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Cited by 174Cardiac Imaging and DiagnosticsHealth Promotion and Cardiovascular PreventionLipoproteins and Cardiovascular Health

Incidental Coronary Artery Calcium: Opportunistic Screening of Previous Nongated Chest Computed Tomography Scans to Improve Statin Rates (NOTIFY-1 Project)

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Sandhu, Alexander T., Rodriguez, Fatima, Ngo, Summer, Patel, Bhavik N., Mastrodicasa, Domenico, Eng, David, Khandwala, Nishith, Balla, Sujana +2 more·2023·Circulation
DOI 10.1161/circulationaha.122.062746PMC PMC10108579
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Abstract

Background: Coronary artery calcium (CAC) can be identified on nongated chest computed tomography (CT) scans, but this finding is not consistently incorporated into care. A deep learning algorithm enables opportunistic CAC screening of nongated chest CT scans. Our objective was to evaluate the effect of notifying clinicians and patients of incidental CAC on statin initiation. Methods: NOTIFY-1 (Incidental Coronary Calcification Quality Improvement Project) was a randomized quality improvement project in the Stanford Health Care System. Patients without known atherosclerotic cardiovascular disease or a previous statin prescription were screened for CAC on a previous nongated chest CT scan from 2014 to 2019 using a validated deep learning algorithm with radiologist confirmation. Patients with incidental CAC were randomly assigned to notification of the primary care clinician and patient versus usual care. Notification included a patient-specific image of CAC and guideline recommendations regarding statin use. The primary outcome was statin prescription within 6 months. Results: Among 2113 patients who met initial clinical inclusion criteria, CAC was identified by the algorithm in 424 patients. After chart review and additional exclusions were made, a radiologist confirmed CAC among 173 of 194 patients (89.2%) who were randomly assigned to notification or usual care. At 6 months, the statin prescription rate was 51.2% (44/86) in the notification arm versus 6.9% (6/87) with usual care ( P <0.001). There was also more coronary artery disease testing in the notification arm (15.1% [13/86] versus 2.3% [2/87]; P =0.008). Conclusions: Opportunistic CAC screening of previous nongated chest CT scans followed by clinician and patient notification led to a significant increase in statin prescriptions. Further research is needed to determine whether this approach can reduce atherosclerotic cardiovascular disease events. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT04789278.

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  • Three included studies employed an AI algorithm (Bunkerhill Health) in which co-investigator CPL holds equity interest.

    “Three included studies41–43 employed an AI algorithm (Bunkerhill Health) in which co-investigator CPL holds equity interest.”

    From Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review (2026) · cites this paper as [41]

    The Methods section (Identification of CAC; page unavailable) confirms that this study used a deep-learning CAC algorithm. Our copy does not identify it as a Bunkerhill Health algorithm or establish that three studies used it. The co-investigator’s equity interest is a disclosure about the citing paper’s authors, not a finding attributed to this source. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • Notification of patients and clinicians based on AI-CAC results increases cardiovascular preventive discussions, statin prescription rates and statin persistence.

    “Notification of patients and clinicians based on these results has been shown to increase cardiovascular preventive discussions, statin prescription rates and statin persistence.40–43”

    From Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review (2026) · cites this paper as [41]

    The Results (Primary Outcome; page not provided) report more documented statin discussions or new prescriptions and a higher six-month statin prescription rate in the notification arm. The Discussion (Limitations; page not provided) says persistence of statin therapy beyond six months still needs to be studied, so this paper does not establish increased statin persistence. (LLM, conf=0.91)

    Experimental — accuracy not yet measured

  • Patient and clinician notifications based on AI-CAC results improved statin prescription and downstream lipid testing, statin persistence, LDL-C reduction and CAD evaluation.

