Literature DB >> 24668104

Glycated hemoglobin measurement and prediction of cardiovascular disease.

Emanuele Di Angelantonio1, Pei Gao1, Hassan Khan1, Adam S Butterworth1, David Wormser1, Stephen Kaptoge1, Sreenivasa Rao Kondapally Seshasai2, Alex Thompson1, Nadeem Sarwar1, Peter Willeit1, Paul M Ridker3, Elizabeth L M Barr4, Kay-Tee Khaw1, Bruce M Psaty5, Hermann Brenner6, Beverley Balkau7, Jacqueline M Dekker8, Debbie A Lawlor9, Makoto Daimon10, Johann Willeit11, Inger Njølstad12, Aulikki Nissinen13, Eric J Brunner14, Lewis H Kuller15, Jackie F Price16, Johan Sundström17, Matthew W Knuiman18, Edith J M Feskens19, W M M Verschuren20, Nicholas Wald21, Stephan J L Bakker22, Peter H Whincup2, Ian Ford23, Uri Goldbourt24, Agustín Gómez-de-la-Cámara25, John Gallacher26, Leon A Simons27, Annika Rosengren28, Susan E Sutherland29, Cecilia Björkelund30, Dan G Blazer31, Sylvia Wassertheil-Smoller32, Altan Onat33, Alejandro Marín Ibañez34, Edoardo Casiglia35, J Wouter Jukema36, Lara M Simpson37, Simona Giampaoli38, Børge G Nordestgaard39, Randi Selmer40, Patrik Wennberg41, Jussi Kauhanen42, Jukka T Salonen43, Rachel Dankner44, Elizabeth Barrett-Connor45, Maryam Kavousi46, Vilmundur Gudnason47, Denis Evans48, Robert B Wallace49, Mary Cushman50, Ralph B D'Agostino51, Jason G Umans52, Yutaka Kiyohara53, Hidaeki Nakagawa54, Shinichi Sato55, Richard F Gillum56, Aaron R Folsom57, Yvonne T van der Schouw58, Karel G Moons58, Simon J Griffin1, Naveed Sattar23, Nicholas J Wareham1, Elizabeth Selvin59, Simon G Thompson1, John Danesh1.   

Abstract

IMPORTANCE: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain.
OBJECTIVE: To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. DESIGN, SETTING, AND PARTICIPANTS: Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. MAIN OUTCOMES AND MEASURES: Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥ 7.5%) risk.
RESULTS: During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. CONCLUSIONS AND RELEVANCE: In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.

Entities:  

Mesh:

Substances:

Year:  2014        PMID: 24668104      PMCID: PMC4386007          DOI: 10.1001/jama.2014.1873

Source DB:  PubMed          Journal:  JAMA        ISSN: 0098-7484            Impact factor:   56.272


  27 in total

1.  Quantifying heterogeneity in a meta-analysis.

Authors:  Julian P T Higgins; Simon G Thompson
Journal:  Stat Med       Date:  2002-06-15       Impact factor: 2.373

2.  2010 ACCF/AHA guideline for assessment of cardiovascular risk in asymptomatic adults: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines.

Authors:  Philip Greenland; Joseph S Alpert; George A Beller; Emelia J Benjamin; Matthew J Budoff; Zahi A Fayad; Elyse Foster; Mark A Hlatky; John McB Hodgson; Frederick G Kushner; Michael S Lauer; Leslee J Shaw; Sidney C Smith; Allen J Taylor; William S Weintraub; Nanette K Wenger; Alice K Jacobs; Sidney C Smith; Jeffrey L Anderson; Nancy Albert; Christopher E Buller; Mark A Creager; Steven M Ettinger; Robert A Guyton; Jonathan L Halperin; Judith S Hochman; Frederick G Kushner; Rick Nishimura; E Magnus Ohman; Richard L Page; William G Stevenson; Lynn G Tarkington; Clyde W Yancy
Journal:  J Am Coll Cardiol       Date:  2010-12-14       Impact factor: 24.094

3.  Floating absolute risk: an alternative to relative risk in survival and case-control analysis avoiding an arbitrary reference group.

Authors:  D F Easton; J Peto; A G Babiker
Journal:  Stat Med       Date:  1991-07       Impact factor: 2.373

4.  Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults.

Authors:  Elizabeth Selvin; Michael W Steffes; Hong Zhu; Kunihiro Matsushita; Lynne Wagenknecht; James Pankow; Josef Coresh; Frederick L Brancati
Journal:  N Engl J Med       Date:  2010-03-04       Impact factor: 91.245

5.  Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies.

