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Utility of hemoglobin A1c in predicting diabetes risk
Open accessAbstract
Background There is controversy surrounding the issue of whether, and how, to screen adults for type 2 diabetes. Our objective was to measure the incidence of new diabetes among outpatients enrolled in a health care system, and to determine whether hemoglobin A1c (HbA1c) values would allow risk stratification for patients' likelihood of developing diabetes over 3 years.Methods We conducted a prospective cohort study with 3-year follow-up at a single large, tertiary care, Department of Veterans Affairs Medical Center (VAMC). A convenience sample of 1,253 outpatients without diabetes, age 45 to 64, with a scheduled visit at the VAMC, were screened for diabetes using an initial HbA1c measurement. All subjects with HbA1c > or = 6.0% (normal, 4.0% to 6.0%) were invited for follow-up fasting plasma glucose (FPG). We then surveyed patients annually for 3 years to ascertain interval diagnosis of diabetes by a physician. The baseline screening process was repeated 3 years after initial screening. After the baseline screening, new cases of diabetes were defined as either the self-report of a physician's diagnosis of diabetes, or by HbA1c > or = 7.0% or FPG > or = 7.0 mmol/L at 3-year follow-up. The incidence of diabetes was calculated as the number of new cases per person-year of follow-up.Results One thousand two hundred fifty-three patients were screened initially, and 56 (4.5%) were found to have prevalent unrecognized diabetes at baseline. The 1,197 patients without diabetes at baseline accrued 3,257 person-years of follow-up. There were 73 new cases of diabetes over 3 years of follow-up, with an annual incidence of 2.2% (95% confidence interval [CI], 1.7% to 2.7%). In a multivariable logistic regression model, baseline HbA1c and baseline body mass index (BMI) were the only significant predictors of new onset diabetes, with HbA1c having a greater effect than BMI. The annual incidence of diabetes for patients with baseline HbA1c < or = 5.5 was 0.8% (CI, 0.4% to 1.2%); for HbA1c 5.6 to 6.0, 2.5% (CI, 1.6% to 3.5%); and for HbA1c 6.1 to 6.9, 7.8% (CI, 5.2% to 10.4%). Obese patients with HbA1c 5.6 to 6.0 had an annual incidence of diabetes of 4.1% (CI, 2.2% to 6.0%).Conclusions HbA1c testing helps predict the likelihood that patients will develop diabetes in the future. Patients with normal HbA1c have a low incidence of diabetes and may not require rescreening in 3 years. However, patients with elevated HbA1c who do not have diabetes may need more careful follow-up and possibly aggressive treatment to reduce the risk of diabetes. Patients with high-normal HbA1c may require follow-up sooner than 3 years, especially if they are significantly overweight or obese. This predictive value suggests that HbA1c may be a useful test for periodic diabetes screening.
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“Indeed, incidence of diabetes in people with A1C levels in this range is more than 10 times that of people with lower levels (4–7).”
From Diagnosis and classification of diabetes mellitus (2013) · cites this paper as [4]
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“Prospective studies indicate that people within the A1C range of 5.5–6.0% have a 5-year cumulative incidence of diabetes that ranges from 12 to 25% (4–7), which is appreciably (three- to eightfold) higher than incidence in the U.S. population as a whole (8).”
From Diagnosis and classification of diabetes mellitus (2013) · cites this paper as [4]
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Cites
(1993) · New England Journal of Medicine · doi:10.1056/nejm199309303291401 · Cited by 24,667
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011
Tuomilehto, J., Lindström, J., Eriksson, J. G., Valle, T. T., Hämäläinen, H., Ilanne-Parikka, P., Keinänen-Kiukaanniemi, S., Laakso, M., Louheranta, A., Rastas, M., et al. (2001) · New England Journal of Medicine · doi:10.1056/nejm200105033441801 · Cited by 10,873
Stratton, I. M. (2000) · BMJ · doi:10.1136/bmj.321.7258.405 · Cited by 9,059
Turner, R. C., Fox, C., Matthews, McElroy, H. H., Cull, C. A., Holman, R. R., Neil, P., Hadden, D. R., Wright, D., Manley, E., et al. (1998) · The Lancet · Cited by 8,419
Pan, X.-R., Li, G.-W., Hu, Y.-H., Wang, J.-X., Yang, W.-Y., An, Z.-X., Hu, Z.-X., Juan-Lin, Xiao, J.-Z., Cao, H.-B., et al. (1997) · Diabetes Care · doi:10.2337/diacare.20.4.537 · Cited by 4,320
Gupta, A., & Uribarri, J. (2016) · Hormone Research in Paediatrics · doi:10.1159/000444053 · Cited by 4,023
Research works printed but not linked: 1
- Lawson ML, Gerstein HC, Tsui E, Zinman B. Effect of intensive therapy on early macrovascular disease in young individuals with type 1 diabetes. Diabetes Care. 1999;22(S1):B35-B39.
