_description

10-year heart disease or stroke risk.

slug

ascvd-atherosclerotic-cardiovascular-disease-2013-risk-calculator-aha-acc

description

The 2013 ASCVD Risk Calculator is a vital tool for estimating the 10-year risk of heart disease or stroke. Developed by the American College of Cardiology (ACC) and the American Heart Association (AHA), this calculator helps healthcare providers assess cardiovascular risk and guide management strategies. By inputting key patient data, including age, cholesterol levels, blood pressure, and smoking status, clinicians can make informed decisions about lifestyle changes and statin therapy to reduce the risk of atherosclerotic cardiovascular disease (ASCVD).

keywords

ASCVD risk calculator, 2013 ASCVD risk, heart disease risk, stroke risk, cardiovascular risk assessment, AHA ACC guidelines, atherosclerotic cardiovascular disease, 10-year heart disease risk, 10-year stroke risk, cholesterol management, statin therapy, cardiovascular disease prevention, heart disease calculator, stroke calculator, cardiovascular risk factors, cholesterol levels, blood pressure, smoking status, diabetes and heart disease, risk of heart attack, risk of stroke, cardiovascular health, heart disease prevention, stroke prevention, cardiology tools, primary care tools, family practice tools, internal medicine tools, pharmacy tools, cardiac health, heart disease management, stroke management, cardiovascular risk reduction, lifestyle changes for heart health, statin use guidelines, cholesterol treatment guidelines, AHA guidelines, ACC guidelines, pooled cohort equation, cardiovascular risk calculator, heart disease risk estimator, stroke risk estimator, cardiovascular risk prediction, heart disease risk prediction, stroke risk prediction, cardiovascular risk factors, cholesterol risk factors, blood pressure risk factors, smoking risk factors, diabetes risk factors, heart disease and diabetes, stroke and diabetes, cardiovascular risk management, heart disease risk management, stroke risk management, cardiovascular risk counseling, heart disease risk counseling, stroke risk counseling, cardiovascular risk discussion, heart disease risk discussion, stroke risk discussion, cardiovascular risk reduction strategies, heart disease risk reduction strategies, stroke risk reduction strategies, cardiovascular risk assessment tools, heart disease risk assessment tools, stroke risk assessment tools, cardiovascular risk assessment guidelines, heart disease risk assessment guidelines, stroke risk assessment guidelines, cardiovascular risk assessment calculator, heart disease risk assessment calculator, stroke risk assessment calculator, cardiovascular risk assessment tool, heart disease risk assessment tool, stroke risk assessment tool, cardiovascular risk assessment methods, heart disease risk assessment methods, stroke risk assessment methods, cardiovascular risk assessment techniques, heart disease risk assessment techniques, stroke risk assessment techniques, cardiovascular risk assessment process, heart disease risk assessment process, stroke risk assessment process, cardiovascular risk assessment procedure, heart disease risk assessment procedure, stroke risk assessment procedure, cardiovascular risk assessment protocol, heart disease risk assessment protocol, stroke risk assessment protocol, cardiovascular risk assessment criteria, heart disease risk assessment criteria, stroke risk assessment criteria, cardiovascular risk assessment standards, heart disease risk assessment standards, stroke risk assessment standards, cardiovascular risk assessment guidelines, heart disease risk assessment guidelines, stroke risk assessment guidelines, cardiovascular risk assessment recommendations, heart disease risk assessment recommendations, stroke risk assessment recommendations, cardiovascular risk assessment parameters, heart disease risk assessment parameters, stroke risk assessment parameters, cardiovascular risk assessment factors, heart disease risk assessment factors, stroke risk assessment factors, cardiovascular risk assessment elements, heart disease risk assessment elements, stroke risk assessment elements, cardiovascular risk assessment components, heart disease risk assessment components, stroke risk assessment components, cardiovascular risk assessment variables, heart disease risk assessment variables, stroke risk assessment variables, cardiovascular risk assessment indicators, heart disease risk assessment indicators, stroke risk assessment indicators, cardiovascular risk assessment measures, heart disease risk assessment measures, stroke risk assessment measures, cardiovascular risk assessment metrics, heart disease risk assessment metrics, stroke risk assessment metrics, cardiovascular risk assessment benchmarks, heart disease risk assessment benchmarks, stroke risk assessment benchmarks, cardiovascular risk assessment targets, heart disease risk assessment targets, stroke risk assessment targets, cardiovascular risk assessment goals, heart disease risk assessment goals, stroke risk assessment goals, cardiovascular risk assessment objectives, heart disease risk assessment objectives, stroke risk assessment objectives, cardiovascular risk assessment aims, heart disease risk assessment aims, stroke risk assessment aims, cardiovascular risk assessment purposes, heart disease risk assessment purposes, stroke risk assessment purposes, cardiovascular risk assessment intentions, heart disease risk assessment intentions, stroke risk assessment intentions

