Cited by 1,234Health Promotion and Cardiovascular PreventionCardiovascular Health and Risk FactorsLipoproteins and Cardiovascular Health

The DOI matches its Crossref record; 92 of the 92 references it cites were found in a registry or an index.

Development and Validation of the American Heart Association’s PREVENT Equations

Open access

Khan, Sadiya S., Matsushita, Kunihiro, Sang, Yingying, Ballew, Shoshana H., Grams, Morgan E., Surapaneni, Aditya, Blaha, Michael J., Carson, April P., Chang, Alexander R., Ciemins, Elizabeth, Go, Alan S., Gutierrez, Orlando M., Hwang, Shih-Jen, Jassal, Simerjot K., Kovesdy, Csaba P., Lloyd-Jones, Donald M., Shlipak, Michael G., Palaniappan, Latha P., Sperling, Laurence, Virani, Salim S., Tuttle, Katherine, Neeland, Ian J., Chow, Sheryl L., Rangaswami, Janani, Pencina, Michael J., Ndumele, Chiadi E., Coresh, Josef, for the Chronic Kidney Disease Prognosis Consortium and the American Heart Association Cardiovascular-Kidney-Metabolic Science Advisory Group·2024·Circulation

DOI 10.1161/circulationaha.123.067626PMC PMC10910659

Open this paper in CoChat — free account Open PDF

Abstract

BACKGROUND: Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. METHODS: The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. RESULTS: Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763–0.809) in female and 0.757 (0.727–0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81–1.16) and 0.94 (0.81–1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD– and heart failure–specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004–0.005] and 0.005 [0.004–0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84–1.20] versus 1.39 [1.14–1.65]; P =0.01). CONCLUSIONS: PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1161/circulationaha.123.067626

Cites

92 of 92 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Should We STOP Angiotensin Converting Enzyme Inhibitors/Angiotensin Receptor Blockers in Advanced Kidney Disease?
Ahmed, A., Jorna, T., & Bhandari, S. (2016) · The Nephron journals/Nephron journals · doi:10.1159/000447068 · Cited by 11,782
KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease
Stevens, P. E., Ahmed, S. B., Carrero, J. J., Foster, B., Francis, A., Hall, R. K., Herrington, W. G., Hill, G., Inker, L. A., Kazancıoğlu, R., et al. (2024) · Kidney International · doi:10.1016/j.kint.2023.10.018 · Cited by 8,530
Self-citation
Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Anderson, C. A. M., Arora, P., Avery, C. L., Baker-Smith, C. M., Beaton, A. Z., Boehme, A. K., Buxton, A. E., et al. (2023) · Circulation · doi:10.1161/cir.0000000000001123 · Cited by 8,300
Self-citation
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
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000625 · Cited by 6,185
Self-citation
Association between Water Intake, Chronic Kidney Disease, and Cardiovascular Disease: A Cross-Sectional Analysis of NHANES Data
Sontrop, J. M., Dixon, S. N., Garg, A. X., Jiménez, I. B., Dohein, O., Huang, S. S., & Clark, W. F. (2013) · American Journal of Nephrology · doi:10.1159/000350377 · Cited by 5,903
Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project
Conroy, R. (2003) · European Heart Journal · doi:10.1016/s0195-668x(03)00114-3 · Cited by 5,290
2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk
Goff, D. C., Lloyd-Jones, D. M., Bennett, G., Coady, S., D’Agostino, R. B., Gibbons, R., Greenland, P., Lackland, D. T., Levy, D., O’Donnell, C. J., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.005 · Cited by 4,945
Self-citation
New creatinine- and cystatin C-based equations to estimate GFR without race
Inker, L. A., Eneanya, N. D., Coresh, J., Tighiouart, H., Wang, D., Sang, Y., Crews, D. C., Doria, A., Estrella, M. M., Froissart, M., et al. (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2102953 · Cited by 4,695
Self-citation
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.
Arnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., Himmelfarb, C. D., Khera, A., Lloyd-Jones, D., McEvoy, J. W., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000678 · Cited by 4,536
Self-citation
Untitled work
(2019) · doi:10.1161/cir.0000000000000677 · Cited by 4,501
Self-citation