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Kalpana, V. N. S., Mary, J., Mini, S., Soumya, N. P. P., & Mondal, S. (2021) · Bioactive Compounds in Health and Disease · doi:10.31989/bchd.v4i10.842 · Cited by 12
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Chen, K., Lin, J., Lin‐Tan, D., Hsu, C., Huang, W., Yen, T., Weng, S., & Hung, C. (2010) · American Journal of Nephrology · doi:10.1159/000321899 · Cited by 11
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Kolberg, J. A., Gerwien, R. W., Watkins, S. M., Wuestehube, L. J., & Urdea, M. S. (2011) · Expert Review of Molecular Diagnostics · doi:10.1586/erm.11.63 · Cited by 11
Agarwal, G., Kaczorowski, J. A., & Hanna, S. (2013) · Canadian Journal of Diabetes · doi:10.1016/j.jcjd.2013.07.001 · Cited by 11
Umehara, A., Nishioka, M., Obata, T., Ebina, Y., Shiota, H., & Hashida, S. (2009) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2009.06.014 · Cited by 11
Nakiriba, R., Mayega, R. W., Piloya, T., Nabukeera‐Barungi, N., & Idro, R. (2018) · Adolescent Health Medicine and Therapeutics · doi:10.2147/ahmt.s178746 · Cited by 10
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Cosson, E., Chiheb, S., Cussac-Pillegand, C., Banu, I., Hamo-Tchatchouang, E., Nguyen, M. T., Aout, M., Charnaux, N., & Valensi, P. E. (2012) · Diabetes & Metabolism · doi:10.1016/j.diabet.2012.08.013 · Cited by 10
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Kilpatrick, E. S. (2005) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1258/0004563053857860 · Cited by 10
Pham, K., Mulugeta, A., Lumsden, A. L., & Hyppönen, E. (2023) · British Journal of Clinical Pharmacology · doi:10.1111/bcp.15793 · Cited by 9
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Sentell, T. L., Cheng, Y., Saito, E., Seto, T. B., Miyamura, J., Mau, M. K. L. M., & Juarez, D. (2015) · Journal of Clinical & Translational Endocrinology · doi:10.1016/j.jcte.2015.08.002 · Cited by 9
Fu, W., Lin, J., You, C., Zhang, J., Lei, J., Zheng, L., Zheng, B., Liu, M., Liu, L., & Li, N. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16581 · Cited by 8
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Salinas, M., López‐Garrigós, M., Pomares, F., Ruiz-Palomar, J. M., Santo-Quiles, A., Lopez‐Penabad, L., Asencio, A., & Uris, J. (2012) · Laboratory Medicine · doi:10.1309/lmb520nchehktxvr · Cited by 8
Du, Y., Kar, P., Abdelhamid, Y. A., Horowitz, M., & Deane, A. M. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.10.029 · Cited by 8
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Alhassan, Z., Budgen, D., Alessa, A., Alshammari, R., Daghstani, T., & Moubayed, N. A. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-30493-5_34 · Cited by 8
Lee, J., Oh, J. S., Zhu, J. H., Hong, S., Park, S. H., Kim, J. H., Kim, H., Seo, M., Kim, K. W., Lee, D. H., et al. (2020) · Scandinavian Journal of Trauma Resuscitation and Emergency Medicine · doi:10.1186/s13049-020-00782-1 · Cited by 7
Lim, W. X. J., Gammon, C. S., von Hurst, P. R., Chepulis, L. M., Mugridge, O., & Page, R. (2021) · Functional Foods in Health and Disease · doi:10.31989/ffhd.v11i11.829 · Cited by 10
