2025 AHA／AC C科学声明：在心血管疾病 一级预防中使用风险评估指导血压管理决策_18232

AHA/ACC SCIENTIFIC STATEMENT

# Use of Risk Assessment to Guide Decision-Making for Blood Pressure Management in the Primary Prevention of Cardiovascular Disease: A Scientific Statement From the American Heart Association and American College of Cardiology

Sadiya S.Khan,MD,MSc,FAHA,FACC,Chair;Marwah Abdalla,MD,MPH,FAHA,FACC;Natalie A.Bello,MD,MPH,FACC;Ciantel A.Blyler,PharmD;Jocelyn Carter,MD,MPH; Vonne Commodore-Mensah,PhD,RSN,FAHA,FACC;Keith C.Ferdinand,MD,FAHA,FACC;Heather M.Johnson,MD,MS,MMM,FAHA,FACC;Daniel Jones,MD,FAHA;Amit Khera,MD,FAHA,FACC;Paul Muntner,PhD,FAHA;Stacey Schott,MD,MPH;Daichi Shimbo,MD;Sidney C.Smith,Jr,MD,FAHA,MACC;Sandra J.Taler,MD,FAHA;Eugene Yang,MD,MS,FACC;Donald M.Lloyd-Jones,MD,ScM,FAHA,FACC,Vice Chair; on behalf of the American Heart Association and American College of Cardiology

ABSTRACT: Risk assessment plays a central role in the primary prevention of cardiovascular disease. The 2017 High Blood Pressure Clinical Practice Guideline incorporated quantitative risk assessment for the first time to guide the initiation of antihypertensive drug therapy and recommended calculation of 10-year risk of atherosclerotic cardiovascular disease with the Pooled Cohort Equations. Although the 2025 High Blood Pressure Guideline reaffirmed this overarching paradigm for risk-based initiation of antihypertensive drug therapy, it updated the recommended risk model to the Predicting Risk of Cardiovascular Disease Events equations, which estimate 10-year risk of total cardiovascular disease(including atherosclerotic cardiovascular disease and heart failure), and defined a new risk threshold for initiation of antihypertensive therapy in patients with stage 1 hypertension. This American Heart Association/American College of Cardiology scientific statement summarizes the rationale to recommend the use of the Predicting Risk of Cardiovascular Disease Events events equations, the evidence base for the new threshold of 10-year risk of cardiovascular disease of≥7.5%, and the population-level implications of these revised recommendations. This scientific statement also offers practical advice for implementing risk assessment as the first step in the comprehensive approach to hypertension management with shared decision-making between patients and clinicians. Remaining gaps in awareness and treatment of hypertension underscore the need for innovative strategies to improve implementation of and adherence to risk-based guideline recommendations, including automation of risk assessment in electronic health records, decision-support aids, and refinement of risk assessment, to equitably improve the initiation of antihypertensive drug therapy, blood pressure control, and outcomes.

Key Words: AHA/ACC Scientific Statements■blood pressure cardiovascular diseases heart failure kidney diseases primary prevention stroke

risk assessment is central in the contemporary R approach to primary prevention of cardiovascular disease(CVD). When the Third Adult Treatment Panel cholesterol guideline first adopted risk scoring into clinical practice recommendations with the Framingham coronary heart disease risk score in 2001,1 the goal was

initially to match lipid-lowering recommendations with a patient's absolute risk for coronary heart disease. ${}^{2}$ Over time, recommendations to use risk-based approaches for the prevention of CVD have increased in clinical prac-tice guidelines, and today, risk equations are available that integrate a broader set of predictors and CVD end

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points. Guidelines now also incorporate various consid-erations into their recommendations, including relative and absolute benefits, potential for adverse effects, and cost-effectiveness, for the growing number of preven-tive therapies.3-7 Consequently, risk-based assessment for the primary prevention of CVD starts with quantitative risk estimation and then incorporates individual patient-specific factors(ie, risk-enhancing factors) and patient preferences to guide patient-clinician discussions and shared decision-making. This approach is designed to direct drug therapy with its potential for side effects and attendant costs to those at higher risk who are most likely to benefit(ie, greater absolute risk reduction[ARR]),resulting in the most cost-effective and efficient approach to reduce CVD risk(lower number needed to treat).

Although the initial framework for risk-based preven-tion was developed in the context of cholesterol manage-ment(Third Adult Treatment Panel2 and reaffirmed in the 2013 American College of Cardiology/American Heart Association[ACC/AHA] Cholesterol Guideline5 and the 2018 AHA/ACC Cholesterol Clinical Practice Guideline6 for lipid-lowering therapy), recommendations on the use of quantitative risk estimation for blood pressure(BP)management were introduced in the 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/PhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults.7 Spe-cifically, the 2017 High Blood Pressure Clinical Practice Guideline recommended the use of BP-lowering medica-tions for patients with stage 1 hypertension(systolic BP 130-139 mmHg or diastolic BP 80-89 mmHg)“with an estimated 10-year atherosclerotic CVD(ASCVD) risk of 10% or higher?7 In designing this recommendation,the guideline writing committee examined evidence from meta-analyses of study-level and participant-level clinical trial data.8-10 To estimate risk, the 2017 High Blood Pres-sure Clinical Practice Guideline recommended use of the Pooled Cohort Equations(PCEs) that were available at the time to estimate 10-year ASCVD risk and to set the threshold for initiating antihypertensive drug therapy for individuals with stage 1 hypertension at 10%, which was judged to be equivalent to the Framingham General Risk Score of≥15%, which was part of the inclusion criteria of SPRINT(Systolic Blood Pressure Intervention Trial).a

The goals of this document are to describe the revised framework for CVD risk assessment of the 2025 AHA/ACC/AANP/AAPA/ABC/ACCP/ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM Guideline for the Prevention,Detection, Evaluation, and Management of High Blood Pressure in Adults11 to initiate antihypertensive therapy(Figure 1), to discuss the evidence to support the selec-tion of the more contemporary PREVENT equations for quantitative risk assessment,12 and to provide the ratio-nale for using a PREVENT 10-year risk estimate of≥7.5%for total CVD events(ASCDV and heart failure[HF]) for initiating BP-lowering drug therapy in stage 1 hyperten-

sion(systolic BP 130-139 mmHg or diastolic BP 80-89 mmHg). It is intended to enhance the uptake of risk assessment in clinical practice by explaining and expand-ing on the rationale underlying updated recommenda-tions for risk assessment with PREVENT and risk-based decision-making for initiation of antihypertensive therapy.The scientific statement concludes with additional con-siderations for optimal implementation of the 2025 High Blood Pressure Guideline in clinical practice and future directions to improve risk-based preventive strategies for hypertension management and to address the growing burden of morbidity and mortality attributable to high BP.

# INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY FOR STAGE 2 HYPERTENSION

Observational data, clinical trials, and meta-analyses of individual-level participant data demonstrate a reduc-tion in CVD event rates with initiation of antihypertensive therapy for all adults with stage 2 hypertension(average systolic BP≥140 mmHg or diastolic BP≥90 mmHg).This includes those with prevalent CVD(secondary pre-vention) and those without CVD(primary prevention).13-15 Therefore, for adults with and without CVD, initiation of drug therapy coupled with lifestyle modification is rec-ommended for those with an average systolic BP≥140 mmHg or diastolic BP≥90 mmHg to reduce BP and the risk of CVD with a Class of Recommendation 1 and Level of Evidence A,716,17 This recommendation is unchanged from the 2017 High Blood Pressure Clinical Practice Guideline,7 This is also supported by the growing body of evidence for the benefit of BP-lowering on non-CVD out-comes, including the prevention of cognitive decline and all-cause death.18-21

# RISK-BASED INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY FOR STAGE 1 HYPERTENSION

Adults with stage 1 hypertension(systolic BP 130-139 mm Hg or diastolic BP 80-89 mm Hg) include a hetero-geneous group of individuals with a broad range of CVD risk. The 2025 High Blood Pressure Guideline recom-mends initiation of antihypertensive treatment for those with stage 1 hypertension who are at increased CVD risk for whom treatment can confer a clinically meaningful ARR. Four major benefit groups were identified from robust and consistent evidence as those who have the potential for a clinically meaningful benefit and thus for whom antihypertensive therapy is recommended in stage 1 hypertension.These include patients with(1) prevalent CVD(secondary prevention),(2) diabetes,(3) chronic kidney disease(CKD) defined as estimated glomeru-lar filtration rate<60 mL·min-1.73 m-2 or albuminuria>30 mg/g, and(4) estimated 10-year risk for total CVD