Flagged first, then by citations

Show all 92 references

Sorted by citations

Items 401–500 of 1,000

Generalizability of VICTORION-1 PREVENT enrollment criteria to the United States population
Aggarwal, R., Bhatt, D. L., Bonaca, M. P., Deck, C., Lesogor, A., Patel, M. R., Stroes, E. S. G., Taub, P. R., & Windecker, S. (2025) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2025.100957 · Cited by 3
External validation of the 2023 American Heart Association Predicting Risk of cardiovascular disease EVENTs equations for atherosclerotic cardiovascular disease in primary cardiovascular prevention setting and comparison with 2021 Systematic COronary Risk Evaluation and 2013 Pooled Cohort Equations
Harpe, R. D. L., Marques-Vidal, P. M., & Vaucher, J. (2025) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwaf213 · Cited by 8
Cardiovascular-kidney-metabolic syndrome, systemic inflammation, and incident dementia: evidence from 400,740 UK Biobank participants
Li, P., Zhang, H., Ma, J., Wang, J., Lv, S., Zhao, X., Yang, X., Luo, Y., Guo, X., Tao, L., et al. (2025) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-025-01805-6 · Cited by 3
Lipid-lowering Therapy Utilization, Adherence, and Outcomes Among Adults With and at-Risk for Atherosclerotic Cardiovascular Disease in an Integrated Healthcare Delivery System in Southern California
Mefford, M. T., Zhou, H. C., Li, K., Zhou, M., Victores, A., Bash, L. D., An, J., Harrison, T. N., Scott, R. D., & Reynolds, K. (2025) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2025.07.011 · Cited by 3
Cholesterol Levels and Cardiovascular Outcomes Following Statin Initiation for Primary Prevention
Thompson, W., Jeong, I. J., Basque, S. R., Abdel-Qadir, H. M., Austin, P. C., Ko, D. T., Famiyeh, I., Chu, A., Fang, J., Odutayo, A., et al. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.101864 · Cited by 3
Association between the dietary inflammatory index and depressive symptoms in adults with cardiovascular–kidney–metabolic syndrome: evidence of metabolic syndrome as a mediator
Tian, R.-N., Zhang, S., Zhang, N., Wu, W.-J., Guo, H.-Q., Wang, C., & Duan, Z.-G. (2025) · Frontiers in Nutrition · doi:10.3389/fnut.2025.1623482 · Cited by 3
Tackling the Cardio-Kidney-Metabolic Burden in Cancer
Nahle, T., Shah, V., Kunhiraman, H. H., Makram, O. M., Ahmed, O., Yerraguntla, S., Gopu, G., Vy, J., Singh, S., Borse, T., et al. (2025) · Current Atherosclerosis Reports · doi:10.1007/s11883-025-01336-5 · Cited by 3
2025 AHA/ACC/Multisociety High Blood Pressure Guideline
McCarthy, C. P., & McEvoy, J. W. (2025) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2025.08.065 · Cited by 3
Waist-to-height ratio and coronary artery calcium incidence: the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)
Mendes, T. B., Generoso, G., Fabiano, R. C., Halpern, B., Janovsky, C. C. P. S., Romero, C. M., Santos, R. D., Benseñor, I. M., Lotufo, P. A., & Bittencourt, M. S. (2025) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2025.101281 · Cited by 3
Interplay of Coronary Artery Calcium and PREVENT Equations in Atherosclerotic Cardiovascular Disease Risk Prediction
Acquah, I., Hagan, K., Shapiro, M. D., Rikhi, R. R., Blumenthal, R. S., Al-Kindi, S. G., & Nasir, K. (2025) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2025.09.1576 · Cited by 3
Estimating 5-year absolute risk of cardiovascular disease using routinely collected electronic medical records from Australian general practices
Kuo, N. I.-H., Barbieri, S., Arnott, C. G., Gallego, B., Gandomkar, Z., Ferdousi, S., Douglas, K. A., Woodward, M., & Jorm, L. R. (2025) · Heart · doi:10.1136/heartjnl-2025-325776 · Cited by 3
Neutrophil percentage to albumin ratio and advanced cardiovascular-kidney-metabolic syndrome in diabetes: a machine learning approach
Zhuang, Z., Liu, X., Lu, H., Wu, Q., Chen, Y., & Ni, Q. Y. (2025) · European journal of medical research · doi:10.1186/s40001-025-03560-w · Cited by 3
The aging hemophilia patient
Lewandowska, M., & Lim, M. Y. (2025) · Hematology · doi:10.1182/hematology.2025000773 · Cited by 3
Association of dietary patterns with all-cause and cardiovascular disease mortality in cardiovascular-kidney-metabolic syndrome: a cohort study
Shao, Y., Wang, Y., Luo, D., Zhou, X., Chen, M., Li, L., & Zhong, H. (2025) · Nutrition Journal · doi:10.1186/s12937-025-01276-5 · Cited by 3
Relationship between 10- and 30-year PREVENT risk scores with coronary artery calcium and incident atherosclerotic cardiovascular disease: MESA
Rikhi, R. R., Chen, H., Carr, J. J., Shapiro, M. D., & Bertoni, A. G. (2025) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwaf770 · Cited by 3
SDOH, healthy lifestyle, and life expectancy in adults with CKM syndrome: two cohort studies
Huang, Q., Nan, W., He, B., & Peng, Z. (2025) · Progress in Cardiovascular Diseases · doi:10.1016/j.pcad.2025.11.012 · Cited by 3