complaint

[ "Chest Pain", "Shortness of Breath" ]

formula

Scoring information is available inAppendix 7 in the Goff, et al. 2014 study.

evidence

The 2013 ACC/AHA ASCVD risk score was developed to provide, at the time, an updated ASCVD risk stratification tool that uses commonly available risk factor variables and that makes conscious efforts to better consider / represent African Americans. Commonly referred to as the Pooled Cohort Equation (PCE), the score was developed from 5 large prospective cohort studies in the United States, with a total sample size of 24,626 in the pooled validation cohort. External validation was performed on 3 similar studies, with a total pooled sample size of 37,759. Patients aged 40 to 79 who were apparently healthy, African American or White, and free of a previous history of MI (recognized or unrecognized), stroke, congestive heart failure, percutaneous coronary intervention, coronary bypass surgery, or atrial fibrillation were included. Importantly, those who were older than 79 and those who had a known history of atrial fibrillation were excluded, meaning that the estimates are not applicable to these patient groups. While the former age-based exclusion is widely known, clinicians may not be as aware of the latter – this serves as a reminder to be especially cautious with the use and interpretation of PCE in these patients.

The authors provided detailed discussions about the choice of outcome (a composite of myocardial infarction, stroke, and death due to coronary heart disease or stroke) in the original paper’s supplementary materials. In particular, heart failure was explicitly mentioned to have been considered as a component of the outcome, but was eventually dropped due to heterogeneity in outcome definition / adjudication among the included cohorts. The authors also mentioned that additional covariates, e.g. BMI, diastolic blood pressure, eGFR, and statin use, were initially explored for inclusion in the model, but were dropped as they did not significantly improve discrimination when added to the model.

While the choice of outcome was sensible at the time that the PCE was developed and was grossly consistent with the definition of major adverse cardiovascular events used in many trials, more contemporary tools such as the European SCORE2 family of risk scores and the American PREVENT risk tool have both opted for broader cardiovascular outcomes.

Notably, the outcome led to a competing risk scenario where deaths due to causes other than coronary heart disease and stroke would prevent observation of further events and therefore constitute a competing event. Despite this, the model was constructed using a Cox proportional hazards model, essentially taking a cause-specific approach to this competing risk scenario. This was probably due to limitations with computing power at the time of development.

In the original paper, internal validation of the score was performed using a 10x10 cross-validation, achieving C-statistics between 0.713 and 0.818 in different subsets (stratified by ethnicity [White vs African Americans] and sex [males vs females]), with calibration plots showing slopes close to 1 for all subsets. In external validation, discrimination was markedly worse for all subsets across all validation cohorts (C-statistics between 0.556 and 0.768), with overestimation of event risks observed in all subsets across all validation cohorts.

Subsequently, multiple studies have externally validated the PCE. A systematic review and meta-analysis published in 2019 pooled 61 validations (30 in men and 31 in women), demonstrating a pooled C-statistic of 0.74 in women and 0.70 in men – both of which were higher than other Framingham-based scores. However, pooled analysis of calibration demonstrated significant overestimation of risks in both sexes, with pooled observed-expected (O/E) ratios of 0.66 in men and 0.76 in women. This has continued to be echoed by later, more contemporary studies, including a 2020 study by Khera et al using data from 8 US cohorts – they observed that calibration was especially bad in high-risk patients and those with high BMI. There were also studies that found the opposite, such as a 2019 Austrian study by Wallisch et al, although these studies appeared to be far fewer and less common than those that showed overestimation. However, a decision curve analysis by Qureshi et al has shown that there was net benefit in replacing the older Framingham cohort-based scores with the PCE.