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Indication for Initiation of Risk-Based Approach to Initiation of Antihypertensive Drug Therapy Ific and Antihypertensive Drug Therapy(≥140/90 mm Hg)Initiate 2 or more antihypertensive Drug therapy in the 140/90 mm Hg?YES Is the average drug therapy medications to lower BP BP≥140/90 mm Hg?for primary or secondary prevention of CVD(COR 1)Initiate antihypertensive drug therapy of 150/90 mm Hg?YES Initiate antihypertensive drug therapy of 150/90 mm Hg?Does the patient have existing medications to lower BP for secondary clinical CVD(CHD, stroke, HF)?prevention of CVD(COR 1)NO Is the patient at increased YES Is the average drug therapy medications to lower BP for secondary PVD(SOR 1)(130-139 or 80-89 mm Hg?YES[130-139 or 80-89 mm Hg]Initiate antihypertensive drug therapy of 150/90 mm Hg?YES Initiate antihypertensive drug therapy of 150/90 mm Hg?YES the patient at increased medications to lower BP for secondary PVD(SOR 1)(130-139 or 80-89 mm Hg]Before the counter pain prevention of CVD(COR 1)NO IS the patient at increased losses of the 139 or 80-89 mm Hg?YES Its the patient at increased medications to lower BP for primary PVD(SOR 1)(130-139 or 80-89 mm Hg]Before the counter pain prevention of CVD(COR 1)Non and the 139 or 80-89 mm Hg?

Figure 1. Comprehensive risk-based framework according to hypertension stage and risk assessment for the initiation of antihypertensive therapy according to the 2025 High Blood Pressure Guide with the use of the PREVENT-CVD equation.*BP indicates blood pressure; CHD, coronary heart disease; CKD, chronic kidney disease; COR, Class of Recommendation; CVD, cardiovascular disease; HF, heart failure; HTN, hypertension; and PREVENT, Predicting Risk of Cardiovascular Disease Events.*The PREVENT calculator is available online at https://professional.heart~/guidelines-and-statements/prevent-calculator.

(ASCVD and HF)≥7.5% by the PREVENT equations for the primary prevention of CVD(Figure 1).12225.257

Many US adults with stage 1 hypertension are eligible for initiation of drug treatment for BP lowering on the basis of only comorbidities. Nationally representative data from NHANES(National Health and Nutrition Examina-tion Survey) estimate that 7% have a history of CVD,9% have diabetes, and 9% have CKD.28 Observational studies demonstrate that people with any 1 of these 3 conditions compared with individuals without these con-ditions have a substantially higher risk for future CVD events.29,30 In addition, randomized clinical trial data and meta-analyses support that adults with CVD,31,32 die-tes,33 and CKD34,35 represent a risk-enriched subset of the population with significant benefit from the initiation of BP-lowering drug therapy.

# Quantitative Risk Assessment for the Initiation of Antihypertensive Drug Therapy

In adults with stage 1 hypertension without CVD, diabetes,or CKD, quantitative risk assessment can further iden-tify individuals who may have a greater absolute benefit from the initiation of BP-lowering drug therapy. Multivari-

able risk prediction tools have evolved considerably over the past 3 decades in the United States from the original Framingham coronary heart disease risk score1,36 to the Framingham Risk Score(general CVD)37 to the PCEs38 to PREVENT.12 Table 1 briefly summarizes the Framingham Risk Score(for general CVD), PCEs, and PREVENT equa-tions, including the populations, predictors, and outcomes included in their development. After evaluating the available evidence base of existing risk tools, the 2025 High Blood Pressure Guideline Writing Committee11 determined that the PREVENT equations12 were the preferred approach to calculate CVD risk and to guide initiation of antihyper-tensive therapy for several reasons:(1) the development of PREVENT in a large, contemporary, representative US sample;(2) superior discrimination and calibration of PRE-VENT compared with the PCEs; and(3) the expansion of the predicted outcome to the more relevant outcome of total CVD(a composite of ASCVD and HF).

# Development and Application of the PREVENT Equations

In 2023, a gap analysis performed by the AHA identified several opportunities to improve current risk assessment

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Table 1. Overview of Multivariable Risk Prediction Models for CVD

||Framingham Risk Score(FRS)|Pooled Cohort Equations(PCEs)|Predicting Risk of CVD EVENTS(PREVENT)*| |---|---|---|---| |Baseline Years|1968-1987|1968-1995|1992-2022| |Derivation Cohorts|FHS FOF|FHS FONFOC CARDIA CHS|FRIC CARDIA CHS UHS MESA Geisinger Optum| |Derivation N|8491|24626|3281919| |Male,N|3969|10745|1442091| |White male,%|↑|85|80| |Black male,%|↑|15|8.0| |Hispanic male,%|↑|0|5.3| |Asian male,%|↑|0|2.5| |Other race and ethnicity,%|↑|0|4.6| |Female, N|4522|13881|1839828| |White female,%|↑|81|78| |Black female,%|↑|19|10| |Hispanic female,%|↑|0|6.0| |Asian female,%|↑|0|2.6| |Other race and ethnicity,%|↑|0|4.1| |Age Range|30-74 y|40-79 y|30-79 y| |Stratification|Sex|Sex Self-identified Black or White Race|Sex| |Predictors|Age|Age|Age| |Predictors||Total cholesterol High density lipoprotein-cholesterol|Non-high density lipoprotein cholesterol High density lipoprotein-cholesterol| ||Systolic blood pressure Diabetes Smoking Antihypertensives|Systolic blood pressure Diabetes Smoking Antihypertensives|Systolic blood pressure Diabetes Smoking Antihypertensives Statin treatment Estimated glomerular filtration rate Urine albumin to creatinine ratio# Hemoglobin A1C# Social deprivation indexS| |Outcomes|CVD(defined as fatal or nonfatal coronary heart disease,angina,stroke,transient ischemic attack, peripheral artery disease, and heart failure)|ASCVD(nonfatal myocardial infarction or coronary heart disease death, or fatal or nonfatal stroke)|Total CVD(nonfatal or fatal coronary heart disease, stroke, and heart failure) ASCVD HF| |Prediction Time Horizon|10-y|10-y|10-y 30-yS|

ARIC indicates Atherosclerosis Risk in Communities Study; ASCVD, atherosclerotic cardiovascular disease; BP, blood pressure; CARDIA, Coronary Artery Risk Devel-opment in Young Adults; CHS, Cardiovascular Health Study; CVD, cardiovascular disease; FHS, Framingham Offspring Study; HF,heart failure; JHS, Jackson Heart Study; MESA, Multi-Ethnic Study of Atherosclerosis; PCE, Pooled Cohort Equation; and PREVENT, Predicting Risk of Cardiovascular Disease Events.

*The PREVENT equations developed separate outcome-specific models for total CVD(composite of ASCVD or HF), ASCVD, or HF. The High Blood Pressure Guideline and this scientific statement use the PREVENT-CVD equations.

tRace and ethnicity were not reported but nearly all Framingham participants were non-Hispanic White

Optional predictors included in add-on PREVENT equations

Model developed with age as a time scale to enable longer-term risk estimates

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CLINICAL STATEMENTS AND GUIDELINES

tools, which led to the development of the sex-specific PREVENT equations as an update to the PCEs.39 Three key areas were identified:(1) the need for risk equations based on contemporary, diverse datasets that include in-dividuals who are representative of the patient population intended for use,(2) incorporation of predictors and out-comes relevant to the growing burden of CKD and HF,40 and(3) expansion to include younger adults starting at 30 years of age with a longer time horizon for estimated risk.12 The derivation sample for the PREVENT equations in-cluded 25 datasets with individual data or estimated data of 328191 adults without CVD at baseline. The outcomes predicted include total CVD(defined as composite of ASCVD and HF) and ASCVD and HF individually. PREVENT enabled 10-year risk estimation for adults 30 to 79 years of age and 30-year risk estimation for adults 30 to 59 years of age. Given the growing recognition of risk related to kid-ney, metabolic, and social determinants of health(SDOH),PREVENT also included optional models with markers of end-organ kidney damage(urine albumin creatinine ra-tio), metabolic dysfunction(hemoglobin A1c), and social risk(mesured by the Social Deprivation Index, which is publicly available online at https://www.graham-center.org/maps-data-tools/social-deprivation-index.html). It is important to note that PREVENT included only predictors that are already routinely measured in clinical practice and should be readily available to primary care clinicians. There-fore,PREVENT is primed for adoption into clinical practice through automated calculation and within decision-support tools in electronic health record(EHR) platforms.