Achieving BMI <25 kg/m2 was associated with reduced predicted risk of atherosclerotic cardiovascular disease in people with obesity or overweight on tirzepatide or placebo: a post hoc analysis of SURMOUNT-1, -3, and -CN
Guo, L., Ding, S., Wang, W., Zhang, H., Dai, S., Li, C., Yuan, Y., Stefański, A., Jouravskaya, I., & FORRESTER, T. D. (2025) · EClinicalMedicine · doi:10.1016/j.eclinm.2025.103722 · Cited by 5
Heart Failure Risk and Events in People With HIV: The Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE)
Bloomfield, G. S., Watanabe, M., McCallum, S., Aberg, J. A., Awwad, A., Campbell, T., Cespedes, M., Chu, S. M., Currier, J. S., Diggs, M. R., et al. (2025) · Circulation Heart Failure · doi:10.1161/circheartfailure.125.013382 · Cited by 3
Association of cardiovascular–kidney–metabolic syndrome stages with mortality: A nationwide, population-based, prospective cohort study
Zhou, X., Zhu, R., Liu, L., Liu, X., Lu, J., Chen, B., Wu, C. Y., Zhang, X., Yang, Y., Cui, J., et al. (2025) · Chinese Medical Journal · doi:10.1097/cm9.0000000000003914 · Cited by 4
Research Priorities and Future Directions in Cardio-Oncology
Mszar, R., Ali, A., Hull, S. C., Ferrucci, L. M., Baldassarre, L. A., Khera, R., Irwin, M. L., & Clasen, S. C. (2026) · Current Treatment Options in Oncology · doi:10.1007/s11864-025-01366-w · Cited by 5
Disease activity and hyperuricemia predict the development of cardiovascular events in patients with Psoriatic Arthritis: results of the 10-year prospective evaluation in the CARMA cohort
Llorca, J., Ivan, F.-A., Moreno-Martínez, M. J., Plaza, Z., Sánchez‐Alonso, F., Ramos, M. J. M., Gómez, M. C. G., Castañeda, S., González-Juanatey, C., González-Gay, M. Á., et al. (2026) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2026.152923 · Cited by 3
Shifting Thresholds
Metlock, F., Nriagu, B. N., Scheuermann, B., Ade, C. J., Kwapong, Y. A., Razavi, A. C., Juraschek, S., McCoy, S. E., Dastmalchi, L. N., Sharma, G. V., et al. (2026) · JACC Advances · doi:10.1016/j.jacadv.2025.102546 · Cited by 3
Association between the frailty index and all-cause and cardiovascular mortality in a population with cardiovascular-kidney-metabolic syndrome: Insights from the NHANES 2011-2018
Wang, X., Hai, X., Ma, A., Liang, X., Cheng, H., Wu, P. S., Hao, Y., Chen, D., & Yan, N. (2026) · The Journal of Frailty & Aging · doi:10.1016/j.tjfa.2025.100131 · Cited by 3
Operationalizing Equity: A Methodologic Framework for Revising Pediatric Clinical Guidance
Portillo, E. N., Ponce, M. R., Bell, S. L., Ellison, A. M., Goyal, M. K., Heard‐Garris, N., Johnson, T. J., & Wright, J. L. (2026) · PEDIATRICS · doi:10.1542/peds.2025-072830 · Cited by 3
The urinary albumin‐to‐creatinine ratio can direct personalized prevention and treatment for cardiovascular and chronic kidney disease
Kramer, H. J., & Bakris, G. L. (2026) · Journal of Internal Medicine · doi:10.1111/joim.70066 · Cited by 4
Performance of the Predicting Risk of Cardiovascular Disease Events Calculator in Rheumatoid Arthritis
Johnson, T. M., Frideres, H., Roul, P., Baker, J. F., Sauer, B. C., Cannon, G. W., Smith, I. D., Kunkel, G. A., Wallace, B. I., Porter, T. R., et al. (2026) · Arthritis & Rheumatology · doi:10.1002/art.70081 · Cited by 3
Association of remnant cholesterol inflammation index with future cardiovascular disease risk in patients with cardiovascular-kidney-metabolic syndrome stages 0–3
Xie, N., Zeng, L., Hu, X., Wu, Z., Lu, W., Luo, S., & Luo, J. (2026) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2026.113146 · Cited by 3
External validation of the PREVENT risk score: performance and clinical utility in an Iranian population
Hasanpour, A., Asgari, S., Khalili, D., Azizi, F., & Hadaegh, F. (2026) · Scientific Reports · doi:10.1038/s41598-026-38614-4 · Cited by 3
The remnant cholesterol inflammatory index and risk of future cardiovascular disease in early CKM syndrome: findings from CHARLS
Yu, Y., Jiao, Y., Chang, S., Li, Y. G., Shang, K., Song, G., & Yin, C. (2026) · Journal of Health Population and Nutrition · doi:10.1186/s41043-026-01286-x · Cited by 4
Development and Validation of a Machine Learning Model for Incident Heart Failure Prediction in Chronic Kidney Disease: A Multicenter Cohort Study
Lu, Y., Chen, J. H., Zhou, S., Lukwaro, A. F., Zhang, X., Yu, W., Chen, H., Chen, Y., Nie, S., & Tang, Y. (2026) · Journal of the American Heart Association · doi:10.1161/jaha.125.046156 · Cited by 3
Combined pre-hypertension, pre-diabetes, and pre-hyperlipidaemia and long-term cardiovascular risk in young adults: a nationwide cohort study
Lee, Y. J., Lee, J. H., Kim, M. N., Kim, H., Park, M. S., Lee, S. J., Han, S., Lee, M., & Cheon, D. Y. (2026) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwag233 · Cited by 3
Risk stratification in early-stage Cardiovascular-Kidney-Metabolic Syndrome: The Potency of visceral adiposity and insulin resistance surrogate indices
He, L., Lin, H., Zhang, X., & 凌秀凤 (2026) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2026.113336 · Cited by 3
