Evaluation of the Finnish Diabetes Risk Score as a screening tool for impaired fasting glucose, impaired glucose tolerance and undetected diabetes
Abstract
Aim To evaluate the performance of FINDRISC as a screening tool for prediabetes - impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) and undetected diabetes (UDD) in subjects at risk of developing diabetes. Subjects and methods 2169 subjects with at least one risk factor for diabetes completed the FINDRISC questionnaire and underwent an oral glucose tolerance test. FINDRISC performance was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results 56.6% of subjects demonstrated normal glucose tolerance (NGT), 14.5% - IFG, 11.4% - IGT and 17.5% - UDD. NGT group demonstrated mean FINDRISC 10.1±3.4, IFG group - 13.8±4.3 (p Conclusions FINDRISC is a feasible, non-invasive and useful tool for identifying subjects at risk for undetected diabetes and prediabetes. Laboratory screening should be performed in subjects with FINDRISC higher than 10.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
FINDRISC is the most commonly evaluated diabetes risk score worldwide and has been recommended as the best available risk assessment tool for clinical practice by a systematic review.
“Moreover, FINDRISC is the most commonly evaluated diabetes risk score worldwide [17,18,19,20,21,22,23,24,25] and has been recommended as the best available risk assessment tool for use in the clinical practice by a systematic review [11].”
From A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults (2015) · cites this paper as [24]
Cites
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 · see citing works
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 · cited 2× · see citing works
“[11] Tuomilehto J, Lindström J, Eriksson J, Valle T, Hämäläinen H, Ilanne-Parikka P, et al.”
BackgroundAdapting the Diabetes Prevention Program Lifestyle Intervention for Delivery in the Community
Ackermann, R. T., & Marrero, D. G. (2007) · The Diabetes Educator · doi:10.1177/0145721706297743 · Cited by 220 · see citing works
Ilanne-Parikka, P., Eriksson, J. G., Lindström, J., Peltonen, M., Aunola, S., Hämäläinen, H., Keinänen-Kiukaanniemi, S., Laakso, M., Valle, T. T., Lahtela, J., et al. (2008) · Diabetes Care · doi:10.2337/dc07-1117 · Cited by 218 · see citing works
Lipoprotein abnormalities and their consequences for patients with type 2 diabetes
Krentz, A. J. (2003) · Diabetes Obesity and Metabolism · doi:10.1046/j.1462-8902.2003.0310.x · Cited by 205 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Recommendations on screening for type 2 diabetes in adults
Pottie, K., Jaramillo, A., Lewin, G., Dickinson, J., Bell, N., Brauer, P., Dunfield, L., Joffres, M., Singh, H., & Tonelli, M. (2012) · Canadian Medical Association Journal · doi:10.1503/cmaj.120732 · Cited by 133 · see citing works
““High risk” or “very high risk” as defined by the task force implies a FINDRISC score (Finnish Diabetes Risk Score) of 15 points or higher, which is associated with prevalences of type 2 diabetes detected through screening that are several times higher than in the UK RCT, depending on the population.(21,22) Thus, we c…”
BackgroundZhang, L., Zhang, Z., Zhang, Y., Hu, G., & Chen, L. (2014) · PLoS ONE · doi:10.1371/journal.pone.0097865 · Cited by 130 · see citing works
“However, most previous studies have been conducted in European countries with the majority of participants as Caucasians [26–32] or other single racial groups [24,33–39].”
BackgroundResultMoreira‐Lucas, T., Duncan, A. M., RABASA-LHORET, R. P. R., Vieth, R., Gibbs, A. L., Badawi, A. F., & Wolever, T. M. S. (2016) · Diabetes Obesity and Metabolism · doi:10.1111/dom.12794 · Cited by 75 · see citing works
“Firstly, participants were prescreened via telephone or email using the Finnish Diabetes Risk Score (FINDRISC) (15)”
MethodInfluentialAssyov, Y., Gateva, A., Tsakova, A., & Kamenov, Z. (2017) · Endocrine Research · doi:10.3109/07435800.2016.1155598 · Cited by 62 · see citing works
“FINDRISC questionnaire (20) was performed on all participants, as it has already been validated in a Bulgarian population sample (21).”