For people with stage 1 hypertension, the predicted 10-year total CVD(ASCVD and HF) risk from PREVENT can differ markedly on the basis of age and risk factor levels, as has been reported from nationally representa-tive samples.41 The use of risk assessment with PRE-VENT and how differences in predicted CVD risk can guide hypertension management in clinical practice are demonstrated in 2 hypothetical patients who both have stage 1 hypertension in Figure 2.

External Validation of the PREVENT Equations

External validation of any risk assessment tool is vital to ensure that the model performs reliably and accurately in its intended or target population.42 Moreover, vali-dated models are more trusted by clinicians, which sup-ports their adoption.43 External validation of PREVENT was performed before publication and dissemination in 3330085 individuals from 21 distinct datasets who were not included in the derivation and represented participants with broad geographic, socioeconomic, racial, and ethnic diversity.In the external validation, the C statistics ranged from 0.74 to 0.89 and the calibration slope(observed ver-sus predicted risk) ranged from 0.89 to 1.09, indicating consistently high discrimination and close alignment be-tween observed event rates and predicted risk.12

This is a far more rigorous and extensive assessment than has been performed for the PCEs or other prior CVD risk equations to date.The development datasets for PRE-VENT included both observational research cohorts and real-world clinical data from EHR-based datasets, which resulted in broad geographic representation from all US census regions and place-based socioeconomic diversity,with 26% of the sample residing in a highly deprived zip code according to the highest tertile of the Social Depri-vation Index.12 The validation sample also had substantial racial and ethnic diversity, with 2632236 million White adults,311209 Black adults,131247 Hispanic adults,and 80139 Asian adults in the external validation. For the first time, Hispanic adults and Asian adults were included in the development of US risk prediction equations.However, the proportions of Hispanic adults and Asian adults in the datasets in PREVENT development were lower than the proportion in the US population. This is particularly important given the heterogeneity in CVD risk observed in these populations,44,45 with prior work demon-strating poor calibration of PCEs among Asian individuals and Hispanic individuals.46,47 However, PREVENT dem-onstrated significantly better calibration(Supplemental Table 1) and discrimination(Supplemental Table 2) in the external validation sample in each racial and ethnic group when directly compared with the PCEs.

In addition to the external validation performed as part of the development of PREVENT, several investigations have examined the performance of the PREVENT equations in US(regial health systems)48,49 and non-US(UK Bio-bank) datasets.50 These have resulted in similar findings,demonstrating good discrimination and calibration overall and among evaluated racial and ethnic groups(Table 2).Although the available data including>4,3 million adults support the accuracy and precision of PREVENT, ongo-ing studies should continue to assess model performance in diverse US samples with careful attention to popula-tions traditionally underrepresented in research studies(eg, racial and ethnic underrepresented groups[American Indian individuals and Alaska Native individuals, Asian indi-viduals, and Hispanic individuals^{[51]}, low socioeconomic sta-tus,uninsured). It is important to note that even if predicted risk is underestimated, adults with stage 1 hypertension and a predicted 10-year CVD risk with PREVENT<7.5%are still eligible for antihypertensive drug treatment after a 3- to 6-month trial of lifestyle modification(Class of Rec-ommendation 1; Level of Evidence B-R recommendation).

RATIONALE FOR PREVENT-BASED 10-YEAR CVD RISK THRESHOLD≥7.5% FOR INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY IN STAGE 1 HYPERTENSION

The development of the new PREVENT equations re-quired the guideline writing committee to evaluate the

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Patient Scenario A Initial Visit: A 35-year-old woman presents for an initial visit to consider antihypertensive therapy due to an elevated Intel Vis: A 35-year-old woman presents for an initial visit to consider antihypertensive therapy due to an elevated BP reading obtained at a community fair. A friend recently learned heart failure, and he is concerned about his risk.Past Medical History: G2P2 with uncomplicated pregnancies) failure, and he is concerned about his risk.(no hypertensive disorders of pregnancy)CVD Risk factors: no tobacco exposure, no history of Current medications: None Physical Examination: Body mass index 32 kg/m2;Systolic blood pressure: None Systolic blood pressure 132 mm Hg, unremarkable Clsbolic pulmonary exam(Bad data: total cholesterol 160 mg/dL, High-density lipoprotein chaloipmonary exam.Lab data: total cholesterol 160 mg/dL, High-density lipoprotein cholesterol 50 mg/dL; eGFR 55 ml/min/1.73m2 Electrocardiogram: normal sinus rhythm, normal axis, and normal QRS voltage voltage in precordial loansx, S (S in V1+ R in V5= 38 mm), and left axis deviation The clinician begins by estimating the patient's 10-year risk for CVD based on the PREVENT equations.The clinician begins by estimating the patient's 10-year risk for CVD based on the PREVENT equations.The clinician explains that this means that this means that if we 10-year risk for CVD based on the PREVENT equations.Lab data: total cholesterol 160 mg/dL, High-density lipoprotein cholesterol 50 mg/dL; eGFR 55 ml/min/1.73m2 Electrocardiogram: normal sinus rhythm, normal axis, and The clinician provides important information on lifestyle changes(DASH eating pattern, reducing sodium intake, voltage in precordial loansxk images of normal sinus rhythm, normal axis, and regular physical activity) and weight loss of at least 5% of body weight to reduce her risk. They agree to re-assess the body weight to lower his risk.Follow-Up Visit: The patient returns for a follow-up visit. She They review the considerations for starting a single has been unsuccessful with weight loss and her systolic BP is today is similar at 135 mm Hg. The clinician discusses the options for initiation of antihypertensive therapy for Stage 1 hypertension given elevated BP even after a trial of lifestyle and the following paper on PREVENT and evidence of left therapy. They consider the pros and cons and the patient's ventricular hypertrophy on electrocardiogram. They consider the preferences in a shared and the potential to initiate antihypertensive drug therapy with a single and the patient's preferences in a shared and the following paper on prevent and evidence of left with the goal of lowering BP and reducing her cumulative action to elevated BP over her life course. Follow-up exposure to elevated BP over her life course. Follow-up is scheduled in 2-4 weeks to review her home BP CVD. Follow-up is scheduled in 2-4 weeks to review her home BP readings, assess office BP, and evaluate for any side effects of treatment.

Figure 2. Two hypothetical clinical scenarios of patients diagnosed with stage 1 hypertension integrating PREVENT-based risk assessment for shared decision-making on initiation of antihypertensive therapy.

These 2 cases highlight common clinical scenarios representing 2 patients presenting with the same high blood pressure(BP) in the stage 1 hypertension range who have different absolute risks for cardiovascular disease(CVD) using the PREVENT-CVD equations. The initial clinical encounter and follow-up encounter identify how guideline-recommended approaches can be implemented to reduce the risk of high BP.The PREVENT calculator is available online at https://professional/ear/guidelines-and-stements/prevent-calculator. CKD indicates chronic kidney disease; DASH, Dietary Approaches to Stop Hypertension; eGFR, estimated glomerular filtration rate; G2P2, gravida 2, para 2; and PREVENT, Predicting Risk of Cardiovascular Disease Events.