Bancks, M. P., Odegaard, A., Koh, W., Yuan, J., Gross, M. D., & Pereira, M. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119884 · Cited by 7
Kalidhindi, S., Uddandrao, V. V. S., Vadivukkarasi, S., Raveendran, N., & Saravanan, G. (2020) · Cardiovascular & Hematological Agents in Medicinal Chemistry · doi:10.2174/1871525718666200131121419 · Cited by 7
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Sieburth, R., Qiu, M., & Shields, C. L. (2015) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.15-17803 · Cited by 7
Study Of HbA1c As A Reliable Indicator For Metabolic Syndrome In Non Diabetic Patients
Šutković, J., & Abdic-Nekic, V. (2013) · Southeast Europe Journal of Soft Computing · doi:10.21533/scjournal.v2i1.41 · Cited by 6
Ramasamy, J., & Parthasarathi, U. K. (2016) · International Journal of Research in Medical Sciences · doi:10.18203/2320-6012.ijrms20161850 · Cited by 6
Nakagami, T., Tanaka, Y., Oya, J., Kurita, M., Isago, C., Hasegawa, Y., Ito, A., Hirota, N., Tsuzura, R., & Uchigata, Y. (2016) · Primary care diabetes · doi:10.1016/j.pcd.2016.07.006 · Cited by 6
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Wipfli, B., Wild, S., Donovan, C., Hanson, G. C., & Thosar, S. S. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18063230 · Cited by 6
Value of serum 1,5-anhydroglucitol measurements in childhood obesity in the continuum of diabetes
Yoo, H. Y., Kwak, B. O., Son, J. S., Kim, K. S., & Chung, S. (2015) · Annals of Pediatric Endocrinology & Metabolism · doi:10.6065/apem.2015.20.4.192 · Cited by 6
Pratap, J. “., Clements, E., & Levy, D. (2006) · Practical Diabetes · doi:10.1002/pdi.1027 · Cited by 6
Strategies to curb the epidemic of diabetes and obesity in primary care settings
Gary‐Webb, T. L., & Brancati, F. L. (2004) · Journal of General Internal Medicine · doi:10.1111/j.1525-1497.2004.41002.x · Cited by 6
Vajravelu, M. E., Hirschfeld, E., Gebremariam, A., Burant, C., Herman, W. H., Peterson, K. E., Meijer, J. L., & Lee, J. M. (2022) · Hormone Research in Paediatrics · doi:10.1159/000528043 · Cited by 5
Buffarini, R., Restrepo–Méndez, M. C., da Silveira, V. M. F., Miranda, J. J., Gonçalves, H., Oliveira, I. O., Horta, B. L., Gigante, D. P., Menezes, A. M. B., & Assunção, M. C. F. (2016) · PLoS ONE · doi:10.1371/journal.pone.0162614 · Cited by 6
Clinical Implications of the DREAM Study
Davidson, M. B. (2007) · Diabetes Care · doi:10.2337/dc06-2051 · Cited by 5
Mukherjee, U. K., Ye, H., & Chhajed, D. (2025) · Journal of Operations Management · doi:10.1002/joom.1363 · Cited by 6
Sabna, B. S., Mahendran, R., Balakrishnan, J., Huang, C.-Y., Jerimon, P. J., Thomas, A., Eswaran, R., Naveen, P., & Angayarkanni, J. (2025) · Probiotics and Antimicrobial Proteins · doi:10.1007/s12602-025-10626-y · Cited by 4
Mostafa, S. A., Khunti, K., Srinivasan, B. T., Webb, D. R., & Davies, M. J. (2011) · Diabetes Management · doi:10.2217/dmt.10.11 · Cited by 4
van Veggel, K. M., Kruithof, M. K., Roelandse-Koop, E. A., Eekhoff, E. M. W., & Nanayakkara, P. W. B. (2014) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2014.11.003 · Cited by 4