Association between C-reactive protein-triglyceride glucose related indices and all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic syndrome
Lai, W., Zhou, Y., Xiao, L., Zhang, T., He, W., He, J., Gu, W., & Lin, Y. (2026) · Cardiovascular Diabetology · doi:10.1186/s12933-026-03228-7 · Cited by 3
The emerging role of coronary computed tomography for the prevention of cardiovascular disease in asymptomatic individuals
Verpalen, V. A., Aboyans, V., Dweck, M. R., Planken, R. N., Henriques, J. P. S., Bhatt, D. L., & Nurmohamed, N. S. (2026) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwag314 · Cited by 3
Antiplatelet Therapy in the Management of Atherosclerotic Cardiovascular Disease: 2026 ACC Scientific Statement
Kumbhani, D. J., Gibson, C. M., Kinlay, S., Peterson, E. D., Pollak, A. W., Tamis‐Holland, J. E., & Verheugt, F. W. A. (2026) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2026.05.037 · Cited by 5
Transformer-based models for predicting cardiovascular risk in Chinese adults: development and validation
Cao, Q., Xu, X., Hong, L., Yin, Y., Wu, S., Li, M., Xu, Y., Li, S., Xu, Y., Wei, H., et al. (2026) · European Heart Journal · doi:10.1093/eurheartj/ehag517 · Cited by 3
The therapeutic approach to cardiovascular–kidney–metabolic syndrome
Rangaswami, J., Lo, K. B., & Ndumele, C. E. (2026) · Nature Reviews Nephrology · doi:10.1038/s41581-026-01109-6 · Cited by 3
Self-citation
Big Data, Big Insights: Leveraging Data Analytics to Unravel Cardiovascular Exposome Complexities
Ibrahim, R., Pham, H. N., Nasir, K., Hahad, O., Sabharwal, A., & Al-Kindi, S. G. (2024) · Methodist DeBakey Cardiovascular Journal · doi:10.14797/mdcvj.1467 · Cited by 3
Polygenic Risk Scores for Coronary Heart Disease
Khan, S. S., & Pencina, M. J. (2024) · JAMA · doi:10.1001/jama.2024.24037 · Cited by 3
Self-citation
Impact of Lipid Lowering Therapies on the Primary Prevention of Atherosclerotic Cardiovascular Disease
Prabhakar, A. P., Vedamurthy, D., & Kalra, D. K. (2025) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-025-00764-x · Cited by 3
Modern therapy of patients with lupus erythematosus must include appropriate management of their heightened rates of atherosclerotic cardiovascular events: a literature update
Gomes, L. L. A., Faden, D. F., Xie, L., Chambers, S., Stone, C. J., Werth, V. P., & Williams, K. J. (2025) · Lupus Science & Medicine · doi:10.1136/lupus-2024-001160 · Cited by 3
Hypertension Canada guideline for the diagnosis and treatment of hypertension in adults in primary care
Goupil, R., Tsuyuki, R. T., Santesso, N. A., Terenzi, K. A., Habert, J., Cheng, G., Gysel, S. C., Bruneau, J., Leung, A. A. C., Campbell, N. R. C., et al. (2025) · Canadian Family Physician · doi:10.46747/cfp.20250616001 · Cited by 8
Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges
Biswas, D., Aminorroaya, A., Croon, P. M., Batinica, B., Pedroso, A. F., & Khera, R. (2025) · Current Atherosclerosis Reports · doi:10.1007/s11883-025-01337-4 · Cited by 4
Development and Validation of Novel Residual Risk Scores for Patients With ASCVD
Mineeva, O., Li, C., Giulianini, F., Häfliger, S., Bubes, V. Y., Rätsch, G., Mora, S., & Demler, O. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.102162 · Cited by 3
Calculated Medicine: Seven Decades of Accelerating Growth
Leff, L. E., & Koperwas, M. L. (2024) · The American Journal of Medicine · doi:10.1016/j.amjmed.2024.03.025 · Cited by 3
Coronary Artery Calcium for Risk Stratification Among Persons With Very High HDL Cholesterol
Razavi, A. C., Mehta, A., Wong, N. D., Rozanski, A., Budoff, M. J., Gianos, E., Vaccarino, V., van Assen, M., Cecco, C. N. D., Miedema, M. D., et al. (2024) · JACC Advances · doi:10.1016/j.jacadv.2024.101217 · Cited by 3
Self-citation
PREVENT and Pooled Cohort Equations in Atherosclerotic Cardiovascular Disease Risk Prediction: A Post Hoc Analysis of SPRINT
Shetty, N. S., Gaonkar, M. P., Patel, N. B., Vekariya, N., Li, P., Arora, G., & Arora, P. K. (2025) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2024.08.024 · Cited by 3
Breaking binary in cardiovascular disease risk prediction
Zhang, Y., & Fahed, A. C. (2025) · npj Cardiovascular Health · doi:10.1038/s44325-024-00041-7 · Cited by 6
Strategies to Address the Metabolic Burden of Psychotropic Medications
Anthamatten, A., & Henry-Okafor, Q. (2025) · The Journal for Nurse Practitioners · doi:10.1016/j.nurpra.2025.105346 · Cited by 3
Metabolic syndrome and Pathobiological Determination of Atherosclerosis in Youth risk score in adolescents with and without perinatally acquired HIV in the Cape Town Adolescent and Antiretroviral Cohort ( CTAAC )‐Heart study
Dirajlal‐Fargo, S., Nyathi, M. N., Sun, S., Balmert, L. C., Kahts, M., Asafu‐Agyei, N. A., Jele, N., Carkeek, E., Legbedze, J., McComsey, G. A., et al. (2025) · HIV Medicine · doi:10.1111/hiv.70049 · Cited by 3
Cardiovascular Risk Factor and Disease Mortality Among Asian Indian, Chinese, and Filipino Adults in the United States, 2018 to 2023