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Table 2.Summary of Selected External Validation Investigations of the PREVENT Risk Prediction Equations

|$$\text{ Population sample overview}$$|Model performance|Model performance|||||| |---|---|---|---|---|---|---|---| |Validation sample/ cohort|N|Racial and ethnic composition (as reported in the study),%|Geographic location|Baseline year(s)|C statistic(95% CI)|Calibration slope (95% CI)|| |PREVENT External Validation12|3330085|Hispanic adults,3.9|United States|1999-2022|Female|Female|| |PREVENT External Validation12|3330085|Non-Hispanic Asian adults,2.4|United States|1999-2022|Female|Female|| |PREVENT External Validation12|3330085|Non-Hispanic Black adults,9.3|United States|1999-2022|||| |PREVENT External Validation12|3330085|Non-Hispanic White adults,79.0|United States|1999-2022|Male|Male|0.94| |PREVENT External Validation12|3330085|Other race or ethnicity,5.1|United States|1999-2022|Male|Male|0.94| |UK Biobank50|388224|Asian or Asian British adults,1.7|United Kingdom|2006-2010|0.74|1.03|| |UK Biobank50|388224|Black or Black British adults,1.6|United Kingdom|2006-2010|0.74|1.03|| |UK Biobank50|388224|Chinese adults,0.6|United Kingdom|2006-2010|0.74|1.03|| |UK Biobank50|388224|Multiracial adults,0.9|United Kingdom|2006-2010|0.74|1.03|| |UK Biobank50|388224|Other ethnic groups,0.9|United Kingdom|2006-2010|0.74|1.03|| |White adults,94.9|||||||| |Integrated health system in New England(Mass General Brigham)48|38137|Asian adults,2.5|Boston,MA|1997-2006|0.72|Slope not reported (observed,7.2%; predicted,7.5%)|| |Integrated health system in New England(Mass General Brigham)48|38137|Black adults,5.6|Boston,MA|1997-2006|0.72|Slope not reported (observed,7.2%; predicted,7.5%)|| |Integrated health system in New England(Mass General Brigham)48|38137|Hispanic adults,3.7|Boston,MA|1997-2006|0.72|Slope not reported (observed,7.2%; predicted,7.5%)|| |Integrated health system in New England(Mass General Brigham)48|38137|White adults,82|Boston,MA|1997-2006|0.72|Slope not reported (observed,7.2%; predicted,7.5%)|| |Integrated health system in New England(Mass General Brigham)48|38137|Other, 5.9(including American Indian, multiracial, unspecified, and unrecorded)|Boston,MA|1997-2006|0.72|Slope not reported (observed,7.2%; predicted,7.5%)|| |Kaiser-Permanente Southern California49|559241|Hispanic adults,31.7|Southern California|2009|0.74|0.97|| |Kaiser-Permanente Southern California49|559241|Non-Hispanic Asian adults,10.5|Southern California|2009|0.74|0.97|| |Kaiser-Permanente Southern California49|559241|Non-Hispanic Black adults,10.6|Southern California|2009|0.74|0.97|| |Kaiser-Permanente Southern California49|559241|Non-Hispanic White adults,42.9|Southern California|2009|0.74|0.97||

PREVENT indicates Predicting Risk of Cardiovascular Disease Events.

Based on a review of the published peer-reviewed studies, this table summarizes 4 external validation studies, including the 1 study performed as part of the develop-ment.For each validation sample, we report the sample size(N),radial and ethnic composition included, geographic location, study period, and model performance metrics.Model performance was assessed with discrimination(C statistic with 95% Cls) and calibration(observed to predicted slope).These data demonstrate the generalizability of PREVENT models in a variety of diverse settings and samples.

available data to determine the PREVENT-based risk threshold for the initiation of antihypertensive therapy. In general, data from randomized controlled trials(RCTs),including risk-based inclusion criteria, event rates in pla-cebo and intervention groups, rates of adverse events re-lated to therapy, and even cost-effectiveness data, should be rigorously evaluated to determine optimal decision thresholds for each risk model and preventive therapy.These concepts have been discussed in greater detail elsewhere in the context of the PCEs for lipid-lowering therapy.4,38,52 As with the 2017 High Blood Pressure Clinical Practice Guideline, the 2025 High Blood Pres-sure Guideline Writing Committee undertook these same strategies and deliberated extensively to ensure that rec-ommendations aligned with RCT evidence for net clini-cal benefit and to understand the impact of different risk thresholds on the numbers and proportions of people considered for BP-lowering therapy in the population.

The risk threshold for initiation of antihypertensive drug therapy in the 2017 High Blood Pressure Clinical Practice Guideline relied on older risk models with the Framing-

ham Risk Score and the PCEs.67 Although the overarching therapy for stage 1 hypertension remained consistent in the 2025 High Blood Pressure Guideline, the decision to select a new risk model resulted in the need to determine the appropriate equivalent predicted risk thresholds when using PREVENT.The new threshold for defining increased risk in the 2025 High Blood Pressure Guideline was determined on the basis of(1) RCT data that included dis-tribution of predicted risk, subgroup analyses by predicted risk, and mean event rates;(2) population-level predicted risk distributions to support equivalent risk thresholds across risk prediction models; and(3) population-level implications of the 2025 High Blood Pressure Guideline-selected risk threshold. This comprehensive approach is consistent with the selection of decision thresholds for the initiation of preventive drug therapy in the earlier 2017 High Blood Pressure Guideline,7 as well as the 2018 AHA/ACC Guideline on the Management of Blood Cholesterol6 and the 2019 CVD Primary Prevention Clinical Practice Guideline.3

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RCT Evidence for Risk-Based Initiation of Antihypertensive Drug Therapy

Initiation of antihypertensive therapy for stage 1 hy-pertension has been studied in several large RCTs.15,31 Although many of these trials included patients with or without clinical CVD, some such as SPRINT included risk-based inclusion criteria.53 Specifically, SPRINT tested the efficacy of intensive BP-lowering to a tar-get<120 mmHg compared with standard care of<140 mmHg and included individuals without baseline CVD but at high risk for CVD defined by a Framingham Risk Score≥15%.8 Of the 9361 individuals enrolled in SPRINT,7103(76%) were enrolled on this basis.SPRINT selected the Framingham Risk Score(general CVD) for its risk-based inclusion criterion because it was the most contemporary risk model at the time of study design. Prespecified subgroup analyses in the SPRINT sample without baseline CVD demonstrated similar risk reduction in the primary outcome among those without CVD(hazard ratio, 0.75[0.58, 0.96]) compared with those with CVD(hazard ratio, 0.70[95% CI, 0.48-1.02];P=0.78). Subsequent post hoc analyses per-formed by baseline Framingham Risk Score,54 older risk prediction scores for HF55 or baseline measurement of cardiac biomarker levels(natriuretic peptides, troponin)56 have demonstrated consistent relative effects across risk strata for intensive BP lowering. Consequently, the consistent relative risk reduction across different risk levels translates into a higher absolute benefit or ARR in those with higher risk, supporting a risk-based approach to treatment initiation.

Similar results were observed in the STEP trial(Strat-egy of Blood Pressure Intervention in the Elderly Hyper-

tensive Patients), which enrolled 8511 patients with hypertension to test the effect of a systolic BP goal of 110 to<130 mm Hg versus 130 to<150 mm Hg.57 This trial did not require a minimal CVD risk profile but was enriched for this, with 61% of the total trial population estimated to have a baseline Framingham Risk Score≥15%. Prespecified subgroup analyses by the baseline Framingham Risk Score demonstrated greater benefit in those with a Framingham Risk Score≥15%(hazard ratio,0.66[95% CI, 0.50-0.86]) compared with nonsignificant benefit of intensive BP lowering for those with scores<15%(0.96[95% CI, 0.62-1.49]). Taken together,these data support a risk-based approach and the use of a decision threshold equivalent to Framingham Risk Score≥15% 10-year risk.

As part of the guideline writing committee delibera-tions for this scientific statement, 10-year CVD risk esti-mates were calculated with the PREVENT base model and compared with risk estimates calculated from the Framingham Risk Score(general CVD) and PCEs among SFRint participants without baseline CVD(Supplemen-tal Methods provides additional details). The distribu-tion of predicted risk according to the Framingham Risk Score,PCEs,and PREVENT is displayed in Figure 3 and demonstrates that the absolute risk estimates calculated with Framingham Risk Score and PCEs in SPRINT par-ticipants that with PREVENT, as expected with Framingham Risk Score and PCEs in SPRINT par-ticipants are higher than with PREVENT, as expected.However, there is substantial overlap, and the majority of SPRINT participants had a PREVENT-CVD 10-year CVD risk≥7.5%(85%).Therefore, a PREVENT 10-year CVD risk estimate≥7.5% was determined to be a reason-able risk threshold that is consistent with the inclusion criteria applied in SPRINT. Moreover, a PREVENT risk threshold of 7.5% translates into an ARR of≈1.9% at

 Figure 3. Distribution of predicted 10-year risk estimates applying PREVENT-CVD, PCEs for ASCVD, and Framingham Risk Score in participants enrolled in SPRINT*:

This figure displays the probability density distribution of predicted 10-year cardiovascular disease(CVD) risks according to the Predicting Risk of Cardiovascular Disease Events(PREVENT), Pooled Cohort Equations(PCEs), and Framingham Risk Score models. The x axis represents the 10-year risk estimate, and the y axis shows the probability density. The kernel density plot provides a smoothed representation of the distribution with the area under the curve of 1. ASCVD indicates atherosclerotic cardiovascular disease; and SPRINT, Systolic Blood Pressure Intervention Trial.*Data for this analysis comprised baseline participants in SPRINT without clinical CVD, with dashed lines representing 10-year predicted risks of 7.5%,10%,and 15%.Supplemental Methods provides additional details.