MethodAschner, P., Muñoz, Ó., Girón, D., García, O., Fernández-Ávila, D. G., Casas, L., Bohórquez, L. F., Clara María Arango, T., Carvajal, L., Ramírez, D. A., et al. (2016) · Colombia Médica · doi:10.2510/colomb · Cited by 58
Masconi, K. L., Matsha, T. E., Echouffo-Tcheugui, J. B., Erasmus, R. T., & Kengne, A. P. (2015) · The EPMA Journal · doi:10.1186/s13167-015-0028-0 · Cited by 52 · see citing works
“[54] 2004 Validate UK (H) Black, Asian Existing 803 40–75 X X”
BackgroundKu, G. M., & Kegels, G. (2013) · Primary care diabetes · doi:10.1016/j.pcd.2013.07.004 · Cited by 49 · see citing works
Salinero-Fort, M., Burgos-Lunar, C., Lahoz, C., Mostaza, J., Abánades-Herranz, J. C., Laguna-Cuesta, F., Cabo, E. E., García-Iglesias, F., González-Alegre, T., Fernández-Puntero, B., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158489 · Cited by 52 · see citing works
“DM risk scores [9] constitute an easy, non-invasive, and inexpensive approach to the assessment of an individual’s risk of UT2DM and dysglycaemia that can reduce the number of people who have to undergo diagnostic glucose tolerance tests [10].”
BackgroundŠtiglic, G., Fijačko, N., Stožer, A., Sheikh, A., & Pajnkihar, M. (2016) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2016.08.010 · Cited by 48 · see citing works
Hellgren, M. I., Petzold, M., Björkelund, C., Wedel, H., Jansson, P. ‐., & Lindblad, U. (2012) · Diabetic Medicine · doi:10.1111/j.1464-5491.2012.03664.x · Cited by 47 · see citing works
Janghorbani, M., Adineh, H., & Amini, M. (2013) · The review of diabetic studies : RDS · doi:10.1900/rds.2013.10.283 · Cited by 46 · see citing works
“Although the FINDRISC tool was developed and validated in European populations [8-10, 14-21], it is also valid for Middle-Eastern populations, despite different lifestyles.”
MethodVandersmissen, G., & Godderis, L. (2015) · International Journal of Occupational Medicine and Environmental Health · doi:10.13075/ijomeh.1896.00407 · Cited by 44 · see citing works
Jølle, A., Midthjell, K., Holmen, J., Carlsen, S. M., Tuomilehto, J. O., Bjørngaard, J. H., & Åsvold, B. O. (2019) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-000769 · Cited by 47 · see citing works
Mavrogianni, C., Lambrinou, C. P., Androutsos, O., Lindström, J., Kivelä, J., Cardon, G., Huys, N., Tsochev, K., Iotova, V., Chakarova, N., et al. (2019) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2019.02.017 · Cited by 43 · see citing works
Self-citationA Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults
Zhang, Y., Hu, G., Zhang, L., Mayo, R., & Chen, L. (2015) · PLOS ONE · doi:10.1371/journal.pone.0120382 · Cited by 41 · see citing works
“Moreover, FINDRISC is the most commonly evaluated diabetes risk score worldwide [17,18,19,20,21,22,23,24,25] and has been recommended as the best available risk assessment tool for use in the clinical practice by a systematic review [11].”
BackgroundMethodThabit, H., Burns, N., Shah, S., Brema, I., Crowley, V., Finnegan, F. R., Daly, B., & Nolan, J. (2013) · Diabetes & vascular disease research · doi:10.1177/1479164113479808 · Cited by 39 · see citing works
Winkler, G., Hídvégi, T., Vándorfi, G., Balogh, S., & Jermendy, G. (2013) · Medical Science Monitor · doi:10.12659/msm.883747 · Cited by 36 · see citing works
“In other studies using the questionnaire, modified or shortened versions were used [19, 20], risk was determined using receiver operating characteristic (ROC) curves [15], and others performed the OGTT only in subjects with a score of ≥15 [14].”
