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Classification of Heart Failure in the Atherosclerosis Risk in Communities (ARIC) Study: A Comparison of Diagnostic Criteria
Open accessAbstract
Background—: Population-based research on heart failure (HF) is hindered by lack of consensus on diagnostic criteria. Framingham (FRM), National Health and Nutrition Examination Survey (NHANES), Modified Boston (MBS), Gothenburg (GTH), and International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) code criteria, do not differentiate acute decompensated heart failure (ADHF) from chronic stable HF. We developed a new classification protocol for identifying ADHF in the Atherosclerosis Risk in Communities (ARIC) Study and compared it with these other schemes. Methods and Results—: A sample of 1180 hospitalizations with a patient address in 4 study communities and eligible discharge codes were selected. After assessing whether the chart contained evidence of possible HF signs, 705 were fully abstracted. Two independent reviewers classified each case as ADHF, chronic stable HF, or no HF, using ARIC classification guidelines. Fifty-nine percent of cases met ARIC criteria for ADHF and 13.9% and 27.1% were classified as chronic stable HF or no HF, respectively. Among events classified as HF by FRM criteria, 68.4% were validated as ADHF, 9.6% as chronic stable HF, and 21.9% as no HF. However, 92.5% of hospitalizations with a primary ICD-9-CM 428 “heart failure” code were validated as ADHF. Sensitivities of comparison criteria to classify ADHF ranged from 38–95%, positive predictive values from 62–92%, and specificities from 19–96%. Conclusions—: Although comparison criteria for classifying HF were moderately sensitive in identifying ADHF, specificity varied when applied to a randomly selected set of suspected HF hospitalizations in the community.
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Statistical Methods for Rates and Proportions
Fleiss, J. L., Levin, B., & Paik, M. C. (2003) · Wiley Series in Probability and Statistics · doi:10.1002/0471445428 · Cited by 18,646
The natural history of congestive heart failure: the Framingham study
McKee, P. A., Castelli, W. P., McNamara, P. M., & Kannel, W. B. (1971) · New England Journal of Medicine · doi:10.1056/nejm197112232852601 · Cited by 3,448
Long-term trends in the incidence of and survival with heart failure
Levy, D., Kenchaiah, S., Larson, M. G., Benjamin, E. J., Kupka, M. J., Ho, K. K. L., Murabito, J. M., & Vasan, R. S. (2002) · New England Journal of Medicine · doi:10.1056/nejmoa020265 · Cited by 2,152
Mant, J., Doust, J., Roalfe, A., Barton, P., Cowie, M., Glasziou, P., Mant, D., McManus, R., Holder, R., Deeks, J., et al. (2009) · Health Technology Assessment · doi:10.3310/hta13320 · Cited by 498
Hewitt, C., Gilbody, S., Brealey, S., Paulden, M., Palmer, S., Mann, R., Green, J., Morrell, J., Barkham, M., Light, K., et al. (2009) · Health Technology Assessment · doi:10.3310/hta13360 · Cited by 330
Cited by
Groenewegen, A., Rutten, F. H., Mosterd, A., & Hoes, A. W. (2020) · European Journal of Heart Failure · doi:10.1002/ejhf.1858 · Cited by 2,043
Roger, V. L. (2013) · Circulation Research · doi:10.1161/circresaha.113.300268 · Cited by 1,728
Final Report of a Trial of Intensive versus Standard Blood-Pressure Control
The SPRINT Research Group (2021) · New England Journal of Medicine · doi:10.1056/nejmoa1901281 · Cited by 454
Obesity and subtypes of incident cardiovascular disease
Ndumele, C. E., Matsushita, K., Lazo, M., Bello, N., Blumenthal, R. S., Gerstenblith, G., Nambi, V., Ballantyne, C. M., Solomon, S. D., Selvin, E., et al. (2016) · Journal of the American Heart Association · doi:10.1161/jaha.116.003921 · Cited by 259
Lee, A. K., Warren, B., Lee, C. J., McEvoy, J. W., Matsushita, K., Huang, E. S., Sharrett, A. R., Coresh, J., & Selvin, E. (2018) · Diabetes Care · doi:10.2337/dc17-1669 · Cited by 226
Shah, R. V., Murthy, V. L., Colangelo, L. A., Reis, J., Venkatesh, B. A., Sharma, R., Abbasi, S. A., Goff, D. C., Carr, J. J., Rana, J. S., et al. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2015.6309 · Cited by 158
Fructosamine and glycated albumin and the risk of cardiovascular outcomes and death
Selvin, E., Rawlings, A. M., Lutsey, P. L., Maruthur, N., Pankow, J. S., Steffes, M., & Coresh, J. (2015) · Circulation · doi:10.1161/circulationaha.115.015415 · Cited by 151
“Heart failure was defined by a hospitalization with an International Classification of Diseases (ICD)-9 code of 428 or death with an underlying cause of ICD-9 428 or ICD-10 I50.”