Authors:  N Sarwar; P Gao; S R Kondapally Seshasai; R Gobin; S Kaptoge; E Di Angelantonio; E Ingelsson; D A Lawlor; E Selvin; M Stampfer; C D A Stehouwer; S Lewington; L Pennells; A Thompson; N Sattar; I R White; K K Ray; J Danesh
Journal:  Lancet       Date:  2010-06-26       Impact factor: 202.731

6.  Continuous relationships between non-diabetic hyperglycaemia and both cardiovascular disease and all-cause mortality: the Australian Diabetes, Obesity, and Lifestyle (AusDiab) study.

Authors:  E L M Barr; E J Boyko; P Z Zimmet; R Wolfe; A M Tonkin; J E Shaw
Journal:  Diabetologia       Date:  2009-01-08       Impact factor: 10.122

7.  Using nontraditional risk factors in coronary heart disease risk assessment: U.S. Preventive Services Task Force recommendation statement.

Authors: 
Journal:  Ann Intern Med       Date:  2009-10-06       Impact factor: 25.391

8.  Statistical methods for the time-to-event analysis of individual participant data from multiple epidemiological studies.

Authors:  Simon Thompson; Stephen Kaptoge; Ian White; Angela Wood; Philip Perry; John Danesh
Journal:  Int J Epidemiol       Date:  2010-05-03       Impact factor: 7.196

9.  Lipid-related markers and cardiovascular disease prediction.

Authors:  Emanuele Di Angelantonio; Pei Gao; Lisa Pennells; Stephen Kaptoge; Muriel Caslake; Alexander Thompson; Adam S Butterworth; Nadeem Sarwar; David Wormser; Danish Saleheen; Christie M Ballantyne; Bruce M Psaty; Johan Sundström; Paul M Ridker; Dorothea Nagel; Richard F Gillum; Ian Ford; Pierre Ducimetiere; Stefan Kiechl; Wolfgang Koenig; Robin P F Dullaart; Gerd Assmann; Ralph B D'Agostino; Gilles R Dagenais; Jackie A Cooper; Daan Kromhout; Altan Onat; Robert W Tipping; Agustín Gómez-de-la-Cámara; Annika Rosengren; Susan E Sutherland; John Gallacher; F Gerry R Fowkes; Edoardo Casiglia; Albert Hofman; Veikko Salomaa; Elizabeth Barrett-Connor; Robert Clarke; Eric Brunner; J Wouter Jukema; Leon A Simons; Manjinder Sandhu; Nicholas J Wareham; Kay-Tee Khaw; Jussi Kauhanen; Jukka T Salonen; William J Howard; Børge G Nordestgaard; Angela M Wood; Simon G Thompson; S Matthijs Boekholdt; Naveed Sattar; Chris Packard; Vilmundur Gudnason; John Danesh
Journal:  JAMA       Date:  2012-06-20       Impact factor: 56.272

10.  The Emerging Risk Factors Collaboration: analysis of individual data on lipid, inflammatory and other markers in over 1.1 million participants in 104 prospective studies of cardiovascular diseases.

Authors:  J Danesh; S Erqou; M Walker; S G Thompson; R Tipping; C Ford; S Pressel; G Walldius; I Jungner; A R Folsom; L E Chambless; M Knuiman; P H Whincup; S G Wannamethee; R W Morris; J Willeit; S Kiechl; P Santer; A Mayr; N Wald; S Ebrahim; D A Lawlor; J W G Yarnell; J Gallacher; E Casiglia; V Tikhonoff; P J Nietert; S E Sutherland; D L Bachman; J E Keil; M Cushman; B M Psaty; R P Tracy; A Tybjaerg-Hansen; B G Nordestgaard; R Frikke-Schmidt; S Giampaoli; L Palmieri; S Panico; D Vanuzzo; L Pilotto; L Simons; J McCallum; Y Friedlander; F G R Fowkes; A J Lee; F B Smith; J Taylor; J Guralnik; C Phillips; R Wallace; D Blazer; K T Khaw; J H Jansson; C Donfrancesco; V Salomaa; K Harald; P Jousilahti; E Vartiainen; M Woodward; R B D'Agostino; P A Wolf; R S Vasan; M J Pencina; E M Bladbjerg; T Jorgensen; L Moller; J Jespersen; R Dankner; A Chetrit; F Lubin; A Rosengren; L Wilhelmsen; G Lappas; H Eriksson; C Bjorkelund; P Cremer; D Nagel; R Tilvis; T Strandberg; B Rodriguez; L M Bouter; R J Heine; J M Dekker; G Nijpels; C D A Stehouwer; E Rimm; J Pai; S Sato; H Iso; A Kitamura; H Noda; U Goldbourt; V Salomaa; J T Salonen; K Nyyssönen; T-P Tuomainen; D Deeg; J L Poppelaars; T Meade; J Cooper; B Hedblad; G Berglund; G Engstrom; A Döring; W Koenig; C Meisinger; W Mraz; L Kuller; R Selmer; A Tverdal; W Nystad; R Gillum; M Mussolino; S Hankinson; J Manson; B De Stavola; C Knottenbelt; J A Cooper; K A Bauer; R D Rosenberg; S Sato; Y Naito; I Holme; H Nakagawa; H Miura; P Ducimetiere; X Jouven; C Crespo; M Garcia-Palmieri; P Amouyel; D Arveiler; A Evans; J Ferrieres; H Schulte; G Assmann; J Shepherd; C Packard; N Sattar; B Cantin; B Lamarche; J-P Després; G R Dagenais; E Barrett-Connor; D Wingard; R Bettencourt; V Gudnason; T Aspelund; G Sigurdsson; B Thorsson; M Trevisan; J Witteman; I Kardys; M Breteler; A Hofman; H Tunstall-Pedoe; R Tavendale; G D O Lowe; Y Ben-Shlomo; B V Howard; Y Zhang; L Best; J Umans; A Onat; T W Meade; I Njolstad; E Mathiesen; M L Lochen; T Wilsgaard; J M Gaziano; M Stampfer; P Ridker; H Ulmer; G Diem; H Concin; F Rodeghiero; A Tosetto; E Brunner; M Shipley; J Buring; S M Cobbe; I Ford; M Robertson; Y He; A M Ibanez; E J M Feskens; D Kromhout; R Collins; E Di Angelantonio; S Kaptoge; S Lewington; L Orfei; L Pennells; P Perry; K Ray; N Sarwar; M Scherman; A Thompson; S Watson; F Wensley; I R White; A M Wood
Journal:  Eur J Epidemiol       Date:  2007-09-18       Impact factor: 8.082