It is important to note that the PCE included ethnicity (African American or not) in the model. This was intentional as the authors noted that previous, Framingham-based scores underrepresented African Americans. However, other ethnic minorities in the US were not given specific consideration, and some studies, such as a 2022 study by Mantri et al, demonstrated that risks may be significantly underestimated in some ethnicities such as south Asians in the United States. Overall, however, there has been criticism on the inclusion of race/ethnicity in PCE and other clinical algorithms. PCE tends to produce higher risk estimates in African Americans and thus may lead to over-intervention which, considering that race is a social construct, may be undesirable and contribute to health inequities. Some studies have also suggested that disparities in social determinants of health may be a critical driver of racial differences in cardiovascular risks. Race and ethnicity were therefore removed from the latest cardiovascular risk score developed by the AHA and ACC (the 2023 PREVENT risk prediction tool), instead including an optional social deprivation variable instead. It is important to bear in mind that studies showing issues with calibration in non-American cohorts (e.g. a Malaysian study by Chia et al) may not actually be due to ethnic differences in cardiovascular risks (which exist), but rather be due to geographical differences in cardiovascular risks which are often prominent. The latter was explicitly considered by the European Society of Cardiology’s SCORE2 family of risk scores. Clinicians outside of the United States should exercise caution when interpreting PCE estimates for their local patients.

measurements

[ { "name": "Total Cholesterol", "unit": "chol_total", "error_min": "40", "error_max": "1000", "warn_min": "150", "warn_max": "500", "conversion": "0.02586", "normal_max_si": "5.2", "normal_max_us": "200", "normal_min_si": "3.9", "normal_min_us": "150", "units_si": "mmol/L", "units_us": "mg/dL" }, { "name": "Systolic BP", "unit": "sbp", "error_min": "30", "error_max": "300", "warn_min": "40", "warn_max": "250", "conversion": "1", "normal_max_si": "120", "normal_max_us": "120", "normal_min_si": "100", "normal_min_us": "100", "units_si": "mm Hg", "units_us": "mm Hg" }, { "name": "HDL Cholesterol", "unit": "chol_hdl", "error_min": "1", "error_max": "155", "warn_min": "1", "warn_max": "95", "conversion": "0.02586", "normal_max_si": "4.01", "normal_max_us": "155", "normal_min_si": "1.55", "normal_min_us": "60", "units_si": "mmol/L", "units_us": "mg/dL" }, { "name": "Age", "unit": "age_ascvd", "error_min": "20", "error_max": "79", "warn_min": "20", "warn_max": "79", "conversion": "1", "normal_max_si": "79", "normal_max_us": "79", "normal_min_si": "20", "normal_min_us": "20", "units_si": "years", "units_us": "years" } ]

information

• These estimates may underestimate the 10-year risk for some race/ethnic groups, including American Indians, some Asian Americans (e.g., of south Asian ancestry), and some Hispanics (e.g., Puerto Ricans).
• It may overestimate the risk for some Asian Americans (e.g., of east Asian ancestry) and some Hispanics (e.g., Mexican Americans).
• Because the primary use of these risk estimates is to facilitate the very important discussion regarding risk reduction through lifestyle change, the imprecision introduced is small enough to justify proceeding with lifestyle change counseling informed by these results.

Optimal Risk Factors

For the comparison of optimal risk factors, these were defined by the following specific risk factor numbers for an individual of the same age, sex and race:

• Total cholesterol of 170 mg/dL.
• HDL-cholesterol of 50 mg/dL.
• Untreated systolic blood pressure of 110 mm Hg.
• No diabetes history.
• Not a current smoker.