Aggarwal, R., Wadhera, R. K., Chiu, N., Szarek, M. J., & Bhatt, D. L. (2025) · Annals of Internal Medicine · doi:10.7326/annals-25-00108 · Cited by 3
Comparative performance of multiple inflammatory indices across different stages of cardiovascular-kidney-metabolism syndrome: A Multi-Cohort Study
Hu, L., Wang, Z., Chen, J., Chen, A., Wang, G., Xie, X., He, Q., Xue, Y., Wu, Z., Zheng, Z., et al. (2025) · Endocrine · doi:10.1007/s12020-025-04390-w · Cited by 3
Plasma small extracellular vesicles: Markers and mediators of atrial scar, in patients with atrial fibrillation
Al-rubaye, S., Ferrero, T. G., Rodriguez-Perez, A. I., Camacho-Meño, L., Labandeira-García, J. L., Álvarez, E., García‐Seara, J., Bravo, S. B., González‐Juanatey, J. R., Rodríguez‐Mañero, M., et al. (2025) · Heart Rhythm · doi:10.1016/j.hrthm.2025.07.058 · Cited by 3
From a genomic risk model to clinical trial implementation in a learning health system: the ProGRESS StudyPreprint
Vassy, J. L., Dornisch, A. M., Karunamuni, R. A., Gatzen, M., Kachulis, C., Lennon, N. J., Brunette, C. A., Danowski, M. E., Hauger, R. L., Garraway, I. P., et al. (2024) · medRxiv · doi:10.1101/2024.11.03.24316516 · Cited by 3
When Does Primary Prevention Encroach on Secondary Prevention?
Deshotels, M. R., Kotta, P. A., Mesa, J. S. R., Oyenubi, O., & Nambi, V. (2024) · Current Atherosclerosis Reports · doi:10.1007/s11883-024-01227-1 · Cited by 2
Advancing Precision Medicine Beyond 'Asian' Race
Le, A. D., Chu, R., Bui, V., & Bacong, A. M. (2024) · Journal of Asian Health · doi:10.59448/jah.v4i2.56 · Cited by 2
Validating the PREVENT Equations—A Contemporary Update to Cardiovascular Risk Assessment
Mangalesh, S., & Nanna, M. G. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.38284 · Cited by 2
Diagnostic Ability of Risk Models in the Field of Ischemic Stroke for Predicting Atherosclerotic Outcomes in Patients with Acute Myocardial Infarction
Goto, H., Saito, Y., Yaginuma, H., Asada, K., Sato, T., Hashimoto, O., Kitahara, H., & Kobayashi, Y. (2024) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.65162 · Cited by 2
Initiating Preventive Care for Hyperlipidemia in the Emergency Department: The Emergency Medicine Cardiovascular Risk Assessment for Lipid Disorders Trial
Ashburn, N. P., Snavely, A. C., Ehrig, M. R., Shapiro, M. D., Herrington, D. M., Reboussin, D. M., Gesell, S. B., & Mahler, S. A. (2025) · Critical Pathways in Cardiology A Journal of Evidence-Based Medicine · doi:10.1097/hpc.0000000000000390 · Cited by 2
Performance of the new PREVENT score for indicating subclinical atherosclerosis in rheumatoid arthritis
Gibbons, J., Bathon, J. M., & Giles, J. T. (2025) · Lara D. Veeken · doi:10.1093/rheumatology/keaf267 · Cited by 2
Tailoring cardiovascular risk prediction to females
Ashcroft, T., de Bakker, M., Anand, A., Sattar, N. A., Maybin, J. A., & Kimenai, D. M. (2025) · Journal of Endocrinology · doi:10.1530/joe-25-0084 · Cited by 3
Addressing Disparities in the Screening and Treatment of Dyslipidemia – A Call to Action
Converse, E., Watson, K., Ahmad, Z., Yang, E., Gianos, E., Sagheer, U., Virani, S. S., & Kalra, D. K. (2025) · Current Cardiovascular Risk Reports · doi:10.1007/s12170-025-00769-6 · Cited by 2
Self-citation
Feasibility of the Implementation of Tools for Heart Failure Risk Prediction
Wang, M. C., Dolan, B., Huang, X., Freaney, P. M., Freed, B. H., Vega, L., Markoski, N., Wainright, A. E., Kane, B. J., Seegmiller, L. E., et al. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.102004 · Cited by 2
Self-citation
Proteomics and the Risk of Incident Embolic and Thrombotic Stroke
Johansen, M. C., Chen, J., Walker, K. A., Wang, Z., Wang, W., Chen, L. Y., Kalani, R., Floyd, J. S., Fornage, M., Pike, J. R., et al. (2025) · Annals of Neurology · doi:10.1002/ana.70011 · Cited by 2
Self-citation
Cardiovascular-Kidney-Metabolic Syndrome: A Paradigm for Value-Based Care
Hermes, Z., Bhatt, A. S., & Vaduganathan, M. (2025) · Journal of Cardiac Failure - Intersections · doi:10.1016/j.yjcafi.2025.05.001 · Cited by 2
Clinical characteristics and in-hospital mortality of chronic myeloid leukemia patients with ischemic heart disease: insights from the JROAD-DPC registry
Shindo, A., Akazawa, H., Ueda, T., Kadowaki, H., Ishida, J., & Komuro, I. (2025) · European Heart Journal Open · doi:10.1093/ehjopen/oeaf101 · Cited by 2
From LDL-C to lipoprotein(a) - those who fail to learn from history are doomed to repeat it
Sarraju, A., & Nissen, S. E. (2025) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2025.101280 · Cited by 2
Comparison of Short‐ and Long‐Term Cardiovascular Disease Risk Assessment Tools in US Young Adults
Zhang, Y., Xia, M., Zhou, H. C., Zhou, M., Fang, M. X., Reynolds, K., Allen, N. B., Gauen, A., Petito, L. C., Xanthakis, V., et al. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.125.042392 · Cited by 3
Development of an optimized risk evaluation system for cardiovascular-kidney-metabolic syndrome-associated coronary heart disease based on tabular prior-data fitted network