MethodBiomarker-based risk prediction of incident heart failure in pre-diabetes and diabetes
Pandey, A., Vaduganathan, M., Patel, K. V., Ayers, C., Ballantyne, C. M., Kosiborod, M. N., Carnethon, M., DeFilippi, C., McGuire, D. K., Khan, S. S., et al. (2021) · JACC: Heart Failure · doi:10.1016/j.jchf.2020.10.013 · Cited by 144
Pandey, A., Patel, K. V., Bahnson, J. L., Gaussoin, S. A., Martin, C. K., Balasubramanyam, A., Johnson, K. C., McGuire, D. K., Bertoni, A. G., Kitzman, D., et al. (2020) · Circulation · doi:10.1161/circulationaha.119.044865 · Cited by 127
Self-citationUpadhya, B., Rocco, M., Lewis, C. E., Oparil, S., Lovato, L. C., Cushman, W. C., Bates, J. T., Bello, N. A., Aurigemma, G., Fine, L. J., et al. (2017) · Circulation: Heart Failure · doi:10.1161/circheartfailure.116.003613 · Cited by 118
Genetic Variants in SGLT1, Glucose Tolerance, and Cardiometabolic Risk
Seidelmann, S. B., Feofanova, E., Yu, B., Franceschini, N., Claggett, B., Kuokkanen, M., Puolijoki, H., Ebeling, T., Perola, M., Salomaa, V., et al. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.07.061 · Cited by 97
Selvin, E., Wang, D., Matsushita, K., Grams, M. E., & Coresh, J. (2018) · Annals of Internal Medicine · doi:10.7326/m18-0091 · Cited by 73
Patel, K. V., Bahnson, J. L., Gaussoin, S. A., Johnson, K. C., Pi-Sunyer, X., White, U., Olson, K. L., Bertoni, A. G., Kitzman, D. W., Berry, J. D., et al. (2020) · Circulation · doi:10.1161/circulationaha.120.050941 · Cited by 69
Self-citationMamic, P., Heidenreich, P. A., Hedlin, H., Tennakoon, L., & Staudenmayer, K. L. (2016) · Journal of Cardiac Failure · doi:10.1016/j.cardfail.2016.06.005 · Cited by 59
Diabetes and Progression of Heart Failure
Echouffo-Tcheugui, J. B., Ndumele, C. E., Zhang, S., Florido, R., Matsushita, K., Coresh, J., Skali, H., Shah, A. M., & Selvin, E. (2022) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2022.03.378 · Cited by 54
Physical activity and incidence of heart failure in postmenopausal women
LaMonte, M. J., Manson, J. E., Chomistek, A. K., Larson, J. C., Lewis, C. E., Bea, J. W., Johnson, K. C., Li, W., Klein, L., LaCroix, A. Z., et al. (2018) · JACC: Heart Failure · doi:10.1016/j.jchf.2018.06.020 · Cited by 49
Teramoto, K., Nadruz Junior, W., Matsushita, K., Claggett, B., John, J. E., Skali, H., Solomon, S., Cheng, S., & Shah, A. M. (2020) · Hypertension · doi:10.1161/hypertensionaha.120.14833 · Cited by 36
Tin, A., Bressler, J., Simino, J., Sullivan, K. J., Mei, H., Windham, B. G., Griswold, M., Gottesman, R. F., Boerwinkle, E., Fornage, M., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000200520 · Cited by 33
Correlations Within and Between Highly Multiplexed Proteomic Assays of Human Plasma
Rooney, M. R., Chen, J., Ballantyne, C. M., Hoogeveen, R. C., Boerwinkle, E., Yu, B., Walker, K. A., Schlosser, P., Selvin, E., Chatterjee, N., et al. (2025) · Clinical Chemistry · doi:10.1093/clinchem/hvaf030 · Cited by 33
Cuthbertson, C. C., Tan, X., Heiss, G., Kucharska‐Newton, A., Nichols, H. B., Kubota, Y., & Evenson, K. R. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.119.012657 · Cited by 26
Self-citation
Metadata
- Authors
- Rosamond, W. D., Chang, P. P., Baggett, C., Johnson, A., Bertoni, A. G., Shahar, E., Deswal, A., Heiss, G., & Chambless, L. E.
- Venue
- Circulation: Heart Failure
- Published
- 2012-03
- Volume
- 5
- Issue
- 2
- Pages
- 152-159
- ISSN
- 1941-3289 (ISSN-L)
- 1941-3297
- OpenAlex
- W2106464473
- Cited by
- 349
- References
- 5
- FWCI
- 9.21
- Type
- journal article
- Language
- en
- Open access
- bronze
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