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10 years based on the SPRINT relative risk reduction of 0.25, which is consistent with prior recommendations for 10-year ARR thresholds for lipid-lowering therapy. ${}^{58,59}$

Population-Based Crosswalk of Risk Estimates Across Prediction Models

Application of different CVD risk prediction models in the same individual can result in different absolute risk esti-mates.60 This can be explained by differences in the pre-dictors selected, end points included, and time period of the development dataset. As risk models evolve, compar-ing the distribution of absolute risk estimates with each model in a nationally representative sample of US adults can be helpful to inform a population-based crosswalk and to enable harmonization across models and guide-line recommendations. Therefore, data from NHANES 2011 to March 2020 were analyzed to determine the distribution of risk estimates when PCEs and PREVENT were applied in the US population by sex(Supplemental Figure 1) and by race and ethnicity(Supplemental Fig-ure 2). The largely overlapping distribution in the popula-tion of PCEs and PREVENT is consistent with the high correlation of PCEs and PREVENT-CVD in NHANES(0.89). This is also similar to the correlation reported in the PREVENT development datasets(0.91)12(Supple-mental Methods provides additional details).

A complementary population-based approach to further support the crosswalk between models is cal-culation of population-based percentiles. The absolute risk estimates for Framingham Risk Score, PCEs, and PREVENT corresponding to a range of population-based percentiles(5th-95th percentiles) among US adults who are eligible for initiation of antihypertensive therapy are shown in Table 3. This demonstrates that a general Framingham Risk Score≥15% and PCEs score

≥10% are roughly equivalent to a PREVENT-CVD risk≥7.5%. All the selected levels of predicted risk from the various models(Framingham Risk Score,≥15%;PCEs,≥10%; and PREVENT,≥7.5%) also coincide in the range of the 75th percentile of the contemporary US population. This is clinically meaningful because the 75th percentile has been identified in other pri-mary prevention guidelines as a decision threshold to consider initiation of preventive therapy(eg, coronary artery calcium scores).

Potential Population-Level Implications of the 2025 Guideline

Defining the potential implications on the population level of the 2025 High Blood Pressure Guideline rec-ommendations for risk-based BP lowering is important for implementation planning by key stakeholders(eg,clinicians, health systems, and policymakers). There-fore, we calculated the number of US adults with stage 1 hypertension who would be eligible for anti-hypertensive drug therapy according to the 2025 High Blood Pressure Guideline and the new risk threshold of 10-year CVD risk using PREVENT≥7.5% and com-pared this with the 2017 High Blood Pressure Clini-cal Practice Guideline with the older risk threshold of 10-year ASCVD risk using PCEs 10%. The number and characteristics of US adults currently on antihyper-tensive therapy and with hypertension are described in Supplemental Table 3. More than 41 million US adults are already on antihypertensive drug therapy, and an-other nearly 16 million have stage 2 hypertension(sys-tolic BP≥140 mmHg or diastolic BP≥90 mmHg) and are eligible for antihypertensive drug therapy. Among those with stage 1 hypertension, further details on the percentage and number of US adults indicated for

Table 3. Population-Based Percentile of 10-Year Risk in US Adults Without CVD Eligible for Antihypertensive Drug Therapy

|US population percentile|10-y Risk estimates from multivariable risk equations(%)||| |---|---|---|---| |US population percentile|Framingham Risk Score|PCEs for ASCVD|PREVENT for CVD| |5th|1.0|0.5|0.4| |10th|1.5|0.8|0.6| |25th|2.9|1.9|1.2| |50th|6.5|5.1|3.2| |73rd|12.8|10.8|7.5| |75th|13.7|11.6|8.0| |90th|24.1|21.4|15.1| |95th|32.6|29.2|20.0|

ASCVD indicates atherosclerotic cardiovascular disease; CVD, cardiovascular disease; PCE, Pooled Cohort Equa-tion; and PREVENT, Predicting Risk of Cardiovascular Disease Events.

The percentile of risk corresponding to estimated risk with the Framingham Risk Score, PCEs, and the PREVENT CVD equations was calculated for the primary prevention population of US adults eligible for risk assessment from NHANES(National Health and Nutrition Survey; survey cycles 2011-2012 to March 2020: n=14254 representing 138865 442 adults).

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antihypertensive drug therapy are detailed in Table 4 and Figure 4, with>5 million eligible on the basis of prevalent CVD, diabetes, or CKD. Of the remaining adults with stage 1 hypertension, those recommended for antihypertensive therapy according to the 2025 AHA/ACC High Blood Pressure Guideline recommen-dations were similar to the 2017 ACC/AHA High Blood Pressure Pressure Clinical Practice Guideline recommendations overall and by age(Supplemental Figure 3). In the small number of US adults with discordant recommendations between the 2025 AHA/ACC High Blood Pressure guideline and 2017 ACC/AHA High Blood Pressure Clinical Practice Guideline(Supplemental Figure 4), the average predicted 10-year CVD risk was low(2.6%;Supplemental Table 4), with modest, nonsignificant dif-ferences in key demographic subgroups by sex and race and ethnicity(Supplemental Table 5).

RACE IN CVD RISK AND RISK-BASED INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY

In contrast to the race-specific coefficients included in the PCEs, PREVENT did not include race as a predictor for several reasons. First, race is not a biological trait, and incorporating it as a predictor may conflate it with being a causal risk factor and confer harm.This has led to emerg-ing consensus in the medical and public health domains to remove race from care algorithms and to prioritize race-conscious perspectives in clinical decision-making.61

Second, race did not contribute to predictive utility when a larger, diverse sample was used in the model derivation. Third, the discrimination and calibration met-rics of PREVENT were tested in each racial and eth-nic group as part of the external validation. PREVENT

Table 4. Number and Percentage of US Adults Eligible for Antihypertensive Drug Therapy for Stage 1 Hypertension According to the 2017 High Blood Pressure Compliance Guideline and 2025 High Blood Pressure Guideline

|Age Groups|20-29 years|30-39 years|40-49 years|50-59 years|60-69 years|70-79 years|Overall| |---|---|---|---|---|---|---|---| |Total Number of NHANES Participants|3692|3375|3480|3443|3555|1931|19476| |Equivalent US population, N|39451465|34084449|35426319|36431288|29654218|15806871|190854611| |Stage 1 HTN (SBP 130-139 or DBP 80-89 mm Hg)|4921275|536972|6761157|6385767|3752884|1498524|28689580| |Eligible for Initiation of Antihypertensive Drug Therapy According to Both 2017 High Blood Pressure Clinical Practice Guideline and 2025 High Blood Pressure 56 Guideline|||||||| |CVD(ASCVD or HF)|16304 (0.3)|59869|193122|329406|350414 (9.3)|280547 (18.7)|1229481 (4.3)| |Diabetes or CKD|501060 (10.2)|632233 (11.8)|1034549 (15.3)|989525 (15.5)|698367 (18.6)|359368 (24.0)|4215101 (14.7)| |Additional Eligibility Indications for Initiation of Antihypertensive Drug Therapy According to 2017 High Blood Pressure Clinical Practice Guideline|||||||| |Not recommended for immediate initiation of drug therapy|4403912 (89.5)|4678051 (87.1)|5513155 (81.5)|4683438 (73.3)|1225620 (32.7)|10348 (0.7)|20514524 (71.5)| |Age>65 y|*|*|*|825318 (22.0)|771790 (51.5)|1597108 (5.6)|(5.6)| |Increased predicted 10-year ASCVD risk (PCE≥10%)|*|*|*|8253165 (17.4)|76472 (5.1)|1133367 (4.0)|| |Additional Eligibility Indications for Initiation of Antihypertensive Drug Therapy According to 2025 High Blood Pressure Guideline|||||||| |Not recommended for immediate initiation of drug therapy|4403912 (89.5)|4678051 (87.1)|5526165 (81.7)|4865507|1221849 (32.6)|0|20695484 (72.1)| |Increased predicted 10-year CVD risk (PREVENT-CVD≥7.5%)|*|0|7321 (8.1)|201330 (3.2)|1482254 (39.5)|858610 (57.3)|2549515 (8.9)|

Values are number of US adults, mean(SD), and percent accounting for complex weighting of NHANES survey sampling.