US Preventive Services Task Force (USPSTF) Guidelines

In 2016, the US Preventive Services Task Force (USPSTF) made similar but slightly different recommendations for adults without a history of cardiovascular disease (CVD) to use a low- to moderate-dose statin for the prevention of CVD events and mortality when all of the following criteria are met:

1. Age 40 to 75 years.
2. 1 or more CVD risk factors (ie, dyslipidemia, diabetes, hypertension, or smoking).
3. Calculated 10-year risk of a cardiovascular event of 10% or greater (B recommendation).

The USPSTF gave a B recommendation—indicating high certainty that the benefit is moderate or moderate certainty that the benefit is moderate to substantial—for starting low- to moderate-dose statins in adults ages 40 to 75 years without a history of cardiovascular disease (CVD) who have one or more CVD risk factors and a 10-year CVD risk of 10% or greater.

The USPSTF dropped its level of endorsement to C for adults with a lower 10-year risk (7.5%-10%) and made no recommendations for adults 76 years of age and older, explaining that there was insufficient evidence for this age group.

These recommendations have been maintained in the 2022 version. 

*Thanks to Vijay Shetty, MBBS, for this summary of the 2016 USPSTF guidelines.

Intensity of Statin Therapy

refrences

{ "Clinical Practice Guidelines": [ { "href": "https://pubmed.ncbi.nlm.nih.gov/30879355/", "text": "Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [published correction appears in Circulation. 2019 Sep 10;140(11):e649-e650. doi: 10.1161/CIR.0000000000000725] [published correction appears in Circulation. 2020 Jan 28;141(4):e60. doi: 10.1161/CIR.0000000000000755] [published correction appears in Circulation. 2020 Apr 21;141(16):e774. doi: 10.1161/CIR.0000000000000771]. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678" }, { "href": "https://pubmed.ncbi.nlm.nih.gov/30586774/", "text": "Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA Guideline on the Management of Blood Cholesterol: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines [published correction appears in Circulation. 2019 Jun 18;139(25):e1182-e1186. doi: 10.1161/CIR.0000000000000698] [published correction appears in Circulation. 2023 Aug 15;148(7):e5. doi: 10.1161/CIR.0000000000001172]. Circulation. 2019;139(25):e1082-e1143. doi:10.1161/CIR.0000000000000625" }, { "href": "https://jamanetwork.com/journals/jama/fullarticle/2795521", "text": "US Preventive Services Task Force. Statin Use for the Primary Prevention of Cardiovascular Disease in Adults: US Preventive Services Task Force Recommendation Statement. JAMA. 2022;328(8):746–753. doi:10.1001/jama.2022.13044" } ], "Manufacturer Website": [], "Original/Primary Reference": [ { "href": "https://circ.ahajournals.org/content/circulationaha/129/25_suppl_2/S49.full.pdf", "text": "Goff DC Jr, et. al. 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014 Jun 24;129(25 Suppl 2):S49-73. doi: 10.1161/01.cir.0000437741.48606.98. Epub 2013 Nov 12." }, { "href": "https://circ.ahajournals.org/content/circulationaha/129/25_suppl_2/S1.full.pdf", "text": "Stone NJ, et al.Circulation. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2014 Jun 24;129(25 Suppl 2):S1-45. doi: 10.1161/01.cir.0000437738.63853.7a. Epub 2013 Nov 12" } ], "Other References": [], "Outcomes": [], "Validation": [ { "href": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246627/", "text": "Chia YC, Lim HM, Ching SM. Validation of the pooled cohort risk score in an Asian population – a retrospective cohort study. BMC Cardiovascular Disorders. 