BackgroundMethodLim, H. M., Chia, Y. C., & Koay, Z. L. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.02.008 · Cited by 38 · see citing works
Fizelova, M., Jauhiainen, R., Stančáková, A., Kuusisto, J., & Laakso, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0166584 · Cited by 30 · see citing works
Meijnikman, A. S., Block, C. D. D., Verrijken, A., Mertens, I., Corthouts, B., & van Gaal, L. (2016) · Journal of diabetes and its complications · doi:10.1016/j.jdiacomp.2016.05.004 · Cited by 34 · see citing works
Impact of sex and age on the performance of FINDRISC: the HUNT Study in Norway
Jølle, A., Midthjell, K., Holmen, J., Tuomilehto, J., Carlsen, S. M., Shaw, J. E., & Åsvold, B. O. (2016) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2016-000217 · Cited by 29 · see citing works
“Serum creatinine (μmol/L) 75 (15) 74 (14) 80 (20) 90 (18) 89 (18) 95 (22)”
Timm, L., Harcke, K., Karlsson, I., Annerstedt, K. S., Alvesson, H., Stattin, N. S., Forsberg, B., Östenson, C., & Daivadanam, M. (2020) · Global Health Action · doi:10.1080/16549716.2020.1795439 · Cited by 31 · see citing works
Finnish Diabetes Risk Score to predict type 2 diabetes in the Isfahan diabetes prevention study.
Janghorbani, M., Adineh, H., & Amini, M. (2013) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.10.018 · Cited by 30 · see citing works
“Although the FINDRISC tool was developed and validated in European populations [7–9,13–20], it is also valid for Middle Eastern populations, despite the differences in lifestyles compared with the western world.”
BackgroundMethodResultInfluentialPrevalence and risk factors for diabetic retinopathy in a high-risk Chinese population
Wang, J., Zhang, R., Chen, R., Sun, J. M., Yang, R., Ke, X.-Y., Chen, H., & Cai, D.-H. (2013) · BMC Public Health · doi:10.1186/1471-2458-13-633 · Cited by 34 · see citing works
“It has been used in different countries for identification of diabetic high-risk individuals [10-21].”
BackgroundDetermining type 2 diabetes risk factors for the adults: A community based study from Turkey.
Cosansu, G., Çelik, S., Özcan, Ş., Olgun, N., Yıldırım, N., & Demir, H. G. (2018) · Primary Care Diabetes · doi:10.1016/j.pcd.2018.05.001 · Cited by 27 · see citing works
Martin, W. P., Sharif, F., & Flaherty, G. (2016) · Irish Journal of Medical Science · doi:10.1007/s11845-016-1442-6 · Cited by 27 · see citing works
Heianza, Y., Arase, Y., Saito, K., Hsieh, S. D., Tsuji, H., Kodama, S., Tanaka, S., Ohashi, Y., Shimano, H., Yamada, N., et al. (2013) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2012-3092 · Cited by 26 · see citing works
Rokhman, M. R., Arifin, B., Zulkarnain, Z., Satibi, S., Perwitasari, D., Boersma, C., Postma, M., & van der Schans, J. (2022) · PLoS ONE · doi:10.1371/journal.pone.0269853 · Cited by 25 · see citing works
“The identification of T2DM can be better addressed using a two-step approach, in which the use of diabetes risk scores as the first step is followed by a blood glucose test [17, 18].”
BackgroundMethodŠtiglic, G., Kocbek, P., Cilar, L., Fijačko, N., Stožer, A., Zaletel, J., Sheikh, A., & Bržan, P. P. (2018) · Diabetic Medicine · doi:10.1111/dme.13605 · Cited by 25 · see citing works
Abdallah, M., Sharbaji, S., Sharbaji, M., Daher, Z., Faour, T., Mansour, Z., & Hneino, M. (2020) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-020-00590-8 · Cited by 29 · see citing works
Salinero-Fort, M., de Burgos-Lunar, C., Prieto, J. M., Rallo, C. L., Abánades-Herranz, J. C., Gómez-Campelo, P., Cuesta, F. L., Estirado-Decabo, E., Iglesias, F. G., Alegre, T. G., et al. (2015) · BMJ Open · doi:10.1136/bmjopen-2014-007195 · Cited by 24 · see citing works
Evaluation of the Finnish Diabetes Risk Score (FINDRISC) for diabetes screening in Kayseri, Turkey
Atayoğlu, A. T., İnanç, N., Başmısırlı, E., & Çapar, A. G. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.01.002 · Cited by 22 · see citing works
Davies, M. J., Gray, L. J., Ahrabian, D., Carey, M., Farooqi, A., Gray, A. M., Goldby, S., Hill, S., Jones, K. L., Leal, J., et al. (2017) · Programme Grants for Applied Research · doi:10.3310/pgfar05020 · Cited by 24 · see citing works
Fokkens, B., van Waateringe, R. V., Mulder, D., Wolffenbuttel, B., & Smit, A. (2017) · Diabetes & Metabolism · doi:10.1016/j.diabet.2017.09.002 · Cited by 21 · see citing works
Uptake of screening for type 2 diabetes risk in general dental practice; an exploratory study
Bould, K., Scott, S., Dunne, S., & Asimakopoulou, K. (2017) · BDJ · doi:10.1038/sj.bdj.2017.174 · Cited by 21 · see citing works
Evaluation of EZSCAN as a screening tool for impaired glucose metabolism.