ASCVCD indicates atherosclerotic cardiovascular disease; CKD, chronic kidney disease; CVD, cardiovascular diseases; DBP, diastolic blood pressure; HF, heart failure;NHANES, National Health and Nutrition Examination Survey; PCE, Pooled Cohort Equation; PREVENT, Predicting Risk of Cardiovascular Disease Events; and SBP,systolic blood pressure.

The number and percent of US adults eligible for antihypertensive therapy for Stage 1 hypertension according to the 2017 High Blood Pressure Clinical Practice Guideline and 2025 High Blood Pressure guideline are displayed on the basis of the NHANES survey cycles 2011 to 2012 to March 2020. Both the 2017 High Blood Pressure Pressure Clinical Practice Guideline and 2025 High Blood Pressure guideline recommendation initiation of antihypertensive drug therapy for individuals with Stage 1 hyper-tension with a history of CVD, diabetes, or CKD. The 2017 High Blood Pressure Clinical Practice Guideline additional recommendation initiation of antihypertensive drug therapy for adults≥65 years of age with SBP 130 to 139 mmHg and for those with increased predicted risk with PEs score≥10%. The 2025 High Blood Pressure Guideline recommendation initiation of antihypertensive drug therapy for adults with PREVENT-CVD score≥75%.The Supplemental Material provides more detailed review of the methods.

*Not eligible

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 Figure 4. Number of US adults already on antihypertensive drug therapy or recommended for antihypertensive drug therapy

Figure 4. Number of US adults already on antihypertensive drug therapy or recommended for antihypertensive drug therapy initiation according to the 2025 High Blood Pressure Guideline and 2017 High Blood Pressure Clinical Practice Guideline.7.11 The graph shows the number of US adults already on antihypertensive drug therapy and those eligible for antihypertensive drug therapy initiation with similar numbers according to the 2017 High Blood Pressure Clinical Practice Guideline in 2025 High Blood Pressure Guidelines(N=66212313). Individuals with stage 2 hypertension or with a history of cardiovascular disease(CVD), diabetes, or chronic kidney disease(CKD)are recommended for antihypertensive drug therapy in both the 2017 High Blood Pressure Clinical Practice Guideline and 2025 High Blood Pressure Guidelines(Guideline. For those with increased predicted risk, the 2017 High Blood Pressure Practice Guideline in 2025 Other guidelines is not recommended a PREVENT-CVD score of≥7.5%. HTN indicates hypertension.

demonstrated similar model performance in each racial and ethnic group and better performance relative to the race-specific PCEs(Supplemental Tables 1 and 2).12,39

In addition to ensuring a broadly diverse and represen-tative sample for development, the PREVENT equations incorporated the Social Deprivation Index, a place-based measure of SDOH similar to what has been included in the UK risk score.62 The optional Social Deprivation Index PREVENT model(derived from a person's 5-digit zip code) showed a modest improvement in the C sta-tistic compared with the base PREVENT model in the validation(0.001-0.002) with similar calibration slopes across race and ethnic groups(0.72-1.10). Although this represents an important step forward in assessing and addressing SDOH as part of risk assessment and prevention of CVD, additional SDOH measures or direct measures of perceived discrimination that may be help-ful when considering risk assessment should be con-sidered. For example, direct measures of bias or racial discrimination may inform CVD risk; in a study of 1845 Black participants, lifetime discrimination was associ-ated with a higher risk of incident hypertension. ${}^{63}$

It is important to note that the absence of race and ethnicity as a predictor in the PREVENT equations does

not imply that racial disparities in CVD or racism does not exist, nor should it minimize the urgent need to address these health disparities. In the United States, non-Hispanic Black adults experience substantially higher risk of hypertension, earlier onset of hypertension, and greater prevalence of hypertension-related adverse out-comes compared with White adults.64 Moreover, con-trol rates of hypertension remain substantially lower in non-Hispanic Black adults(especially men) and His panic adults, contributing to worse outcomes.64 In non-Hispanic Black women, rates of hypertensive disorders of pregnancy are substantially higher and are a leading contributor to adverse maternal and neonatal outcomes,potentially perpetuating intergenerational health dis-parities.65,66 These pervasive inequities are attributable to multiple interrelated adverse SDOH, including socioeco-nomic factors, explicit and implicit bias in patient-clinician relationships, and barriers in high-quality health care access.67-69 As a result, race is a powerful marker of CVD risk that represents differences in SDOH, structural rac-ism, and myriad lived experiences.69 Indeed, when SDOH are accounted for, the Black-White difference in incident CVD and CVD mortality is almost completely attenu-ated.71,72 Higher rates of hypertension and other CVD

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CLUNICAL STATEMENTS AND GUDEVALDENLES

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risk factors included in PREVENT translate into higher CVD risk estimates with PREVENT for non-Hispanic Black adults compared with White adults.73 However, less is known about the social drivers of differences in CVD risk among disaggregated Asian groups and Hispanic groups, which warrants increased attention.45,51,74

HOLISTIC RISK ASSESSMENT BEYOND QUANTITATIVE RISK ESTIMATION

Risk assessment is the first step in the primary preven-tion of CVD to identify individuals who are most likely to have a CVD event.10 In an analysis of adults with stage 1 hypertension in the REGARDS study(Reasons for Geo-graphic and Racial Differences in Stroke),>85% of CVD events occurred among participants with higher CVD risk,defined by a 10-year predicted ASCVD risk≥7.5% us-ing the PCEs.10 In addition, participants with any high-risk condition, defined by age≥65 years, diabetes, CKD, his-tory of CVD, or higher 10-year predicted ASCVD risk, had an≈6 times higher rate of CVD events compared with their counterparts without a high-risk condition. These data support the integrative risk-based decision-making approach proposed in the 2025 High Blood Pressure Guideline, which includes comorbidities(CVD, diabetes,or CKD) and predicted 10-year risk(PREVENT-CVD≥7.5%) for initiation of antihypertensive therapy in stage 1 hypertension.75 Because PREVENT is intended for adults 30 to 79 years of age, risk estimates cannot be calcu-lated for adults<30 or≥80 years of age. However, it is reasonable to expect that most adults≥80 years of age are at increased CVD risk and that most adults<30 years of age are at lower CVD risk on the basis of age alone.In fact, no adults even in the 30- to 39-year-old group with stage 1 hypertension without CVD, diabetes, or CKD achieve a risk threshold of 75%(Table 4). However, for younger adults with stage 1 hypertension for whom risk cannot be calculated(<30 years of age) or any adult for whom risk with PREVENT is estimated to be low(<7.5%),the 2025 High Blood Pressure Guideline includes a rec-ommendation to initiate antihypertensive drug therapy if initial lifestyle interventions are not successful after a 3-to 6-month trial(Class of Recommendation 1; Level of Evidence B-R). This is especially important in minoritized populations who are more likely to develop hypertension at an earlier age. In an analysis of NHANES, nearly 25%of Black adults reported age at hypertension diagnosis before 30 years of age.76

Integration of Quantitative and Qualitative Risk Assessment

Despite the improved accuracy and precision of the PRE-VENT equations on a population level, potential limita-tions remain, as with any risk model, at the individual level.