2014;14:163. doi:10.1186/1471-2261-14-163." }, { "href": "https://content.onlinejacc.org/article.aspx?articleid=2510228", "text": "Henderson K, Kaufman BG, Stearns S, et al. Validation of the Atherosclerotic Cardiovascular Disease (ASCVD) Pooled Cohort Risk Equations by Education Level: The Atheroschlerosis Risk in Communities (ARIC) Study. J Am Coll Cardiol. 2016;67(13_S):1842. doi:10.1016/S0735-1097(16)31843-5." }, { "href": "https://www.ncbi.nlm.nih.gov/pubmed/27151343", "text": "Rana JS, et al. Accuracy of the Atherosclerotic Cardiovascular Risk Equation in a Large Contemporary, Multiethnic Population. J Am Coll Cardiol. 2016 May 10;67(18):2118-30. doi: 10.1016/j.jacc.2016.02.055." }, { "href": "https://pubmed.ncbi.nlm.nih.gov/27445216/", "text": "Qureshi WT, Michos ED, Flueckiger P, et al. Impact of Replacing the Pooled Cohort Equation With Other Cardiovascular Disease Risk Scores on Atherosclerotic Cardiovascular Disease Risk Assessment (from the Multi-Ethnic Study of Atherosclerosis [MESA]). Am J Cardiol. 2016;118(5):691-696. doi:10.1016/j.amjcard.2016.06.015" }, { "href": "https://pubmed.ncbi.nlm.nih.gov/30429082/", "text": "Wallisch C, Heinze G, Rinner C, Mundigler G, Winkelmayer WC, Dunkler D. External validation of two Framingham cardiovascular risk equations and the Pooled Cohort equations: A nationwide registry analysis. Int J Cardiol. 2019;283:165-170. doi:10.1016/j.ijcard.2018.11.001" }, { "href": "https://bmcmedicine.biomedcentral.com/articles/10.1186/s12916-019-1340-7", "text": "Damen JA, Pajouheshnia R, Heus P, et al. Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis. BMC Med. 2019;17(1):109. Published 2019 Jun 13. doi:10.1186/s12916-019-1340-7" }, { "href": "https://pubmed.ncbi.nlm.nih.gov/33119108/", "text": "Khera R, Pandey A, Ayers CR, et al. Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index [published correction appears in JAMA Netw Open. 2020 Dec 1;3(12):e2030880. doi: 10.1001/jamanetworkopen.2020.30880]. JAMA Netw Open. 2020;3(10):e2023242. Published 2020 Oct 1. doi:10.1001/jamanetworkopen.2020.23242" }, { "href": "https://pubmed.ncbi.nlm.nih.gov/33115904/", "text": "Al-Shamsi S, Govender RD, King J. External validation and clinical usefulness of three commonly used cardiovascular risk prediction scores in an Emirati population: a retrospective longitudinal cohort study. BMJ Open. 2020;10(10):e040680. Published 2020 Oct 28. doi:10.1136/bmjopen-2020-040680" }, { "href": "https://pubmed.ncbi.nlm.nih.gov/36564709/", "text": "Mantri NM, Merchant M, Rana JS, Go AS, Pursnani SK. Performance of the pooled cohort equation in South Asians: insights from a large integrated healthcare delivery system. BMC Cardiovasc Disord. 2022;22(1):566. Published 2022 Dec 23. doi:10.1186/s12872-022-02993-z" } ], "Validations": [] }

pearls

• In 2013 the American College of Cardiology (ACC) and the American Heart Association (AHA) released new guidelines for the evaluation and treatment of cholesterol in order to reduce the risk of atherosclerotic cardiovascular disease (ASCVD).

• This calculator provides a simplified way to follow the ASCVD treatment recommendations for patients without known ASCVD and with LDL levels between 70-189 mg/dL (1.81-4.90 mmol/L). Our ASCVD Risk Algorithm is a step-wise approach for all adult patients – including those with known ASCVD.

• The treatment algorithm proposed by the ACC/AHA suggests aggressive treatment for many patients, but specifically notes that patients with known ASCVD and patients with extreme LDL levels (≥190 mg/dL / 4.92 mmol/L) are at the highest risk; it also provides the “intensity” of statin treatment based on patients' predicted risk levels.