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Chowdhury, S. K. (2022) · Annals of International medical and Dental Research · doi:10.53339/aimdr.2022.8.2.14 · Cited by 3
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Hawes, E. M., Rahim, M., Haratipour, Z., Orun, A. R., O'Rourke, M. L., Oeser, J. K., Kim, K.-H., Claxton, D. P., Blind, R. D., Young, J. D., et al. (2024) · Biochimie · doi:10.1016/j.biochi.2024.02.012 · Cited by 4
Salinas, M., López‐Garrigós, M., Carratalá, A., Aguado, C., Díaz, J., Ortuño, M., Borja, E. R., Yago, M., Chinchilla, V. C., Marcaida, G., et al. (2011) · Endocrinología y Nutrición · doi:10.1016/j.endonu.2011.02.009 · Cited by 4
Salinas, M., López‐Garrigós, M., Carratalá, A., Aguado, C., Díaz, J., Ortuño, M., Borja, E. R., Yago, M., Chinchilla, V. C., Marcaida, G., et al. (2011) · Endocrinología y Nutrición (English Edition) · doi:10.1016/s2173-5093(11)70050-2 · Cited by 4
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Jones, S. L., & Nichols, K. K. (2007) · Optometry · doi:10.1016/j.optm.2007.05.011 · Cited by 4
Body Mass Index as a Guide for Diagnosing Prediabetes and Diabetes
Franklin, J., Thanavaro, J. L., & Ellis, P. A. (2011) · The Journal for Nurse Practitioners · doi:10.1016/j.nurpra.2011.03.032 · Cited by 4
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Maki, K. G. (2017) · Communication Research Reports · doi:10.1080/08824096.2017.1361394 · Cited by 2
Revisiting screening for type 2 diabetes mellitus: the case for and against using HbA1c
Hanna, F., Wilkie, V., Issa, B. G., & Fryer, A. A. (2015) · British Journal of General Practice · doi:10.3399/bjgp15x684637 · Cited by 3
Diagnostic performance of glycated haemoglobin (HbA1c) for diabetes mellitus in dogs
Oikonomidis, I. L., Tsouloufi, T. K., Tzenetidou, Z., Cerón, J. J., Tvarijonaviciute, A., Konstantinidis, A. O., & Soubasis, N. (2023) · The Veterinary Journal · doi:10.1016/j.tvjl.2023.105958 · Cited by 4
Nithiya, T., & Udayakumar, R. (2016) · Journal of Advances in Medical and Pharmaceutical Sciences · doi:10.9734/jamps/2016/24114 · Cited by 3
Wijaya, A., Aditiawati, A., & Saleh, I. (2016) · Sari Pediatri · doi:10.14238/sp17.1.2015.17-20 · Cited by 3
Association of cardiovascular events with glycosylated haemoglobin in diabetic patients
Deo, R., Karki, P., Sharma, S., & Acharya, P. (1970) · Kathmandu University Medical Journal · doi:10.3126/kumj.v6i4.1739 · Cited by 3
Davidson, M. B. (2005) · Current Opinion in Internal Medicine · doi:10.1097/01.med.0000184296.15069.93 · Cited by 3
Aspects of Abnormal Glucose Regulation in Various Manifestations of Coronary Artery Disease
Pétursson, P. (2012) · Gothenburg University Publications Electronic Archive (Gothenburg University) · Cited by 3
Hagman, E. (2016) · Figshare · Cited by 3
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Pennington, B., Cummins, E., Chandler, A., & Fotheringham, J. (2025) · PharmacoEconomics · doi:10.1007/s40273-025-01520-0 · Cited by 2
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Huffman, F. G., Exebio, J. C., Zarini, G. G., & Exebio, C. (2010) · Journal of Immigrant and Minority Health · doi:10.1007/s10903-010-9363-3 · Cited by 2