This is particularly relevant in populations who may have been underrepresented in the development(eg, Ameri-can Indian/Alaska Native populations) or are at height-ened CVD risk due to risk-enhancing factors(eg, a history of hypertensive disorders of pregnancy77). Ultimately, risk prediction is a probabilistic estimate based on individu-als with similar characteristics. Therefore, not all individ-ual patients with 10-year predicted total CVD risk≥7.5%will have a CVD event over the next 10 years, and some adults with predicted risk<7.5% will have CVD events.10 Consequently, quantitative risk assessment should be in-tegrated with other individual-level patient characteristics to personalize risk assessment, and this may be especially useful in patients with a predicted 10-year risk for total CVD with PREVENT near the risk threshold of 7.5%. ${}^{6}$ The 2025 High Blood Pressure Guideline suggest the consideration of other factors such as adverse social fac-tors(eg, residing in a highly deprived area, experiences of discrimination, lower educational attainment), biomark-ers(eg,natriuretic peptides),imaging(eg,left ventricular hypertrophy, diastolic dysfunction),78 and 30-year risk as-sessment with PREVENT.79,80 Of note, a 12-lead ECG is recommended in the evaluation of all adults with hyper-tension to screen for left ventricular hypertrophy(Class of Recommendation 1; Level of Evidence C-E), which is associated with significantly higher risk of CVD. Although a post hoc analysis of SPRINT demonstrated that indi-viduals with malignant left ventricular hypertrophy defined by 12-lead ECG and cardiac biomarker elevation had a much greater ARR with intensive BP lowering, prospec-tive trial data in this high-risk subset of individuals with stage 1 hypertension and left ventricular hypertrophy are needed.78.81 Ultimately, risk assessment should be paired with patient preferences to inform shared decision-making for hypertension management.3,82

Another important consideration in risk assessment is the dynamic nature of CVD risk factors that are included in the PREVENT risk estimates, including systolic BP,which can vary over days to weeks. Because models like PREVENT also include other nonmodifiable(eg, age)and more static(eg, cholesterol) risk factors, risk esti-mates are less likely to have marked short-term variabil-ity. Data from NHANES examined this question among 702 participants with 2 visits conducted a median of 21 days apart; only 0.3% of participants with 10-year pre-dicted risk<5% or≥10% at an initial visit were recatego-rized across the 7.5% threshold.83

ADDRESSING IMPLEMENTATION GAPS IN RISK-BASED INITIATION OF ANTIHYPERTENSIVE DRUG THERAPY

Prior studies have reported that multivariable risk predic-tion equations are more accurate at estimating 10-year CVD risk than clinicians and are superior to counting

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AND GULENES CLINICAL STATEMENTS

the number of risk factors.84 However, several barriers may hinder the effective integration of risk assessment tools into routine clinical practice. For example, limit-ed access to risk calculators within clinical workflows and inconsistent integration into EHR systems affect their usability at the point of care.85,86 Likewise, limited awareness or acceptability among patients and clinici-cians of the benefits of CVD risk assessment and risk-based prevention may hinder widespread adoption.87 Furthermore, workflow and time constraints, particularly in high-volume clinical settings, often limit the ability to conduct comprehensive risk assessments during rou-tine visits.86 These challenges are more pronounced in rural health care settings, where lower EHR adoption rates exacerbate disparities in risk assessment imple-mentation.89

Proposed strategies to overcome barriers to imple-menting risk assessment tools in clinical practice are broadly relevant in clinical care beyond antihypertensive management and should focus on 3 key areas: ensur-ing access to resources and a supportive environment(opportunity), equipping clinicians with the necessary knowledge and skills(capability), and fostering the motivation required to integrate these tools into routine care.87,90 Strengthening opportunity involves integrating automated risk assessment prompts directly into EHR systems, which has been shown to improve documenta-tion of risk factors and guideline-based management.85 Expanding telehealth services can facilitate remote CVD risk assessment, particularly in areas with limited health care access.91 In addition, policy-driven financial incentives such as federal funding programs aimed at increasing EHR adoption in resource-constrained set-tings may help reduce disparities in the implementation of risk assessment tools. Enhancing capability can result from structured education and training initiatives for clinici-cians to build the skills needed to effectively use these tools. Continuing medical education courses and training programs may improve adherence to risk assessment guideline recommendations.92 Mobile applications and web-based platforms93 may be useful tools for calculat-ing CVD risk, providing clinicians and patients with con-venient resources to incorporate risk assessment into shared decision-making. These may enhance accessibil-ity in low-resource settings,ensuring that risk calculators are functional across diverse clinical environments.87,94

Integrating risk assessment tools into standardized antihypertensive medication protocols has the potential to improve patient outcomes, particularly when paired with behavioral interventions. Electronic reminders and audit-feedback mechanisms have proved modestly effective in promoting adherence to risk-based guideline recommendations.95 However, overcoming health system barriers such as updating outdated risk scores within EHRs is key and requires institutional commitment,financial investment, and prioritization of information

technology infrastructure to ensure seamless integration into clinical workflows.

COMPREHENSIVE STRATEGIES TO REDUCE HYPERTENSION-RELATED RISK

In addition to optimizing the identification of individu-als who will benefit from initiation of antihypertensive therapy, key modifiable lifestyle factors associated with hypertension should be addressed as part of a compre-hensive strategy to improve cardiovascular health and to reduce BP-related risk. Lifestyle interventions that target weight loss, heart-healthy dietary eating patterns, re-duced intake of sodium, use of salt substitutes, reduced alcohol intake, physical activity, and stress reduction have demonstrated benefit in both the prevention and treat-ment of hypertension.96,97 Measuring and tracking prog-ress in promoting favorable health behaviors to lower BP and CVD risk can be optimized with the AHA's Life's Essential 8 framework.98-100 Conversely, when not opti-mized, these lifestyle and psychosocial factors can result in elevated BP and CVD risk.101 Beyond individual-level strategies, local and national policies supporting the re-design of the built environment(ie, neighborhood design,transportation networks, housing natural environments)and food supply(ie, sodium reduction Food Is Medicine policies) are needed to promote healthy behaviors and lifestyles.102,103

FUTURE DIRECTIONS AND UNANSWERED QUESTIONS IN RISK ASSESSMENT

Refining CVD Risk Calculation, Implementation,and Communication

The PREVENT equations provide an important advance-ment in accurate and precise CVD risk prediction and therefore improve the identification of individuals for risk-based hypertension management. Although the PREVENT calculator is available online, EHR-based integration may improve the use of risk calculation but must be paired with innovative strategies to optimize initiation of antihypertensive therapy when indicated. A recent single-center trial that used machine learning in the EHR to identify individuals with left ventricular hy-pertrophy demonstrated an increase in the diagnosis and treatment of hypertension in those randomized to a clinical support pathway.104 Future research should also investigate whether incorporation of left ventricu-lar hypertrophy from an ECG, blood-based biomarkers(eg, high-sensitivity troponin or brain natriuretic peptide),or polygenic risk scores can improve risk assessment when considered sequentially or if risk for HF and a PREVENT-specific threshold for HF should be consid-ered in addition to total CVD, which was the focus of a

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recent AHA scientific statement on risk-based primary prevention of HF.80,105,107 Last, communication and in-terpretation of absolute risk to guide treatment can be challenging for both patients and clinicians. Use of the recently developed PREVENT-Risk Age calculator108(similar to the Heart Age tool created for the Framing-ham Heart Score109) may be a helpful way to convey the meaning of PREVENT risk estimates to patients. How-ever, tailored risk communication strategies and decision aids may be helpful and should be rigorously evaluated in prospective studies.