Chen, L.-Z., Chen, X.-L., Ding, R., Shi, Q.-T., & Hu, D. (2013) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2013.03.001 · Cited by 20 · see citing works
“A sensitivity rate of 67–84% and specificity rate of 61–67% for IGM have been reported from several studies [22,23].”
BackgroundResultNieto-Martinez, R., González-Rivas, J., Ugel, E., Marulanda, M., Durán, M., Mechanick, J., & Aschner, P. (2019) · Primary Care Diabetes · doi:10.1016/j.pcd.2019.04.006 · Cited by 17 · see citing works
EZSCAN as a Screening Tool for Prediabetes and Diabetes in a Large Mexican Population
Sanchez Hernandez, O. E. (2015) · Journal of Diabetes & Metabolism · doi:10.4172/2155-6156.1000505 · Cited by 8 · see citing works
“A sensitivity rate of 67–84% and specificity rate of 61–67% for IGM have been reported from several studies [22,23].”
ResultMyostatin and carbohydrate disturbances
Assyov, Y., Velikova, T., & Kamenov, Z. (2017) · Endocrine Research · doi:10.1080/07435800.2016.1198802 · Cited by 15 · see citing works
“035 Diastolic Blood Pressure*, mmHg 80 (10) 80 (15) 80 (15) ns ns ns AST, U/l 22 [18-29] 21 [15-27] 18 [15-22] ns 0.”
Leung, A. Y. M., Xu, X., Chau, P. H., Yu, E. Y. T., Cheung, M. K. T., Wong, C. K. H., Fong, D., Wong, J. Y. H., & Lam, C. L. K. (2018) · JMIR mhealth and uhealth · doi:10.2196/10662 · Cited by 13 · see citing works
“In the United States, the optimal cutoff value of FINDRISC for identifying undiagnosed diabetes was 11 [31], while in Bulgaria the cutoff point was recommended as 12 (there was no differentiation between sexes) [30], and in Colombia it was 14 (for both men and women) [20].”
Acosta-Reyes, J. L., Garrido, D. P. R., Acosta, T., Aschner, P. J., Fraga, C. A., Vázquez‐Fernández, A., Tuomilehto, J. O., & Gabriel, R. (2025) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2025.112480 · Cited by 14 · see citing works
Mugume, I. B., Wafula, S. T., Kadengye, D. T., & van Olmen, J. (2023) · PLoS ONE · doi:10.1371/journal.pone.0276858 · Cited by 13 · see citing works
Riesgo de Diabetes Mellitus tipo 2, Sobrepeso y Obesidad en adultos del Distrito de Barranquilla
Leyton, M. R., Charris, M. M., Campo, A. M. A., Torres, I. C., Muñoz, M., & Mertínez, M. A. A. (2018) · doi:10.29105/respyn17.4-1 · Cited by 11
Musso, G. (2011) · Annals medicus · doi:10.3109/07853890.2011.579152 · Cited by 11 · see citing works
A meta‐analysis of diabetes risk prediction models applied to prediabetes screening
Liu, Y.-J., Yu, S.-R., Feng, W., Mo, H.-F., Hua, Y.-T., Zhang, M., Zhu, Z. Q., Zhang, X.-P., Wu, Z., Zheng, L., et al. (2024) · Diabetes, obesity and metabolism · doi:10.1111/dom.15457 · Cited by 10 · see citing works
“Of the four pooled models, FINDRISC represents the world's first diabetes risk assessment tool, developed through the cohort study method, and is by far the most widely used tool worldwide, with the highest frequency of external validation being in different ethnic groups or populations.”