Zhu, S., Zhang, H., Liu, Y., Bu, W., Wu, Q., Wang, J., Chen, W., Wu, Q., Geng, Z., & Liu, F. (2025) · Digital Health · doi:10.1177/20552076251379379 · Cited by 2
Impact of PREVENT Cardiovascular Risk Equations on Statin Eligibility by Subgroup and Risk Thresholds: A Cross-Sectional Study
Wright, A. P., McCoy, A. B., Garcia, K., Embí, P. J., Clair, W. K., Linton, M. F., & Wright, A. T. (2025) · Journal of General Internal Medicine · doi:10.1007/s11606-025-09858-z · Cited by 2
The effect of low-dose aspirin on reversing frailty status in older prefrail and frail adults: a secondary analysis of the ASPREE randomised clinical trial
Handono, A. P., Ryan, J. L., Setiawan, F., Espinoza, S. E., Phyo, A. Z. Z., Zhu, C., Nelson, M. R., Ernst, M. E., Orchard, S. G., Wolfe, R. S., et al. (2025) · Age and Ageing · doi:10.1093/ageing/afaf271 · Cited by 2
Machine learning for predicting cardiovascular events in older adults with type 2 diabetes using Medicare claims and electronic health records
Htoo, P. T., Paik, J. M., Everett, B. M., Glynn, R. J., Bykov, K., Hahn, G., Liu, J., Wexler, D. J., & Patorno, E. (2025) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2025.112001 · Cited by 2
Prognostic Value of the American Heart Association PREVENT Cardiovascular Disease Risk Equations in Cancer Survivorship: A NHANES Population‐Based Study (2009–2018)
Al-Jarshawi, M. H. A., Kobo, O. M., Ko, D. T., Wijeysundera, H. C., Azam, M. G., Silverwood, V., Bajpai, R. C., Bagur, R., & Mamas, M. A. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.125.042209 · Cited by 2
Unfavorable Social Determinants of Health and Obesity
Philip, J. S., Hagan, K., Shahid, I., Chang, R. P., Prakash, S., Friedman, M., Titus, A., Kundi, H., Amin, Z., Javed, U., et al. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.102154 · Cited by 2
The prognostic significance of metabolic score for insulin resistance in evaluating all-cause and cardiovascular mortality risk among individuals across stages 1–4 of cardiovascular–kidney–metabolic syndrome: a nationwide prospective cohort study
Wang, J., & Du, B. (2025) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2025.104361 · Cited by 2
The association of steatotic liver disease with cardiometabolic criteria and cardiovascular disease risk in a large cohort of people living with human immunodeficiency virus
Sterling, R. K., Sternberg, A. L., Lake, J. E., Naggie, S., Heath, S. L., Price, J. C., Wilson, L., Crandall, H., Gawrieh, S., Chalasani, N., et al. (2025) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2025.101330 · Cited by 2
Interplay of glycated hemoglobin and traditional risk factors for the risk of atherosclerotic cardiovascular disease and all-cause mortality in people without diabetes
Masrouri, S., Hasanpour, A., Ebrahimi, N., & Hadaegh, F. (2025) · Cardiovascular Diabetology · doi:10.1186/s12933-025-02968-2 · Cited by 3
Predictive Value of Serum N‐Terminal pro‐B‐Type Natriuretic Peptide and Troponin T for Incident Heart Failure: A Meta‐Analysis of 9 International Cohorts
Bansal, N., Grams, M. E., Coresh, J., Matsushita, K., Ballew, S. H., Sang, Y., Surapaneni, A., Ärnlöv, J., Bell, S., Berry, J. D., et al. (2025) · Journal of the American Heart Association · doi:10.1161/jaha.125.041683 · Cited by 2
Self-citation
Therapeutic Considerations in Preventing Chronic Kidney Disease
Nicholas, S. B., Nobakht, N., & Alicic, R. Z. (2025) · Annual Review of Medicine · doi:10.1146/annurev-med-043024-013325 · Cited by 2
Effect of caloric restriction on cardiovascular‐kidney‐metabolic health in young adults: A secondary analysis of the randomised CALERIE trial
Chang, R. P., Claggett, B. L., Redman, L. M., Ravussin, É., Apovian, C. M., & Ostrominski, J. W. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.70308 · Cited by 2
Mining the risk: early cardiovascular detection in workers
Jorquera, R., Droppelmann, G., Dollmann, M., Blanco, G., Ahumada, I., Lira, A., & Feijoo, F. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1678172 · Cited by 3
Telehealth for Integrated Cardiovascular and Diabetes Management: A Scoping Review
Estêvão, M. D., Fernandes, M. T., Sousa‐Coelho, A. L. D., Espírito‐Santo, M., & Nascimento, T. (2025) · Journal of Diabetes Research · doi:10.1155/jdr/1093671 · Cited by 2
Association of PREVENT risk model with body fat distribution and subclinical left ventricular dysfunction
Hirose, K., Nakanishi, K., Daimon, M., Sawada, N., Konoma, S., Kobayashi, S., Seki, H., Yoshida, Y., Hirokawa, M., Nakao, T., et al. (2025) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2025.101368 · Cited by 2
Bundled measurement of LDL-cholesterol, lipoprotein(a), and high sensitivity C-reactive protein across the spectrum of cardiovascular risk
Razavi, A. C., Troy, A. L., Sperling, L. S., & Blumenthal, R. S. (2025) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2025.101384 · Cited by 2
Self-citation