Expanding the Generalizability of the PREVENT Equations

Ongoing work should continue to evaluate the generaliz-ability of PREVENT in datasets and settings not included in the original development, as well as among subsets of patients with risk-enhancing factors, specifically, patients with a greater burden of adverse SDOH who may not routinely seek care, women with reproductive risk fac-tors(eg, adverse pregnancy outcomes), and those with inflammatory conditions(eg, rheumatoid arthritis, sar-coidosis, or HIV) who are at higher risk of CVD.4 It is also important to acknowledge the heterogeneity within populations of individuals. For example, aggregating in-dividuals into broad racial and ethnic groups(eg, Asian individuals, Hispanic individuals) may mask within-group heterogeneity in CVD risk.110-112 EHR data from geo-graphic areas with more enriched samples of Hispanic adults and Asian adults are needed to examine disag-gregated groups more carefully and to evaluate the generalizability of PREVENT performance in these het-erogeneous groups.74,113 Although the PREVENT models were developed for the United States, evaluation of PRE-VENT in samples outside the United States may also of-fer insights into generalizability to other countries. ${}^{114}$

Assessing and Addressing a Broader Array of SDOH

Further research should include a broader array of individual-level and area-based SDOH in risk assess-ment and hypertension management. Emerging work on novel polysocial risk scores suggests their poten-tial utility in identifying individuals at higher risk for hypertension-related adverse health outcomes.115 Among those identified to have adverse social factors or to reside in more deprived areas, care plans for hy-pertension management should include strategies to support patients and to connect them with community resources to address food insecurity, housing instabil-ity, and prescription assistance.116 Health care organi-zations and community partnerships may sustain and bridge care gaps, particularly because rates of health insurance churn may be increasing.117 In addition, health

care teams should receive training on cultural compe-tence and implicit bias to optimize equity in care delivery,particularly among marginalized populations who are more likely to experience disproportionate burden of hy-pertension.118 The importance of SDOH in hypertension control was recently highlighted as part of a National Heart, Lung, and Blood Institute and Centers for Dis-ease Control and Prevention workshop.119

CONCLUSIONS

The 2025 multisecality High Blood Pressure Guideline represents a major advancement for the management of patients with high BP with the goal of optimally prevent-ing complications of elevated BP by identifying those who will benefit from most BP-lowering medication(ie, rec-ommending the right treatment to the right person at the right time). The present document details the evidence supporting the updated recommendation to integrate the PREVENT equations into the comprehensive approach to risk-based treatment of hypertension and the ratio-nale for the recommendation to use a 10-year CVD risk threshold≥7.5% with the PREVENT equations for initia-tion of antihypertensive therapy in stage 1 hypertension.Evidence for this risk threshold is supported by clinical trial data, distributions of PREVENT risk estimates in the US population, and the population level, implications of the new PREVENT risk threshold on adults with stage 1 hypertension. This multipronged approach provides an overarching framework that can be applied when the PREVENT equations are updated in the future or when new risk scores are developed and may be applied by other guidelines to define risk-based strategies across the spectrum of primary prevention. Optimal implemen-tation of the 2025 High Blood Pressure Guideline rec-ommendations by clinicians, health systems, and public health initiatives would generate substantial momentum toward eliminating the increasing population burden and costs of heart disease, stroke, and non-CVD morbidity(eg, dementia) attributable to hypertension.120,121

ARTICLE INFORMATION

The American Heart Association and American College of Cardiology make every effort to avoid any actual or potential conflicts of interest that may arise as a result of an outside relationship or a personal, professional, or business interest of a member of the writing panel. Specifically, all members of the writing group are required to complete and submit a Disclosure Questionnaire showing all such relationships that might be perceived as real or potential conflicts of interest.

This statement was approved by the American Heart Association Science Advisory and Coordinating Committee on June 18, 2025, the American College of Cardiology Clinical Policy Approval Committee on June 24, 2025, and the American Heart Association Executive Committee on July 21, 2025. A copy of the document is available at https://professional.heartg./statements by using either"Search for Guidelines& Statements" or the"Browse by Topic" area. To purchase additional reprints, call 215-356-2721 or email Meredith.Edelman@wolterskluwer.com

This article has been published in Hypertension and the Journal of the American College of Cardiology.

The American Heart Association requests that this document be cited as follows:Khan SS,Abdalla M,Bello NA,Blyler CA,Carter J,Commodore-Mensah Y,Ferdinand

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CLINICAL STATEMENTS

KC,Johnson HM,Jones D,Khera A,Muntner P,Schott S,Shimbo D,Smith SC Jr,Taler SJ,Yang E,Y Lloyd-Jones DM; on behalf of the American Heart Association and American College of Cardiology. Use of risk assessment to guide decision-making for blood pressure management in the primary prevention of cardiovascular disease:a scientific statement from the American Heart Association and American College of Cardiology. Circulation.2025;152:e--e--...doi:10.1161/CIR.0000000000001355

The expert peer review of AHA-commissioned documents(eg, scientific statements, clinical practice guidelines, systematic reviews) is conducted by the AHA Office of Science Operations. For more on AHA statements and guidelines development, visit https://professionalheart.org/statements.Select the"Guide-lines& Statements* drop-down, then click"Publication Development"

Disclosures

Writing Group Disclosures

|Writing group member|Employment|Research grant|Other research support|Speakers& bureau/ honoraria|Expert witness|Ownership interest|Consultant/ advisory board|Other| |---|---|---|---|---|---|---|---|---| |Sadiya S. Khan|Northwestern University Feinberg School of Medicine|None|None|None|None|None|None|None| |Donald M. Lloyd-Jones|Boston University Chobanian & Avedesian School of Medicine|None|None|None|None|None|None|None| |Marwah Abdalla|Columbia University Irving Medical Center|None|None|None|None|None|None|None| |Natalie A. Bello|Cedars-Sinai Medical Center|None|None|None|None|None|None|None| |Ciantel A. Blyler|Cedars-Sinai Medical Center Heart Institute|None|None|None|None|None|None|None| |Jocelyn Carter|Massachusetts General Hospital|None|None|None|None|None|None|None| |Joyneon Carter|Massachusetts General Hospital|None|None|None|None|None|None|None| |Mensah|Johns Hopkins University School of Public Health and Nursing|None|None|None|None|None|None|None| |Keith C. Ferdinand|Tulane University School of Medicine|None|None|None|None|None|None|None| |Heather M. Johnson|Christine E. Lynn Women's Health and Wellness Institute, Boca Raton Regional Hospital, Baptist Health South Florida, Atlantic University Schmidt College of Medicine|None|None|Esperiont|None|None|Medtronic*; Novartis*; Esperion* Amgen*|None| |Daniel Jones|University of Mississippi Medical Center|None|None|None|None|None|None|None| |Amit Khera|UT Southwestern Medical Center|None|None|None|None|None|None|None| |Paul Munnter|University of Alabama at Birmingham|None|None|None|None|None|None|None| |Stacey Schott|Johns Hopkins University School of Medicine|None|None|None|None|Eli Lilly*; Merck*; Novo Nordisk*; Pfizer*|American College of Preventive Medicine*|None| |Daichi Shimbo|Columbia University Irving Medical Center|None|None|None|None|None|None|None| |Sidney C. Smith, Jr|University of North Carolina|None|None|None|None|None|None|None| |Sandra J. Taler|Mayo Clinic|None|None|None|None|None|None|None| |Eugene Yang|University of Washington Medical Center|Microsoft Research (grant to support research on new BP measurement|None|None|None|None|American College of Cardiologyt; Idorsiat; SkyLabs*|None|

This table represents the relationships of writing group members that may be perceived as actual or reasonably perceived conflicts of interest as reported on the Disclosure Questionnaire, which all members of the writing group are required to complete and submit. A relationship is considered to be“significant” if(a) the person receives$5000 or more during any 12-month period, or 5% or more of the person's gross income; or(b) the person owns 5% or more of the voting stock or share of the entity, or owns$5000 or more of the fair market value of the entity. A relationship is considered to be"modest if it is less than"significant" under the preceding definition.*Modest.

*Modest.

tSignificant.

CLINICAL STATE AND GURLDESINMENTS

Khan et al

Risk Assessment for Blood Pressure Management in Preventing CVD

CLINICAL STANDEMENTS

Reviewer Disclosures

|||||||||| |---|---|---|---|---|---|---|---|---| |Reviewer|Employment|Research grant|Other research|Speakers|Expert|Ownership interest|Consultant/ advisory board|Other| |Donna K. Arnett|University of South Carolina|None|None|None|None|None|None|None| |Olivia Blazek|Indiana University|None|None|None|None|None|None|None| |Adam P. Bress|University of Utah, School of Medicine|None|None|None|None|None|None|None| |Jordana B. Cohen|University of Pennsylvania, Perelman School of Medicine|None|None|None|None|None|None|None| |Wanpen Vongpataninas|University of Texas Southwestern Medical Center|None|None|None|None|None|None|None| |Karol E. Watson|David Geffen School of Medicine|None|None|None|None|None|None|None|

This table represents the relationships of reviewers that may be perceived as actual or reasonably perceived conflicts of interest as reported on the Disclosure Ques-tionnaire, which all reviewers are required to complete and submit. A relationship is considered to be“significant” if a( a) the person receives$5000 or more during any 12-month period, or 5% or more of the person's gross income; or(b) the person owns 5% or more of the voting stock or share of the entity, or owns$5000 or more of the fair market value of the entity. A relationship is considered to be"most if" it is less than"significant" under the preceding definition.

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