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Items: 1 to 20 of 55

1.

Diabetes risk assessment among squatter settlements in Pakistan: A cross-sectional study.

Ishaque A, Shahzad F, Muhammad FH, Usman Y, Ishaque Z.

Malays Fam Physician. 2016 Aug 31;11(2-3):9-15. eCollection 2016.

2.

Predicting glycated hemoglobin levels in the non-diabetic general population: Development and validation of the DIRECT-DETECT prediction model - a DIRECT study.

Rauh SP, Heymans MW, Koopman AD, Nijpels G, Stehouwer CD, Thorand B, Rathmann W, Meisinger C, Peters A, de Las Heras Gala T, Glümer C, Pedersen O, Cederberg H, Kuusisto J, Laakso M, Pearson ER, Franks PW, Rutters F, Dekker JM.

PLoS One. 2017 Feb 10;12(2):e0171816. doi: 10.1371/journal.pone.0171816. eCollection 2017.

3.

Perceived risk of diabetes seriously underestimates actual diabetes risk: The KORA FF4 study.

Kowall B, Rathmann W, Stang A, Bongaerts B, Kuss O, Herder C, Roden M, Quante A, Holle R, Huth C, Peters A, Meisinger C.

PLoS One. 2017 Jan 31;12(1):e0171152. doi: 10.1371/journal.pone.0171152. eCollection 2017.

4.

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing-Based Algorithm With Statewide Electronic Medical Records.

Zheng L, Wang Y, Hao S, Shin AY, Jin B, Ngo AD, Jackson-Browne MS, Feller DJ, Fu T, Zhang K, Zhou X, Zhu C, Dai D, Yu Y, Zheng G, Li YM, McElhinney DB, Culver DS, Alfreds ST, Stearns F, Sylvester KG, Widen E, Ling XB.

JMIR Med Inform. 2016 Nov 11;4(4):e37.

5.

Impact of statistical models on the prediction of type 2 diabetes using non-targeted metabolomics profiling.

Yengo L, Arredouani A, Marre M, Roussel R, Vaxillaire M, Falchi M, Haoudi A, Tichet J; D.E.S.I.R Study Group, Balkau B, Bonnefond A, Froguel P.

Mol Metab. 2016 Aug 23;5(10):918-25. doi: 10.1016/j.molmet.2016.08.011. eCollection 2016 Oct.

6.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study.

Pollock BD, Hu T, Chen W, Harville EW, Li S, Webber LS, Fonseca V, Bazzano LA.

J Diabetes Complications. 2017 Jan;31(1):86-93. doi: 10.1016/j.jdiacomp.2016.07.025. Epub 2016 Jul 27.

PMID:
27503406
7.

Risk scores for predicting incidence of type 2 diabetes in the Chinese population: the Kailuan prospective study.

Wang A, Chen G, Su Z, Liu X, Liu X, Li H, Luo Y, Tao L, Guo J, Liu L, Chen S, Wu S, Guo X.

Sci Rep. 2016 May 25;6:26548. doi: 10.1038/srep26548.

8.

Evaluation of Non-Laboratory and Laboratory Prediction Models for Current and Future Diabetes Mellitus: A Cross-Sectional and Retrospective Cohort Study.

Ahn CH, Yoon JW, Hahn S, Moon MK, Park KS, Cho YM.

PLoS One. 2016 May 23;11(5):e0156155. doi: 10.1371/journal.pone.0156155. eCollection 2016.

9.

Plasma Copeptin, AVP Gene Variants, and Incidence of Type 2 Diabetes in a Cohort From the Community.

Roussel R, El Boustany R, Bouby N, Potier L, Fumeron F, Mohammedi K, Balkau B, Tichet J, Bankir L, Marre M, Velho G.

J Clin Endocrinol Metab. 2016 Jun;101(6):2432-9. doi: 10.1210/jc.2016-1113. Epub 2016 Apr 6.

10.

Development and Validation of HealthImpact: An Incident Diabetes Prediction Model Based on Administrative Data.

McCoy RG, Nori VS, Smith SA, Hane CA.

Health Serv Res. 2016 Oct;51(5):1896-918. doi: 10.1111/1475-6773.12461. Epub 2016 Feb 21.

PMID:
26898782
11.

Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives.