View more
  72 in total

1.  Relations of Postload and Fasting Glucose With Incident Cardiovascular Disease and Mortality Late in Life: The Cardiovascular Health Study.

Authors:  Erika F Brutsaert; Sanyog Shitole; Mary Lou Biggs; Kenneth J Mukamal; Ian H deBoer; Evan L Thacker; Joshua I Barzilay; Luc Djoussé; Joachim H Ix; Nicholas L Smith; Robert C Kaplan; David S Siscovick; Bruce M Psaty; Jorge R Kizer
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2015-08-27       Impact factor: 6.053

2.  Risk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study.

Authors:  C M Parrinello; K Matsushita; M Woodward; L E Wagenknecht; J Coresh; E Selvin
Journal:  Diabetes Obes Metab       Date:  2016-06-14       Impact factor: 6.577

3.  Inverse association between fasting plasma glucose and risk of ventricular arrhythmias.

Authors:  Francesco Zaccardi; David R Webb; Sudhir Kurl; Kamlesh Khunti; Melanie J Davies; Jari A Laukkanen
Journal:  Diabetologia       Date:  2015-06-03       Impact factor: 10.122

Review 4.  Novel metabolic biomarkers of cardiovascular disease.

Authors:  Majken K Jensen; Monica L Bertoia; Leah E Cahill; Isha Agarwal; Eric B Rimm; Kenneth J Mukamal
Journal:  Nat Rev Endocrinol       Date:  2014-09-02       Impact factor: 43.330

5.  Association of a Biomarker of Glucose Peaks, 1,5-Anhydroglucitol, With Subclinical Cardiovascular Disease.

Authors:  Menglu Liang; John William McEvoy; Yuan Chen; A Richey Sharrett; Elizabeth Selvin
Journal:  Diabetes Care       Date:  2016-08-01       Impact factor: 19.112

6.  Serum albumin concentration and incident type 2 diabetes risk: new findings from a population-based cohort study.

Authors:  Setor K Kunutsor; Hassan Khan; Jari A Laukkanen
Journal:  Diabetologia       Date:  2015-02-14       Impact factor: 10.122

Review 7.  Utility of different glycemic control metrics for optimizing management of diabetes.

Authors:  Klaus-Dieter Kohnert; Peter Heinke; Lutz Vogt; Eckhard Salzsieder
Journal:  World J Diabetes       Date:  2015-02-15

Review 8.  New and emerging biomarkers in cardiovascular disease.

Authors:  Leah E Cahill; Monica L Bertoia; Sarah A Aroner; Kenneth J Mukamal; Majken K Jensen
Journal:  Curr Diab Rep       Date:  2015-11       Impact factor: 4.810

9.  Impact of Diabetes Mellitus on Stroke and Survival in Patients With Atrial Fibrillation.

Authors:  Sri Harsha Patlolla; Hon-Chi Lee; Peter A Noseworthy; Waldemar E Wysokinski; David O Hodge; Eddie L Greene; Bernard J Gersh; Rowlens M Melduni
Journal:  Am J Cardiol       Date:  2020-06-30       Impact factor: 2.778

10.  Are There Clinical Implications of Racial Differences in HbA1c? A Difference, to Be a Difference, Must Make a Difference.

Authors:  Elizabeth Selvin
Journal:  Diabetes Care       Date:  2016-08       Impact factor: 19.112

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.