    “Patient and clinician notifications based on AI-CAC results improved statin prescription and downstream lipid testing, statin persistence, low-density lipoprotein cholesterol (LDL-C) reduction and CAD evaluation.41–43”

    From Prognostication and clinical opportunities with AI for coronary artery calcium: a scoping review (2026) · cites this paper as [41]

    The Results (Primary Outcome and Secondary Clinical Outcomes; page unavailable) report more statin prescriptions and lipid testing with notification, and lower LDL-C among patients who had repeat lipid testing. The Abstract Results report more CAD testing. The Limitations state that statin persistence beyond six months was not yet known, so this paper does not support the persistence part of the claim. (LLM, conf=0.91)

    Experimental — accuracy not yet measured

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References 34 · Cited by 174

Research works printed but not linked: 28

  1. [1]Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K and Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation. 2022; 145: e153– e639. 35078371
  2. [2]Metser G, Bradley C, Moise N, Liyanage-Don N, Kronish I and Ye S. Gaps and Disparities in Primary Prevention Statin Prescription During Outpatient Care. Am J Cardiol. 2021; 161: 36– 41. 34794616 PMC8607804
  3. [4]Saeed A, Zhu J, Thoma F, Marroquin O, Aiyer A, Agarwala A, Virani SS, Gulati M, Lee JS, Reis S, Saba S, Ballantyne C and Mulukutla S. Cardiovascular Disease Risk-Based Statin Utilization and Associated Outcomes in a Primary Prevention Cohort: Insights From a Large Health Care Network. Circ Cardiovasc Qual Outcomes. 2021; 14: e007485. 34455825
  4. [5]Clough JD, Martin SS, Navar AM, Lin L, Hardy NC, Rogers U and Curtis LH. Association of Primary Care Providers' Beliefs of Statins for Primary Prevention and Statin Prescription. J Am Heart Assoc. 2019; 8: e010241. 30681391 PMC6405576
  5. [6]Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, Liu K, Shea S, Szklo M, Bluemke DA, O'Leary DH, Tracy R, Watson K, Wong ND and Kronmal RA. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008; 358: 1336– 45. 18367736
  6. [8]Budoff MJ, Lutz SM, Kinney GL, Young KA, Hokanson JE, Barr RG, Steiner R, Nath H, Lopez-Garcia C, Duca LM, Rahmani S, Osawa K, Regan EA, Li D and Casaburi R. Coronary Artery Calcium on Noncontrast Thoracic Computerized Tomography Scans and All-Cause Mortality. Circulation. 2018; 138: 2437– 2438. 30571584 PMC6317728
  7. [9]Eng D, Chute C, Khandwala N, Rajpurkar P, Long J, Shleifer S, Khalaf MH, Sandhu AT, Rodriguez F, Maron DJ, Seyyedi S, Marin D, Golub I, Budoff M, Kitamura F, Takahashi MS, Filice RW, Shah R, Mongan J, Kallianos K, Langlotz CP, Lungren MP, Ng AY and Patel BN. Automated coronary calcium scoring using deep learning with multicenter external validation. NPJ Digit Med. 2021; 4: 88. 34075194 PMC8169744
  8. [11]O'Sullivan JW, Muntinga T, Grigg S and Ioannidis JPA. Prevalence and outcomes of incidental imaging findings: umbrella review. BMJ. 2018; 361: k2387. 29914908 PMC6283350
  9. [12]Ganguli I, Simpkin AL, Lupo C, Weissman A, Mainor AJ, Orav EJ, Rosenthal MB, Colla CH and Sequist TD. Cascades of Care After Incidental Findings in a US National Survey of Physicians. JAMA Netw Open. 2019; 2: e1913325. 31617925 PMC6806665
  10. [13]Chiles C, Duan F, Gladish GW, Ravenel JG, Baginski SG, Snyder BS, DeMello S, Desjardins SS, Munden RF and Team NS. Association of Coronary Artery Calcification and Mortality in the National Lung Screening Trial: A Comparison of Three Scoring Methods. Radiology. 2015; 276: 82– 90. 25759972 PMC5137795
  11. [14]Haller C, Vandehei A, Fisher R, Boster J, Shipley B, Kaatz C, Harris J, Shin SR, Townsend L, Rouse J, Davis S, Aden J and Thomas D. Incidence and Implication of Coronary Artery Calcium on Non-gated Chest Computed Tomography Scans: A Large Observational Cohort. Cureus. 2019; 11: e6218. 31890419 PMC6929257
  12. [15]Hughes-Austin JM, Dominguez A 3rd, Allison MA, Wassel CL, Rifkin DE, Morgan CG, Daniels MR, Ikram U, Knox JB, Wright CM, Criqui MH and Ix JH. Relationship of Coronary Calcium on Standard Chest CT Scans With Mortality. JACC Cardiovasc Imaging. 2016; 9: 152– 9. 26777213 PMC4744104
  13. [16]Mets OM, Vliegenthart R, Gondrie MJ, Viergever MA, Oudkerk M, de Koning HJ, Mali WP, Prokop M, van Klaveren RJ, van der Graaf Y, Buckens CF, Zanen P, Lammers JW, Groen HJ, Isgum I and de Jong PA. Lung cancer screening CT-based prediction of cardiovascular events. JACC Cardiovasc Imaging. 2013; 6: 899– 907. 23769488