Points to keep in mind:

• While the score was developed and validated in a large population from the United States, several studies have suggested that the risk calculator substantially over-estimates 10-year risk, while other studies have suggested that its risk estimates are accurate.
• This score may not be generalizable to the global population.
• Statins are highly emphasized in the guidelines and recommendations, but lifestyle modifications are likely just as – if not more – important to ASCVD risk.
• Commonly referred to as the Pooled Cohort Equation (PCE).
• The PCE is not applicable to patients with atrial fibrillation or those older than 79 as they were excluded in the original derivation and validation study.

usecase

Patients at risk for atherosclerotic cardiovascular disease (ASCVD).

reasons

The ASCVD Risk Estimate is a standardized guideline to predict risk and recommend management strategies for those at risk of hard ASCVD (i.e. myocardial infarction, stroke, or death due to coronary heart disease or stroke).

next_advice

When Considering Starting Statins

First, always engage in a clinician-patient discussion of the potential for ASCVD risk reduction, adverse effects, drug-drug interactions, and patient preferences. Consider:

• Potential for ASCVD risk-reduction benefits.
• Potential for adverse effects and drug-drug interactions.
• Heart-healthy lifestyle.
• Management of other risk factors.
• Patient preferences.

See Section 5 of the relevant 2018 American guidelines for a discussion and recommendations about statin safety. Also see Table 3 of the same guidelines for summary of grossly equivalent statin intensities for different statins at different doses.

When Considering or Using High-Intensity Statins 

The guidelines recommend the treating clinician consider:

• Multiple or serious comorbidities, such as impaired renal or hepatic function.
• A history of previous statin intolerance or muscle disorders.
• Unexplained elevated levels of alanine transaminase greater than three times the upper limit of normal.
• Patient characteristics or concomitant use of medications that affect statin metabolism.
• Age older than 75 years.

Remember that the risk of statin-related adverse effects are generally intensity-dependent. 

Additional Factors that are ASCVD Risk Enhancers per 2018 American Guidelines

• Family history of premature ASCVD.
• Persistently elevated LDL-C levels at or above 160 mg/dL (4.1 mmol/L).
• Chronic kidney disease.
• Metabolic syndrome.
• Conditions specific to women (e.g. preeclampsia, premature menopause).
• Inflammatory diseases (especially rheumatoid arthritis, psoriasis, HIV).
• Ethnicity (e.g. South Asian ethnicity).
• Persistently elevated triglycerides levels at or above 175 mg/dL (2.0 mmol/L).

• And in selected individuals if measured:

  • High-sensitivity C-reactive protein (hsCRP) levels at or above 2.0 mg/L.

  • Lp(a) levels above 50 mg/dL (125 nmol/L).

  • ApoB at or above 130 mg/dL.

  • Ankle-brachial index <0.9.

When Monitoring Statin Effects and Side Effects

• Assess adherence, response to therapy, and adverse effects within 4 to 12 weeks following statin initiation or change in therapy.
• Measure fasting lipid levels.
• Do not routinely monitor alanine transaminase or creatine kinase levels unless symptomatic.
• Screen and treat type 2 diabetes according to current practice guidelines; heart-healthy lifestyle habits should be encouraged to prevent progression to diabetes.

next_actions

next_management

diseases

[ "Diabetes Mellitus", "Dyslipidemia", "Myocardial Infarction", "Stroke / Transient Ischemic Attack (TIA)" ]