BackgroundInfluentialLatest Considerations in Diagnosis and Treatment of Appendicitis During Pregnancy
Lotfipour, S., Jason, M., Liu, V., Helmy, M., Hoonpongsimanont, W., McCoy, C., & Chakravarthy, B. (2018) · Clinical Practice and Cases in Emergency Medicine · doi:10.5811/cpcem.2018.1.36218 · Cited by 10 · see citing works
Hellgren, M., Daka, B., Jansson, P., & Lindblad, U. (2015) · Primary Care Diabetes · doi:10.1016/j.pcd.2014.10.009 · Cited by 10 · see citing works
Limited Effectiveness of Diabetes Risk Assessment Tools in Seniors’ Facility Residents
Featherstone, T. R., Eurich, D. T., & Simpson, S. H. (2016) · Value in Health · doi:10.1016/j.jval.2016.09.2403 · Cited by 8 · see citing works
“[28] Tankova T, Chakarova N, Atanassova I, Dakovska L.”
BackgroundMethodAzzouz, M., Boudiba, A., Guerchani, M., Lyes, Y., Hannachi, R., Baghous, H., Meftah, A., & Mimouni, S. (2014) · Médecine des Maladies Métaboliques · doi:10.1016/s1957-2557(14)70877-6 · Cited by 9 · see citing works
Prediction of a 10-year risk of type 2 diabetes mellitus in the Turkish population
Sezer, Ö., Lafçi, N. Ö., Korkmaz, S., & Dağdeviren, H. (2021) · Medicine · doi:10.1097/md.0000000000027721 · Cited by 8 · see citing works
Brunetti, P., Baldessin, L., & Pagliacci, S. (2021) · Journal of Public Health · doi:10.1093/pubmed/fdab046 · Cited by 8 · see citing works
Levterova, B. A., Orbetzova, M. M., Levterov, G., Dimitrova, D., & Todorov, P. T. (2018) · Biotechnology & Biotechnological Equipment · doi:10.1080/13102818.2018.1532319 · Cited by 12 · see citing works
“The prevalence of patients with diabetes is increasing among all age groups in Bulgaria, mainly due to the rise in overweight and obese people as a consequence of unhealthy diet, and lack of physical activity [2,3].”
BackgroundRecalibration in Validation Studies of Diabetes Risk Prediction Models: A Systematic Review
Masconi, K. L., Matsha, T. E., Erasmus, R. T., & Kengne, A. P. (2015) · International Journal of Statistics in Medical Research · doi:10.6000/1929-6029.2015.04.04.5 · Cited by 7 · see citing works
Murteira, R., Cary, M., Galante, H., Romano, S., Guerreiro, J., & Rodrigues, A. T. (2023) · Primary Care Diabetes · doi:10.1016/j.pcd.2023.04.007 · Cited by 7 · see citing works
Validation of Finnish Diabetes Risk Score Indonesia Version in Yogyakarta
Pertiwi, P., Perwitasari, D., & Satibi, S. (2021) · Borneo Journal of Pharmacy · doi:10.33084/bjop.v4i1.1575 · Cited by 7 · see citing works
Utilização do FINDRISC no Rastreio da Diabetes em Utentes Assintomáticos
Dantas, R., Azevedo, T., Alves, M., Balsa, M., Albuquerque, I., Ferreira, M., Pedrosa, C., Gomes, F., Fonseca, C., & Guimarães, J. (2017) · Revista Portuguesa de Endocrinologia Diabetes e Metabolismo · doi:10.26497/2017.000008.000108 · Cited by 7
Kanellakis, S., Mavrogianni, C., Karatzi, K., Lindstrom, J., Cardon, G., Iotova, V., Wikström, K., Shadid, S., Moreno, L., Tsochev, K., et al. (2020) · Nutrients · doi:10.3390/nu12040960 · Cited by 6 · see citing works
Mahmoodzadeh, S., Jahani, Y., Najafipour, H., Sanjari, M., Shadkam-Farokhi, M., & Shahesmaeili, A. (2022) · International Journal of Endocrinology and Metabolism · doi:10.5812/ijem-127114 · Cited by 5 · see citing works
“In other external validation studies, AUC ranges from 76% to 89% (13-15) for AUSDRISK and from 43% to 82% (16-29) for FINDRISC.”