  14. [17]Xie X, Zhao Y, de Bock GH, de Jong PA, Mali WP, Oudkerk M and Vliegenthart R. Validation and prognosis of coronary artery calcium scoring in nontriggered thoracic computed tomography: systematic review and meta-analysis. Circ Cardiovasc Imaging. 2013; 6: 514– 21. 23756678
  15. [18]Balakrishnan R, Nguyen B, Raad R, Donnino R, Naidich DP, Jacobs JE and Reynolds HR. Coronary artery calcification is common on nongated chest computed tomography imaging. Clin Cardiol. 2017; 40: 498– 502. 28300293 PMC6490415
  16. [19]Kirsch J, Martinez F, Lopez D, Novaro GM and Asher CR. National trends among radiologists in reporting coronary artery calcium in non-gated chest computed tomography. Int J Cardiovasc Imaging. 2017; 33: 251– 257. 27677761
  17. [20]Phillips WJ, Johnson C, Law A, Turek M, Small AR, Inacio JR, Dent S, Ruddy T, Beanlands RS, Chow BJW and Small GR. Reporting of coronary artery calcification on chest CT studies in breast cancer patients at high risk of cancer therapy related cardiac events. Int J Cardiol Heart Vasc. 2018; 18: 12– 16. 29750180 PMC5941242
  18. [22]Pickhardt PJ, Graffy PM, Perez AA, Lubner MG, Elton DC, Summers RM. Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value. Radiographics. 2021; 41(2): 524– 542. 33646902 PMC7924410
  19. [23]Naslund U, Ng N, Lundgren A, Fharm E, Gronlund C, Johansson H, Lindahl B, Lindahl B, Lindvall K, Nilsson SK, Nordin M, Nordin S, Nyman E, Rocklov J, Vanoli D, Weinehall L, Wennberg P, Wester P, Norberg M and group Vt. Visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA): a pragmatic, open-label, randomised controlled trial. Lancet. 2019; 393: 133– 142. 30522919
  20. [24]Rozanski A, Gransar H, Shaw LJ, Kim J, Miranda-Peats L, Wong ND, Rana JS, Orakzai R, Hayes SW, Friedman JD, Thomson LE, Polk D, Min J, Budoff MJ and Berman DS. Impact of coronary artery calcium scanning on coronary risk factors and downstream testing the EISNER (Early Identification of Subclinical Atherosclerosis by Noninvasive Imaging Research) prospective randomized trial. J Am Coll Cardiol. 2011; 57: 1622– 32. 21439754 PMC3104928
  21. [26]Benner JS, Erhardt L, Flammer M, Moller RA, Rajicic N, Changela K, Yunis C, Cherry SB, Gaciong Z, Johnson ES, Sturkenboom MC, Garcia-Puig J, Girerd X and Investigators RO. A novel programme to evaluate and communicate 10-year risk of CHD reduces predicted risk and improves patients' modifiable risk factor profile. Int J Clin Pract. 2008; 62: 1484– 98. 18691228 PMC2658032
  22. [27]Jacobson TA, Gutkin SW and Harper CR. Effects of a global risk educational tool on primary coronary prevention: the Atherosclerosis Assessment Via Total Risk (AVIATOR) study. Curr Med Res Opin. 2006; 22: 1065– 73. 16846539
  23. [28]Karmali KN, Persell SD, Perel P, Lloyd-Jones DM, Berendsen MA and Huffman MD. Risk scoring for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2017; 3: CD006887. 28290160 PMC6464686
  24. [29]Persell SD, Brown T, Lee JY, Shah S, Henley E, Long T, Luther S, Lloyd-Jones DM, Jean-Jacques M, Kandula NR, Sanchez T and Baker DW. Individualized Risk Communication and Outreach for Primary Cardiovascular Disease Prevention in Community Health Centers: Randomized Trial. Circ Cardiovasc Qual Outcomes. 2015; 8: 560– 6. 26555123
  25. [30]Persell SD, Lloyd-Jones DM, Friesema EM, Cooper AJ and Baker DW. Electronic health record-based patient identification and individualized mailed outreach for primary cardiovascular disease prevention: a cluster randomized trial. J Gen Intern Med. 2013; 28: 554– 60. 23143672 PMC3599027
  26. [31]Uretsky S, Chokshi N, Kobrinski T, Agarwal SK, Po JR, Awan H, Jagarlamudi A, Gudiwada SP, D'Avino RC and Rozanski A. The interplay of physician awareness and reporting of incidentally found coronary artery calcium on the clinical management of patients who underwent noncontrast chest computed tomography. Am J Cardiol. 2015; 115: 1513– 7. 25900351
  27. [32]Nelson AJ, Haynes K, Shambhu S, Eapen Z, Cziraky MJ, Nanna MG, Calvert SB, Gallagher K, Pagidipati NJ and Granger CB. High-Intensity Statin Use Among Patients With Atherosclerosis in the U.S. J Am Coll Cardiol. 2022; 79: 1802– 1813. 35512860 PMC9344279
  28. [33]McClelland RL, Chung H, Detrano R, Post W and Kronmal RA. Distribution of coronary artery calcium by race, gender, and age: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Circulation. 2006; 113: 30– 7. 16365194