input_schema

[ { "conditionality": "", "default": null, "fhir_rules": null, "inct": null, "label_en": "<p>Age</p>", "name": "age", "optional": false, "tips_en": "This calculator only applies to individuals 40-75 years of age.", "type": "textbox", "unit": "age_ascvd" }, { "conditionality": "", "default": 0, "label_en": "<p>Diabetes</p>", "md_calc_info_concept": null, "name": "diabetes", "option_fhir_rules": null, "optional": false, "options": [ { "label": "No", "value": 0 }, { "label": "Yes", "value": 1 } ], "show_points": false, "tips_en": "", "type": "toggle" }, { "conditionality": "", "default": null, "label_en": "<p>Sex</p>", "md_calc_info_concept": null, "name": "sex", "option_fhir_rules": null, "optional": false, "options": [ { "label": "Female", "value": 0 }, { "label": "Male", "value": 1 } ], "show_points": false, "tips_en": "", "type": "toggle" }, { "conditionality": "", "default": 0, "label_en": "<p>Smoker</p>", "md_calc_info_concept": null, "name": "smoker", "option_fhir_rules": null, "optional": false, "options": [ { "label": "No", "value": 0 }, { "label": "Yes", "value": 1 } ], "show_points": false, "tips_en": "", "type": "toggle" }, { "conditionality": "", "default": null, "fhir_rules": null, "inct": null, "label_en": "<p>Total cholesterol</p>", "name": "chol_total", "optional": false, "tips_en": "", "type": "textbox", "unit": "chol_total" }, { "conditionality": "", "default": null, "fhir_rules": null, "inct": null, "label_en": "<p>HDL cholesterol</p>", "name": "chol_hdl", "optional": false, "tips_en": "", "type": "textbox", "unit": "chol_hdl" }, { "conditionality": "", "default": null, "fhir_rules": null, "inct": null, "label_en": "<p>Systolic blood pressure</p>", "name": "sbp", "optional": false, "tips_en": "", "type": "textbox", "unit": "sbp" }, { "conditionality": "", "default": 0, "label_en": "<p>Treatment for hypertension</p>", "md_calc_info_concept": null, "name": "bptreated", "option_fhir_rules": null, "optional": false, "options": [ { "label": "No", "value": 0 }, { "label": "Yes", "value": 1 } ], "show_points": false, "tips_en": "", "type": "toggle" }, { "conditionality": "", "default": null, "label_en": "<p>Race</p>", "mdcalc_info_concept": null, "name": "race", "option_fhir_rules": null, "optional": true, "options": [ { "label": "White", "value": 1 }, { "label": "African American", "value": 2 }, { "label": "Other", "value": 3 } ], "show_points": false, "tips_en": "Race may/may not provide better estimates of CV risk; optional", "type": "radio" } ]

instructions

• Our ASCVD Risk Algorithm is a step-wise approach for all adult patients – including those with known ASCVD.
• This calculator is for use only in adult patients without known ASCVD and LDL 70-189 mg/dL (1.81-4.90 mmol/L).

published

2022-04-21T20:29:16.669Z

purpose

[ "Prognosis", "Formula" ]

search_terms

[ "Acs", "mi", "stroke", "cva", "tia", "ten", "ldl", "diabetes", "pooled cohort equation" ]

