146 related articles for article (PubMed ID: 26559166)
1. Utility of Continuous Metabolic Syndrome Score in Assessing Risk of Type 2 Diabetes: The Isfahan Diabetes Prevention Study.
Janghorbani M; Amini M
Ann Nutr Metab; 2016; 68(1):19-25. PubMed ID: 26559166
[TBL] [Abstract][Full Text] [Related]
2. The product of triglycerides and glucose in comparison with fasting plasma glucose did not improve diabetes prediction.
Janghorbani M; Almasi SZ; Amini M
Acta Diabetol; 2015 Aug; 52(4):781-8. PubMed ID: 25572334
[TBL] [Abstract][Full Text] [Related]
3. Risk of diabetes in combined metabolic abnormalities and body mass index categories.
Janghorbani M; Soltanian N; Sirous M; Amini M; Iraj B
Diabetes Metab Syndr; 2016; 10(1 Suppl 1):S71-8. PubMed ID: 26610402
[TBL] [Abstract][Full Text] [Related]
4. Metabolic syndrome in first degree relatives of patients with type 2 diabetes: Incidence and risk factors.
Janghorbani M; Amini M
Diabetes Metab Syndr; 2011; 5(4):201-6. PubMed ID: 25572763
[TBL] [Abstract][Full Text] [Related]
5. Low-density lipoprotein cholesterol and metabolic syndrome in an Iranian high-risk population.
Janghorbani M; Amini M
Diabetes Metab Syndr; 2015; 9(2):91-7. PubMed ID: 25108602
[TBL] [Abstract][Full Text] [Related]
6. Utility of serum lipid ratios for predicting incident type 2 diabetes: the Isfahan Diabetes Prevention Study.
Janghorbani M; Amini M
Diabetes Metab Res Rev; 2016 Sep; 32(6):572-80. PubMed ID: 26663847
[TBL] [Abstract][Full Text] [Related]
7. Incidence of metabolic syndrome and its risk factors among type 2 diabetes clinic attenders in Isfahan, Iran.
Janghorbani M; Amini M
Endokrynol Pol; 2012; 63(5):372-80. PubMed ID: 23115071
[TBL] [Abstract][Full Text] [Related]
8. Cross-sectional evaluation of the Finnish Diabetes Risk Score: a tool to identify undetected type 2 diabetes, abnormal glucose tolerance and metabolic syndrome.
Saaristo T; Peltonen M; Lindström J; Saarikoski L; Sundvall J; Eriksson JG; Tuomilehto J
Diab Vasc Dis Res; 2005 May; 2(2):67-72. PubMed ID: 16305061
[TBL] [Abstract][Full Text] [Related]
9. Finnish Diabetes Risk Score to predict type 2 diabetes in the Isfahan diabetes prevention study.
Janghorbani M; Adineh H; Amini M
Diabetes Res Clin Pract; 2013 Dec; 102(3):202-9. PubMed ID: 24262944
[TBL] [Abstract][Full Text] [Related]
10. Factor analysis of metabolic syndrome components and predicting type 2 diabetes: Results of 10-year follow-up in a Middle Eastern population.
Ayubi E; Khalili D; Delpisheh A; Hadaegh F; Azizi F
J Diabetes; 2015 Nov; 7(6):830-8. PubMed ID: 25492310
[TBL] [Abstract][Full Text] [Related]
11. Continuous and Dichotomous Metabolic Syndrome Definitions in Youth Predict Adult Type 2 Diabetes and Carotid Artery Intima Media Thickness: The Cardiovascular Risk in Young Finns Study.
Magnussen CG; Cheriyan S; Sabin MA; Juonala M; Koskinen J; Thomson R; Skilton MR; Kähönen M; Laitinen T; Taittonen L; Hutri-Kähönen N; Viikari JS; Raitakari OT
J Pediatr; 2016 Apr; 171():97-103.e1-3. PubMed ID: 26681473
[TBL] [Abstract][Full Text] [Related]
12. Associations of hip circumference and height with incidence of type 2 diabetes: the Isfahan diabetes prevention study.
Janghorbani M; Amini M
Acta Diabetol; 2012 Dec; 49 Suppl 1():S107-14. PubMed ID: 22080142
[TBL] [Abstract][Full Text] [Related]
13. First report on the validity of a continuous Metabolic syndrome score as an indicator for Metabolic syndrome in a national sample of paediatric population - the CASPIAN-III study.
Shafiee G; Kelishadi R; Heshmat R; Qorbani M; Motlagh ME; Aminaee T; Ardalan G; Taslimi M; Poursafa P; Larijani B
Endokrynol Pol; 2013; 64(4):278-84. PubMed ID: 24002955
[TBL] [Abstract][Full Text] [Related]
14. Anthropometric indices predicting incident type 2 diabetes in an Iranian population: the Isfahan Cohort Study.
Talaei M; Sadeghi M; Marshall T; Thomas GN; Iranipour R; Nazarat N; Sarrafzadegan N
Diabetes Metab; 2013 Oct; 39(5):424-31. PubMed ID: 23867722
[TBL] [Abstract][Full Text] [Related]
15. Normal fasting plasma glucose predicts type 2 diabetes and cardiovascular disease in elderly population in Taiwan.
Huang CL; Chang HW; Chang JB; Chen JH; Lin JD; Wu CZ; Pei D; Hung YJ; Lee CH; Chen YL; Hsieh CH
QJM; 2016 Aug; 109(8):515-22. PubMed ID: 26576838
[TBL] [Abstract][Full Text] [Related]
16. Metabolic syndrome vs Framingham Risk Score for prediction of coronary heart disease, stroke, and type 2 diabetes mellitus.
Wannamethee SG; Shaper AG; Lennon L; Morris RW
Arch Intern Med; 2005 Dec 12-26; 165(22):2644-50. PubMed ID: 16344423
[TBL] [Abstract][Full Text] [Related]
17. Low Levels of High-Density Lipoprotein Cholesterol Do Not Predict the Incidence of Type 2 Diabetes in an Iranian High-Risk Population: The Isfahan Diabetes Prevention Study.
Janghorbani M; Amini M; Aminorroaya A
Rev Diabet Stud; 2016; 13(2-3):187-196. PubMed ID: 28012282
[TBL] [Abstract][Full Text] [Related]
18. Prognostic impact of different definitions of metabolic syndrome in predicting cardiovascular events in a cohort of non-diabetic Tehranian adults.
Hosseinpanah F; Asghari G; Barzin M; Golkashani HA; Azizi F
Int J Cardiol; 2013 Sep; 168(1):369-74. PubMed ID: 23041003
[TBL] [Abstract][Full Text] [Related]
19. Continuous Metabolic Syndrome Scores for Children Using Salivary Biomarkers.
Shi P; Goodson JM; Hartman ML; Hasturk H; Yaskell T; Vargas J; Cugini M; Barake R; Alsmadi O; Al-Mutawa S; Ariga J; Soparkar P; Behbehani J; Behbehani K; Welty F
PLoS One; 2015; 10(9):e0138979. PubMed ID: 26418011
[TBL] [Abstract][Full Text] [Related]
20. The metabolic syndrome as a tool for predicting future diabetes: the AusDiab study.
Cameron AJ; Magliano DJ; Zimmet PZ; Welborn TA; Colagiuri S; Tonkin AM; Shaw JE
J Intern Med; 2008 Aug; 264(2):177-86. PubMed ID: 18298479
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]