BackgroundTraoré, S., Paré, B., Dabourou, D. L., Guira, O., Sagna, Y., Kamouni, J. P., Zoungrana, L., Bognounou, R., Tiéno, H., & Drabo, Y. (2021) · Open Journal of Internal Medicine · doi:10.4236/ojim.2021.112003 · Cited by 5 · see citing works
Montes-Ochoa, S., Serna-Arrieta, K., Estrada-Ávila, S., Lopez, F. G., & Sánchez, I. P. (2016) · Medicina y Laboratorio · doi:10.36384/01232576.105 · Cited by 5 · see citing works
“Es importante resaltar que los valores de sensibilidad y especificidad del test se mantienen elevados aun usando puntos de corte más altos [30-32].”
BackgroundArnardóttir, E., Sigurðardóttir, Á., Graue, M., Kolltveit, B. H., & Skinner, T. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20166606 · Cited by 4 · see citing works
“To identify those at risk, the reported best cut-off points may vary between countries, from 11 points in Bulgaria [33] to 15 points in Norway [34], where lower income status in the country may have an influence towards the lower cut-off point [35].”
Zatońska, K., Basiak-Rasała, A., Połtyn–Zaradna, K., Różańska, D., Karczewski, M., Wołyniec, M., & Szuba, A. (2021) · Vascular Health and Risk Management · doi:10.2147/vhrm.s321700 · Cited by 7 · see citing works
Risco de desenvolvimento do diabetes tipo 2 em enfermeiras e sua relação com alterações metabólicas
Sánchez-Jiménez, B., Chico‐Barba, G., Rodríguez-Ventura, A. L., Sámano, R., Veruete-Bedolla, D., & Morales‐Hernández, R. M. (2019) · Revista Latino-Americana de Enfermagem · doi:10.1590/1518-8345.3002.3161 · Cited by 13 · see citing works
“This study was based on the WHO ethical principles (Declaration of Helsinki) and was approved by the Institutional Research, Ethical and Biosafety Committees (registration number: 212250-3300- 11402-01-15).”
Method[Development and validation of a screening score for prediabetes and undiagnosed diabetes.]
Rojas-Martínez, R., Escamilla-Núñez, C., Gómez-Velasco, D., Zárate-Rojas, E., & Aguilar-Salinas, C. (2018) · Salud Pública de México · doi:10.21149/9057 · Cited by 4 · see citing works
Yoles, I., Baevsky, T., Rosenberg, R., & Shevy, M. (2017) · American Journal of Perinatology · doi:10.1055/s-0037-1604193 · Cited by 4 · see citing works
Katoh, S., Peltonen, M., Zeniya, M., Kaji, M., Sakamoto, Y., Utsunomiya, K., & Tuomilehto, J. (2016) · Primary Care Diabetes · doi:10.1016/j.pcd.2015.07.006 · Cited by 4 · see citing works
Estudo LIDIA: risco de diabetes mellitus tipo 2 numa população rural dos Açores
Viveiros, A. S., Borges, M., Martins, R., Anahory, B., & Cordeiro, M. S. (2015) · Revista Portuguesa de Endocrinologia Diabetes e Metabolismo · doi:10.1016/j.rpedm.2014.11.004 · Cited by 4 · see citing works
Goh, G., Ower, P., & Eaton, K. (2021) · British Dental Journal · doi:10.1038/s41415-021-3223-5 · Cited by 3 · see citing works
Marcinkiewicz, A., Hanke, W., Kałużny, P., Lipińska-Ojrzanowska, A., Wiszniewska, M., & Walusiak-Skorupa, J. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15040638 · Cited by 3
Zhang, R., Wang, J., Luo, J., Yang, X.-Y., Yang, R., Cai, D.-H., & Zhang, H. (2015) · PubMed · doi:10.6133/apjcn.2015.24.3.14 · Cited by 4 · see citing works
Ture, N., Emecen, A. N., & Unal, B. (2025) · Primary Health Care Research and Development · doi:10.1017/s1463423625000180 · Cited by 2 · see citing works
“FINDRISC score has been validated in many European countries, including Sweden (Hellgren et al. , 2012), Greece (Makrilakis et al. , 2011), Spain (Soriguer et al. , 2012), Italy (Franciosi et al. , 2005), Bulgaria (Tankova et al. , 2011), and Slovenia ( Š tiglic et al. , 2016).”