Modelling irregular samples for analyzing the risk of complications of diabetes mellitus
Kim, D. S., & Walsh, J. P. (2012) · International Conference on Ubiquitous Information Management and Communication (IMCOM) · doi:10.1145/2184751.2184797 · Cited by 2
Chang, K.-S., Lee, K., & Lim, H. (2009) · Korean Diabetes Journal · doi:10.4093/kdj.2009.33.6.537 · Cited by 2
Qvist, R., Ismail, I. S., Chinna, K., & Muniandy, S. (2008) · Indian Journal of Clinical Biochemistry · doi:10.1007/s12291-008-0055-x · Cited by 2
Nutritional Management of Diabetes Mellitus
(2016) · CRC Press eBooks · doi:10.1201/9781315381664-3 · Cited by 2
Rodrigues, F. F. L. (2011) · doi:10.11606/d.22.2011.tde-18072011-105441 · Cited by 2
Cohen, C. C., Hollands, S., & Liu, H. H. (2020) · American Journal of Health Promotion · doi:10.1177/0890117120927307 · Cited by 1
Diabetes and Health Care: An Overview
Abhilash, M., & Augustine, R. (2014) · Apple Academic Press eBooks · doi:10.1201/b16415-6 · Cited by 2
Abhilash, M., & Augustine, R. (2014) · Apple Academic Press eBooks · doi:10.1201/b16415-2 · Cited by 1
Bashir, M. I., Wani, A. I., & Masoodi, S. R. (2011) · J Med Sci · doi:10.33883/jms.v14i1.62 · Cited by 1
Pyadala, N., Mallepaddi, P. C., Ravi Kumar, B. N., Konyak, M. N., & Polvarapu, R. G. (2022) · Asian Journal of Medical Sciences · doi:10.3126/ajms.v13i5.42905 · Cited by 1
G6PC1 and G6PC2 influence G6P flux but not HSD11B1 activity
Hawes, E. M., Boortz, K. A., Oeser, J. K., O’Rourke, M. L., & O’Brien, R. M. (2023) · Journal of Molecular Endocrinology · doi:10.1530/jme-23-0070 · Cited by 1
Ercan, Ş., Yücel, N., & Orçun, A. (2013) · Journal of Medical Biochemistry · doi:10.2478/jomb-2014-0017 · Cited by 1
Al-Mutairi, G. F., Abdul-Halim, I. M., Albawi, A. A., & El-Shazly, M. K. (2013) · Greener Journal of Medical Sciences · doi:10.15580/gjms.2013.2.012013399 · Cited by 1
Rani, K., Singh, S., Bansal, M., & Gupta, V. (2016) · Heart India · doi:10.4103/2321-449x.178123 · Cited by 1
Suman, S., & Dey, S. (2020) · International Journal of Home Science · doi:10.22271/23957476.2020.v6.i3i.1093 · Cited by 1
Utility of hemoglobin A1c to screen for impaired glucose tolerance
Ginting, E. K., Aditiawati, A., & Irfanuddin, I. (2014) · Wahana Riset Akuntansi · doi:10.14238/pi54.4.2014.07 · Cited by 1
HbA1c-Bestimmung – ein neues Diagnosekriterium? / HbA1c – The new diagnostic criterion?
Steveling, A., Völzke, H., Nauck, M. A., & Wallaschofski, H. (2009) · Journal of Laboratory Medicine · doi:10.1515/jlm.2009.003 · Cited by 1
The Evidence to Screen for Type 2 Diabetes
Engelgau, M. M., & Narayan, K. M. V. (2010) · Wiley eBooks · doi:10.1002/9780470682807.ch6 · Cited by 1
Hathaway, Q. A. (2019) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.4052 · Cited by 1
Atualização dos critérios diagnósticos para Diabetes Mellitus utilizando a A1C
Magalhães, G. L., Júnior, C. A. M., de Oliveira, C. M., & Mundim, A. V. (2011) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
Is Prediabetes a Risk Factor or is it a Disease?