Müller B, Wilcke A, Boulesteix AL, Brauer J, Passarge E, Boltze J, Kirsten H.

Hum Genet. 2016 Mar;135(3):259-72. doi: 10.1007/s00439-016-1636-z. Epub 2016 Feb 2. Review.

12.

Adapting existing diabetes risk scores for an Asian population: a risk score for detecting undiagnosed diabetes in the Mongolian population.

Dugee O, Janchiv O, Jousilahti P, Sakhiya A, Palam E, Nuorti JP, Peltonen M.

BMC Public Health. 2015 Sep 22;15:938. doi: 10.1186/s12889-015-2298-9.

13.

Validating prediction scales of type 2 diabetes mellitus in Spain: the SPREDIA-2 population-based prospective cohort study protocol.

Salinero-Fort MÁ, de Burgos-Lunar C, Mostaza Prieto J, Lahoz Rallo C, Abánades-Herranz JC, Gómez-Campelo P, Laguna Cuesta F, Estirado De Cabo E, García Iglesias F, González Alegre T, Fernández Puntero B, Montesano Sánchez L, Vicent López D, Cornejo Del Río V, Fernández García PJ, Sabín Rodríguez C, López López S, Patrón Barandío P; SPREDIA-2 Group.

BMJ Open. 2015 Jul 28;5(7):e007195. doi: 10.1136/bmjopen-2014-007195.

14.

Circulating peroxiredoxin 4 and type 2 diabetes risk: the Prevention of Renal and Vascular Endstage Disease (PREVEND) study.

Abbasi A, Corpeleijn E, Gansevoort RT, Gans RO, Struck J, Schulte J, Hillege HL, van der Harst P, Stolk RP, Navis G, Bakker SJ.

Diabetologia. 2014 Sep;57(9):1842-9. doi: 10.1007/s00125-014-3278-9. Epub 2014 Jun 4.

15.

Dietary isoflavone intake is associated with evoked responses to inflammatory cardiometabolic stimuli and improved glucose homeostasis in healthy volunteers.

Ferguson JF, Ryan MF, Gibney ER, Brennan L, Roche HM, Reilly MP.

Nutr Metab Cardiovasc Dis. 2014 Sep;24(9):996-1003. doi: 10.1016/j.numecd.2014.03.010. Epub 2014 Apr 18.

16.

Evaluation of Finnish Diabetes Risk Score in screening undiagnosed diabetes and prediabetes among U.S. adults by gender and race: NHANES 1999-2010.

Zhang L, Zhang Z, Zhang Y, Hu G, Chen L.

PLoS One. 2014 May 22;9(5):e97865. doi: 10.1371/journal.pone.0097865. eCollection 2014.

17.

Comparison of diabetes risk score estimates and cardiometabolic risk profiles in a middle-aged Irish population.

Phillips CM, Kearney PM, McCarthy VJ, Harrington JM, Fitzgerald AP, Perry IJ.

PLoS One. 2013 Nov 13;8(11):e78950. doi: 10.1371/journal.pone.0078950. eCollection 2013.

18.

Over time, do anthropometric measures still predict diabetes incidence in chinese han nationality population from chengdu community?

Liu K, He S, Hong B, Yang R, Zhou X, Feng J, Wang S, Chen X.

Int J Endocrinol. 2013;2013:239376. doi: 10.1155/2013/239376. Epub 2013 Oct 12.

19.

Nonlaboratory-based risk assessment algorithm for undiagnosed type 2 diabetes developed on a nation-wide diabetes survey.

Zhou X, Qiao Q, Ji L, Ning F, Yang W, Weng J, Shan Z, Tian H, Ji Q, Lin L, Li Q, Xiao J, Gao W, Pang Z, Sun J.

Diabetes Care. 2013 Dec;36(12):3944-52. doi: 10.2337/dc13-0593. Epub 2013 Oct 21.

20.

Elevated HbA1c and fasting plasma glucose in predicting diabetes incidence among older adults: are two better than one?

Lipska KJ, Inzucchi SE, Van Ness PH, Gill TM, Kanaya A, Strotmeyer ES, Koster A, Johnson KC, Goodpaster BH, Harris T, De Rekeneire N; Health ABC Study.

Diabetes Care. 2013 Dec;36(12):3923-9. doi: 10.2337/dc12-2631. Epub 2013 Oct 17.

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