Stage-specific risks of mortality and renal outcomes in cardiovascular-kidney-metabolic syndrome: findings from a nationwide Japanese cohort
Fujimoto, K., Kikuchi, M., Nakai, M., Konta, T., Iseki, K., Tsuruya, K., Yamagata, K., Narita, I., Moriyama, T., Shibagaki, Y., et al. (2025) · Clinical and Experimental Nephrology · doi:10.1007/s10157-025-02800-x · Cited by 4
Primary Hyperparathyroidism Associated With Elevated Coronary Artery Calcium Scores and Increased Cardiovascular Risk
Bauzon, J. S., Romero-Vélez, G., Ramchand, J., Ramchand, S. K., SIPERSTEIN, A. E., & Jin, J. (2025) · Endocrine Practice · doi:10.1016/j.eprac.2025.11.014 · Cited by 2
Prediction of cardiovascular disease risk in women and individuals with polycystic ovary syndrome using the American Heart Association PREVENT model: A long-term population-based cohort study
Heidari, P., Farrokhi, R., Firouzi, F., Zivari, Y., Azizi, F., Tehrani, F. R., & Behboudi‐Gandevani, S. (2026) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2026.101408 · Cited by 2
Circadian disruption is associated with advanced cardio-kidney-metabolic syndrome in overweight and obese adults: evidence from the NHANES database
Zhang, Q., Ye, T., Zhou, X.-L., Li, B., & Zhang, Z. (2026) · Nutrition & Metabolism · doi:10.1186/s12986-025-01072-2 · Cited by 2
Coronary artery calcium clinical utilization: An update
Mortada, I., Odigie‐Okon, E., Motiwala, A., Allencherril, J., Qadeer, A., Gaalema, D. E., Abdulla, A., Blackwell, T. A., & Jneid, H. M. (2026) · Current Problems in Cardiology · doi:10.1016/j.cpcardiol.2026.103258 · Cited by 2
Association of cardiovascular risk scores with coronary plaque and its progression among individuals with family history of coronary artery disease
Soh, C. H., Nerlekar, N., Whitmore, K., Salib, A., Watts, G. F., Nicholls, S. J., & Marwick, T. H. (2026) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2026.101423 · Cited by 2
Ten Hot Topics in Cardiovascular Risk Management for Chronic Kidney Disease
Marqués, M., Ortíz, A., Romero-González, G. A., Díez, J., Santamaría, R., Puente-García, A., Alcázar, R., de Sequera, P., Górriz, J. L., & Quiroga, B. (2026) · Cardiorenal Medicine · doi:10.1159/000550943 · Cited by 2
AI-CVD-HF: A heart failure risk prediction model based on coronary artery calcium scans compared with PREVENT-HF
Mirjalili, S. R., Atlas, K. C., Reeves, A. P., Zhang, C., Wasserthal, J., Azimi, A., Hashemi, A., MozafaryBazargany, M., Jolfayi, A. G., Atlas, T. L., et al. (2026) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2026.101464 · Cited by 2
Phenotypic clustering of cardiovascular risk profiles in systemic lupus erythematosus
Azoulay, L.-D., Kachenoura, N., Boussouar, S., Charpentier, E., Pasi, N., Nguyen, L.-A., Broussaud, T., Giron, A., Leite, J., Abdallah, N. A., et al. (2026) · Lupus · doi:10.1177/09612033261425762 · Cited by 3
Assessment for Long-Term Cardiovascular Disease Risk in Pregnancy
Khan, S. S., & Yee, L. M. (2026) · JAMA Cardiology · doi:10.1001/jamacardio.2025.5602 · Cited by 2
Self-citation
Bridging the Gap in Racial/Ethnic Disparities: Perspectives from the 2025 American Heart Association/American College of Cardiology High Blood Pressure Guideline
Reddy, T. K., Ancha, B., Grant, J. K., & Ferdinand, K. C. (2026) · Current Hypertension Reports · doi:10.1007/s11906-026-01367-6 · Cited by 2
Cardiovascular Events in US Adults Aged ≥80 Years: Incidence, Risk Factors, and Outcomes
Muntner, P., Safford, M. M., Goyal, P., Alexander, K. P., Levitan, E. B., Nanna, M. G., Reid, R.-J., Sterling, M. R., & Bowling, C. B. (2026) · Circulation Population Health and Outcomes · doi:10.1161/circoutcomes.125.012379 · Cited by 2
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 adults: a commentary from the European Renal Best Practice (ERBP)
Kanbay, M., Çöpür, S., Sarafidis, P. A., Ferro, C. J., & Ortíz, A. (2026) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfag055 · Cited by 2
Development and Validation of the AI-HeartAge Model in Framingham and UK Biobank
Korzinski, T. J., Prescott, B. R., Hamel‐Sellman, D. J., Xanthakis, V., Cooper, L. L., Hamburg, N. M., Tsao, C. W., Benjamin, E. J., Vasan, R. S., & Mitchell, G. F. (2026) · Hypertension · doi:10.1161/hypertensionaha.125.26209 · Cited by 2
The association between 10-year cardiovascular risk and fracture incidence in postmenopausal women: a prospective analysis from the Women's Health Initiative
Hossain, R., Laddu, D., Crandall, C. J., Ensrud, K. E., Cauley, J. A., Gabriel, K. P., Haring, B., Hardy, S. T., LeBoff, M. S., Manson, J. E., et al. (2026) · The Lancet Regional Health - Americas · doi:10.1016/j.lana.2026.101440 · Cited by 2
Development and evaluation of cardiovascular disease risk prediction models for patients with type 2 diabetes
Yang, Y., Liu, T., Liao, C.-Y., Lee, S. J., Keyvanshokooh, E., Shao, H., Weber, M. B., Pasquel, F. J., & Garcia, G. P. (2026) · Scientific Reports · doi:10.1038/s41598-026-45129-5 · Cited by 2