Muthusamy, K., & Vella, A. V. (2011) · Wiley eBooks · doi:10.1002/9781444340280.ch1
Sánchez, M. V. M., Bonilla, A. G., & Oropesa, C. F. (2011) · Farmacéuticos de Atención Primaria · doi:10.1016/s2172-3761(11)70019-x
HbA1c determination – A new diagnostic criterion?1
Steveling, A., Völzke, H., Nauck, M. A., & Wallaschofski, H. (2009) · Journal of Laboratory Medicine · doi:10.1515/jlm.2009.003et
Pioglitazone for adults with high risk of developing type 2 diabetes mellitus
Cao, L., Sun, H., Wu, H., Lü, Q., & McKee, A. M. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd011759
RetractedUtility of hemoglobin A1c to screen for impaired glucose tolerance
Ginting, E. K., Aditiawati, A., & Irfanuddin, I. (2014) · Paediatrica Indonesiana · doi:10.14238/pi54.4.2014.223-6
Yücel, N., Orçun, A., & Kartal, L. K. (2014)
Glucose Challenge Test as a Predictor of Type 2 Diabetes
Overton, R. (2022) · Digital Archive @ GSU · doi:10.57709/7941068
Rationalisation of the biochemistry laboratory : which way forwards?
Buhagiar, G. (2005) · OAR@UM (University of Malta)
Genetic and Functional Studies Implicate G6PC2 in the Regulation of Fasting Blood Glucose
Bouatia‐Naji, N., & O’Brien, R. M. (2016) · Springer eBooks · doi:10.1007/978-3-319-01574-3_16
Medication Adherence of Older Adults with Diabetes Mellitus Type II
Hutapea, D. M. M. (2016)
(2019) · University of Thi-Qar Journal of Science · doi:10.32792/utq/utjsci/vol5/3/6
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Turner, M. (2017) · uO Research (University of Ottawa) · doi:10.20381/ruor-20940
Diagnostik und Pathogenese des Diabetes mellitus Typ 2
Lehmann, R., & Spinas, G. A. (2005) · Swiss Medical Forum ‒ Schweizerisches Medizin-Forum · doi:10.4414/smf.2005.05653
Diagnostic Criteria for Prediabetes
Kim, G. E. (2018) · Elsevier eBooks · doi:10.1016/b978-0-323-55138-0.00003-6
Kazemi, M., Nezamzadeh, M., & Farsi., F. (2019) · Military Caring Sciences · doi:10.29252/mcs.6.1.1
Assessment of prevalence of dry eyes in diabetic patients
Kinga, N. (2019) · International Journal of Advanced Research in Medicine · doi:10.22271/27069567.2019.v1.i2a.6
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Vyas, D. R., Vyas, R. K., & Soni, Y. (2020) · Saudi Journal of Medical and Pharmaceutical Sciences · doi:10.36348/sjmps.2020.v06i01.018
Jonker, L., Fisher, S., Westgate, R., & Overend, L. (2020) · British Journal of Diabetes · doi:10.15277/bjd.2020.238
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Sweeney, E. L. (2019) · Northumbria Research Link (Northumbria University)
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Rancati, L. B. (2004)
Lloyd, I., & Saunders, P. (2020) · CAND Journal · doi:10.54434/candj.64
de Courten, M. (2010) · doi:10.1002/9780470682807.ch2
Metadata
- Authors
- Edelman, D., Olsen, M. K., Dudley, T. K., Harris, A. C., & Oddone, E. Z.
- Affiliations
- Duke University (US)
- Durham VA Medical Center (US)
- Corresponding author
- Edelman, David
- Venue
- Journal of General Internal Medicine
- Published
- 2004-12
- Volume
- 19
- Issue
- 12
- Pages
- 1175-1180
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC1492588
- OpenAlex
- W2044864388
- Cited by
- 213
- References
- 38
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 4 · 2023: 11 · 2022: 4 · 2021: 7 · 2020: 11 · 2019: 8 · 2018: 7 · 2017: 4 · 2016: 17 · 2015: 11 · 2014: 14 · 2013: 12 · 2012: 10
- FWCI
- 4.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of General Internal Medicine (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Keywords
- HbA1c, type 2 diabetes, diabetes screening, diabetes risk prediction, risk stratification, diabetes incidence, fasting blood glucose, body mass index, veterans, outpatients, undiagnosed diabetes, glycemic control, veterans health system, prediabetes, Diabetes Prevention Program, prediabetes screening
- MeSH terms
- Blood Glucose, Diabetes Mellitus, Type 2, Follow-Up Studies, Glycated Hemoglobin, Humans, Middle Aged, Obesity, Prospective Studies, Regression Analysis, Body Mass Index
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.
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