Diabetes Risk Score of Adult Applications to Primary Health Care Center: A Cross-Sectional Study
EVCİMEN, H., AYYILDIZ, N. İ., & Doğan, U. (2023) · Van Sağlık Bilimleri Dergisi · doi:10.52976/vansaglik.1162785 · Cited by 2 · see citing works
Baer, R., Zenerato, L. N., Jardine, M., & dos Santos, L. R. (2020) · Revista Eletrônica Acervo Científico · doi:10.25248/reac.e2978.2020 · Cited by 2
Andreeva-Gateva, P., Konsulova, P., Orbetzova, M., Georgieva-Nikolova, R., Tafradjiiska-Hadjiolova, R., Angelova, V., Voynikov, Y., Nikolova, I., & Simova, I. (2016) · Postgraduate medicine · doi:10.1080/00325481.2016.1240590 · Cited by 2 · see citing works
Hyperglycemia screening based on survey data: an international instrument based on WHO STEPs dataset
Moradifar, P., Amini, H., & Amiri, M. (2022) · BMC Endocrine Disorders · doi:10.1186/s12902-022-01222-0 · Cited by 1 · see citing works
“In several studies based on the Finnish Diabetes Risk Score, the sensitivity of the proposed LR models, using various combinations of variables, in the diagnosis of prediabetes was reported in the range 60–84%, whereas their specificity was reported in the range 53–61% [33, 34].”
MethodKondakis, K., Grammatikaki, E., Kondakis, M., Molnár, D., Gómez-Martínez, S., González-Gross, M., Kafatos, A., Manios, Y., Pavón, D. J., Gottrand, F., et al. (2022) · Journal of Pediatric Endocrinology & Metabolism (JPEM) · doi:10.1515/jpem-2022-0265 · Cited by 1 · see citing works
Katoh, S., Peltonen, M., Zeniya, M., Sakamoto, Y., Utsunomiya, K., Nishimura, R., & Tuomilehto, J. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9103161 · Cited by 1 · see citing works
“Third, we did not test other diabetes risk scores [34,35]; we decided to use the FINDRISC because it has been widely used and confirmed in many studies [5,36,37].”
MethodAbdallah, M., Sharbaji, S., Sharbaji, M., Daher, Z., Faour, T., Mansour, Z., & Hneino, M. (2020) · doi:10.21203/rs.3.rs-46875/v1 · Cited by 1
Predicting Risk of Type 2 Diabetes Mellitus: A Population-Based Study
Kılıç, M., Cetinkaya, F., & Kiliç, A. (2016) · The Annals of Clinical and Analytical Medicine · doi:10.4328/jcam.3887 · Cited by 1
Montoya, P. A., Múñoz, Ó., Cardozo, D. M. G., García, O. M., Fernandez-Ávila, D. G., Casas, L. Á., Bohórquez, L. F., Toro, C. M. A., Carvajal, L., de Peña, D. R., et al. (2016) · Colombia medica · doi:10.25100/cm.v47i2.2207 · Cited by 60 · see citing works
Azzouz, M., Yuergui, L., Guerchani, M., Meftah, A., Mimouni, S., & Boudiba, A. (2014) · doi:10.1016/j.ando.2014.07.447 · Cited by 1
A Preliminary Report of Type 2 Diabetes Risk and Related Factors
Büyüksoy, G. D., & Öz, H. (2020) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-020-00567-8
“In several studies, scale scores of women are higher than that of men, and being a woman increases the risk of diabetes [9, 21, 24, 25].”