Authors
Sandhu, A. T., Rodriguez, F., Ngo, S., Patel, B. N., Mastrodicasa, D., Eng, D., Khandwala, N., Balla, S., Sousa, D., & Maron, D. J.
Affiliations
  • VA Palo Alto Health Care System (US)
  • Division of Cardiovascular Medicine, Department of Medicine (A.T.S., F.R., S.N., D.J.M.), Stanford University, CA.
  • Stanford Medicine (US)
  • Mayo Clinic in Arizona (US)
  • University of California, San Francisco (US)
  • Patient Representative, Hollister, CA (D.S.).
ORCID
Venue
Circulation
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2023-02-28
Volume
147
Issue
9
Pages
703-714
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
DOI
10.1161/circulationaha.122.062746
PMC
PMC10108579
OpenAlex
W4308364833
Cited by
174
References
34
Citations by year
2026: 51 · 2025: 60 · 2024: 45 · 2023: 18
FWCI
17.48
Type
journal article
Language
en
Open access
Locations
  • Circulation (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • HHS | NIH | National Heart, Lung, and Blood Institute (1K23HL151672-01, 5K01HL144607-02)
  • American Heart Association (American Heart Association/Robert Wood Johnson Harold Amos Medical Faculty Development Program)
  • Doris Duke Charitable Foundation (2022051)
  • Stanford University (Human-Centered Artificial Intelligence Seed Grant)
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
  • Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
Keywords
coronary artery calcium, incidental finding, opportunistic screening, deep learning algorithms, statin prescribing, patient notification, atherosclerotic cardiovascular disease, primary care, quality improvement
MeSH terms
Calcium, Cardiovascular Diseases, Coronary Artery Disease, Coronary Vessels, Humans, Risk Factors, Tomography, X-Ray Computed, Risk Assessment, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Atherosclerosis, Vascular Calcification

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