seo

{ "keywords_en": "ASCVD risk calculator, 2013 ASCVD risk, heart disease risk, stroke risk, cardiovascular risk assessment, AHA ACC guidelines, atherosclerotic cardiovascular disease, 10-year heart disease risk, 10-year stroke risk, cholesterol management, statin therapy, cardiovascular disease prevention, heart disease calculator, stroke calculator, cardiovascular risk factors, cholesterol levels, blood pressure, smoking status, diabetes and heart disease, risk of heart attack, risk of stroke, cardiovascular health, heart disease prevention, stroke prevention, cardiology tools, primary care tools, family practice tools, internal medicine tools, pharmacy tools, cardiac health, heart disease management, stroke management, cardiovascular risk reduction, lifestyle changes for heart health, statin use guidelines, cholesterol treatment guidelines, AHA guidelines, ACC guidelines, pooled cohort equation, cardiovascular risk calculator, heart disease risk estimator, stroke risk estimator, cardiovascular risk prediction, heart disease risk prediction, stroke risk prediction, cardiovascular risk factors, cholesterol risk factors, blood pressure risk factors, smoking risk factors, diabetes risk factors, heart disease and diabetes, stroke and diabetes, cardiovascular risk management, heart disease risk management, stroke risk management, cardiovascular risk counseling, heart disease risk counseling, stroke risk counseling, cardiovascular risk discussion, heart disease risk discussion, stroke risk discussion, cardiovascular risk reduction strategies, heart disease risk reduction strategies, stroke risk reduction strategies, cardiovascular risk assessment tools, heart disease risk assessment tools, stroke risk assessment tools, cardiovascular risk assessment guidelines, heart disease risk assessment guidelines, stroke risk assessment guidelines, cardiovascular risk assessment calculator, heart disease risk assessment calculator, stroke risk assessment calculator, cardiovascular risk assessment tool, heart disease risk assessment tool, stroke risk assessment tool, cardiovascular risk assessment methods, heart disease risk assessment methods, stroke risk assessment methods, cardiovascular risk assessment techniques, heart disease risk assessment techniques, stroke risk assessment techniques, cardiovascular risk assessment process, heart disease risk assessment process, stroke risk assessment process, cardiovascular risk assessment procedure, heart disease risk assessment procedure, stroke risk assessment procedure, cardiovascular risk assessment protocol, heart disease risk assessment protocol, stroke risk assessment protocol, cardiovascular risk assessment criteria, heart disease risk assessment criteria, stroke risk assessment criteria, cardiovascular risk assessment standards, heart disease risk assessment standards, stroke risk assessment standards, cardiovascular risk assessment guidelines, heart disease risk assessment guidelines, stroke risk assessment guidelines, cardiovascular risk assessment recommendations, heart disease risk assessment recommendations, stroke risk assessment recommendations, cardiovascular risk assessment parameters, heart disease risk assessment parameters, stroke risk assessment parameters, cardiovascular risk assessment factors, heart disease risk assessment factors, stroke risk assessment factors, cardiovascular risk assessment elements, heart disease risk assessment elements, stroke risk assessment elements, cardiovascular risk assessment components, heart disease risk assessment components, stroke risk assessment components, cardiovascular risk assessment variables, heart disease risk assessment variables, stroke risk assessment variables, cardiovascular risk assessment indicators, heart disease risk assessment indicators, stroke risk assessment indicators, cardiovascular risk assessment measures, heart disease risk assessment measures, stroke risk assessment measures, cardiovascular risk assessment metrics, heart disease risk assessment metrics, stroke risk assessment metrics, cardiovascular risk assessment benchmarks, heart disease risk assessment benchmarks, stroke risk assessment benchmarks, cardiovascular risk assessment targets, heart disease risk assessment targets, stroke risk assessment targets, cardiovascular risk assessment goals, heart disease risk assessment goals, stroke risk assessment goals, cardiovascular risk assessment objectives, heart disease risk assessment objectives, stroke risk assessment objectives, cardiovascular risk assessment aims, heart disease risk assessment aims, stroke risk assessment aims, cardiovascular risk assessment purposes, heart disease risk assessment purposes, stroke risk assessment purposes, cardiovascular risk assessment intentions, heart disease risk assessment intentions, stroke risk assessment intentions", "meta_description_en": "The 2013 ASCVD Risk Calculator is a vital tool for estimating the 10-year risk of heart disease or stroke. Developed by the American College of Cardiology (ACC) and the American Heart Association (AHA), this calculator helps healthcare providers assess cardiovascular risk and guide management strategies. By inputting key patient data, including age, cholesterol levels, blood pressure, and smoking status, clinicians can make informed decisions about lifestyle changes and statin therapy to reduce the risk of atherosclerotic cardiovascular disease (ASCVD)." }

specialty

[ "Cardiology", "Family Practice", "Internal Medicine", "Pharmacy", "Primary Care" ]

departments

[ "Cardiac" ]

tags

[]

version_number

1

versions

[]

related

[ { "calcId": 3400, "short_title_en": "ASCVD Risk Algorithm", "slug": "ascvd-atherosclerotic-cardiovascular-disease-risk-algorithm-including-known-ascvd-aha-acc" }, { "calcId": 10499, "short_title_en": "SCORE2", "slug": "systematic-coronary-risk-evaluation-score2" }, { "calcId": 10491, "short_title_en": "PREVENT", "slug": "predicting-risk-cardiovascular-disease-events-prevent" } ]

ismed

true

section

[ "whenToUseViewed", "pearlsPitfallsViewed", "whyUseViewed", "nextStepsViewed", "evidenceViewed" ]

cleaned_departments

[ "cardiology" ]

cleaned_use

[ "Patients at risk for atherosclerotic cardiovascular disease (ASCVD)." ]

pub

false