BackgroundBalogh, D. M., Osgyán, K., Békeffy, M., Kempler, M., Balaton, G., Rizzo, M., Horváth, V., Kempler, P., & Menyhárt, A. (2026) · Medicina · doi:10.3390/medicina62081539
“Importantly, individuals with high FINDRISC scores may exhibit completely normal glucose levels, whereas individuals with prediabetes may have low clinical risk scores [16,17].”
Evaluating the performance of TAG-IT for prediabetes detection in Indonesian population
Jeem, Y., Yuantari, R., Widiatninda, H. A., Andriani, R. N., & Makkiyyah, S. S. (2026) · International Journal of Public Health Science (IJPHS) · doi:10.11591/ijphs.v15i1.26887
Riesgo cardiovascular en pacientes con FINDRISC-C mayor o igual a 12
Santana, K. L. C., Cantillo, H. J. M., Romero, D. F. O., Restrepo, H. K. C., Fernández, E. A. T., & Caballero, H. G. Y. (2023) · Revista Repertorio de Medicina y Cirugía · doi:10.31260/repertmedcir.01217372.1028
Mugume, I. B., Wafula, S. T., Kadengye, D., & van Olmen, J. V. (2021) · Research Square · doi:10.21203/rs.3.rs-414395/v1
Diabetes Risk Profile for an Argeş County Adult Sample – Findrisc Score Characteristics
Roşescu, R., Cînpeanu, O. C., Teodorescu, C., & Tarcea, M. (2020) · Acta Medica Transilvanica · doi:10.2478/amtsb-2020-0040
“In order to assess the risk for diabetes mellitus type 2 the FINDRISC score was calculated, validated and used like variable in many independent cohort studies.(24-30) Our questionnaire consisted of 15 questions and tracked personal data, anthropometric measurements, blood sugar and blood pressure levels, along with a…”
MethodExercise Patterns and Perceptions among South Asian Adults in the United States: The SHAPE Study
Frediani, J., Shaikh, N. I., & Weber, M. (2020) · Translational Journal of the American College of Sports Medicine · doi:10.1249/tjx.0000000000000123
“In-person or phone-based prescreening (n = 117) included a brief screening questionnaire with demographic questions, the Finnish Diabetes Risk Score (FINDRISC) screening tool (10), at in-person assessments, and anthropometric measures.”
MethodA Novel Rule Pruning Ensemble Learning Approach to Recognize the Risk of Impaired Glucose Tolerance
Suganya, K., & Sankari, L. (2017) · IJARCCE · doi:10.17148/ijarcce.2017.6421
“TsvetalinaTankova et al (2011) [8] evaluated the performance of Finnish Diabetes Risk Score (FINDRISC) on screening the impaired fasting glucose (IFG) and impaired glucose tolerance (IGT) and undetected diabetes (UDD) to find the risk level of diabetes.”
Gonçalves, D. J., Garcia, A. D. J., Silva, C. A. D. S., Neta, E. M. D. Q. S., Azevedo, J. J. P., de Jesus, N. C. S., & Fernandes, A. C. (2020) · Enfermagem: Inovação, Tecnologia e Educação em Saúde · doi:10.37885/200901399
- Authors
- Tankova, T., Chakarova, N., Atanassova, I., & Dakovska, L.
- Affiliations
- Medical University of Sofia (BG)
- Corresponding author
- Tankova, Tsvetalina
- Venue
- Diabetes Research and Clinical Practice
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 92
- Issue
- 1
- Pages
- 46-52
- ISSN
- 0168-8227 (ISSN-L)
- OpenAlex
- W2061253431
- Cited by
- 101
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 8 · 2022: 7 · 2021: 7 · 2020: 10 · 2019: 6 · 2018: 10 · 2017: 5 · 2016: 15 · 2015: 9 · 2014: 6 · 2013: 10 · 2012: 3
- FWCI
- 5.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Research and Clinical Practice (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ministry of Education, Youth and Science
- Topics
- 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
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- FINDRISC, diabetes risk score, prediabetes, impaired fasting glucose, impaired glucose tolerance, diabetes screening, risk factor questionnaire, oral glucose tolerance test, screening sensitivity and specificity
- MeSH terms
- Adult, Blood Glucose, Diabetes Mellitus, Fasting, Female, Humans, Male, Middle Aged, Glucose Intolerance
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