Authors: Khan, S. S., Matsushita, K., Sang, Y., Ballew, S. H., Grams, M. E., Surapaneni, A., Blaha, M. J., Carson, A. P., Chang, A. R., Ciemins, E., Go, A. S., Gutierrez, O. M., Hwang, S.-J., Jassal, S. K., Kovesdy, C. P., Lloyd-Jones, D. M., Shlipak, M. G., Palaniappan, L. P., Sperling, L., Virani, S. S., Tuttle, K., Neeland, I. J., Chow, S. L., Rangaswami, J., Pencina, M. J., Ndumele, C. E., Coresh, J., & for the Chronic Kidney Disease Prognosis Consortium and the American Heart Association Cardiovascular-Kidney-Metabolic Science Advisory Group
Affiliations: Northwestern University (US)
Johns Hopkins University (US)
New York University (US)
University of Mississippi Medical Center (US)
Departments of Nephrology and Population Health Sciences, Geisinger Health, Danville, PA (A.R.C.).
American Medical Group Association (US)
Kaiser Permanente (US)
Departments of Epidemiology and Medicine, University of Alabama at Birmingham (O.M.G.).
National Heart, Lung, and Blood Institute (US)
University of California San Diego (US)
University of Tennessee Health Science Center (US)
Department of Preventive Medicine, Northwestern University, Chicago, IL (D.M.L.-J.).
San Francisco VA Medical Center (US)
Stanford Medicine (US)
Emory University (US)
Aga Khan University (PK)
University of Washington (US)
University Hospitals of Cleveland (US)
Western University of Health Sciences (US)
George Washington University (US)
Duke University (US)
ORCID: Khan, Sadiya S.
Matsushita, Kunihiro
Sang, Yingying
Ballew, Shoshana H.
Grams, Morgan E.
Surapaneni, Aditya
Blaha, Michael J.
Carson, April P.
Chang, Alexander R.
Ciemins, Elizabeth
Go, Alan S.
Gutierrez, Orlando M.
Hwang, Shih-Jen
Jassal, Simerjot K.
Kovesdy, Csaba P.
Lloyd-Jones, Donald M.
Shlipak, Michael G.
Palaniappan, Latha P.
Sperling, Laurence
Virani, Salim S.
Tuttle, Katherine
Neeland, Ian J.
Chow, Sheryl L.
Rangaswami, Janani
Pencina, Michael J.
Ndumele, Chiadi E.
Coresh, Josef
Venue: Circulation
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2024-02-06
Volume: 149
Issue: 6
Pages: 430-449
ISSN: 0009-7322 (ISSN-L)
1524-4539
DOI: 10.1161/circulationaha.123.067626
PMC: PMC10910659
OpenAlex: W4388573970
Cited by: 1,234
References: 92
Citations by year: 2026: 631 · 2025: 467 · 2024: 134
FWCI: 314.97
Type: journal article
Language: en
Update notices: correction (2024-03-11)
correction (2026-10-14)
Open access: green
www.ncbi.nlm.nih.gov
Locations: Circulation (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Digital Commons-TMC (Texas Medical Center) (submittedVersion)
eCommons - AKU (Aga Khan University) (submittedVersion)
Funders: HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446)
HHS | NIH | National Heart, Lung, and Blood Institute (R21HL165376)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipoproteins and Cardiovascular Health
Keywords: PREVENT equations, cardiovascular risk prediction, absolute cardiovascular risk, atherosclerotic cardiovascular disease, heart failure, albumin-creatinine ratio, estimated glomerular filtration rate, social deprivation index, HbA1c, risk discrimination and calibration
MeSH terms: Adult, Aged, Albumins, American Heart Association, Cardiovascular Diseases, Creatinine, Female, Heart Failure, Glycated Hemoglobin, Humans, Male, Middle Aged, Risk Factors, Risk Assessment, Atherosclerosis

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Development and Validation of the American Heart Association’s PREVENT Equations

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks