Literature DB >> 21340624

HbA1c and cardiovascular risk score identify people who may benefit from preventive interventions: a 7 year follow-up of a high-risk screening programme for diabetes in primary care (ADDITION), Denmark.

T Lauritzen1, A Sandbaek, M V Skriver, K Borch-Johnsen.   

Abstract

AIMS/HYPOTHESIS: The measurement of HbA(1c) is suggested as a diagnostic test for diabetes. Screening for diabetes also identifies individuals with elevated cardiovascular risk but who are free of diabetes. This study aims to assess whether screening by HbA(1c) or glucose measures alone, or in combination with a cardiovascular risk assessment, identifies people who may benefit from preventive interventions, i.e. people with screen detected diabetes and people belonging to groups with excess mortality, during a median follow-up of 7 years.
METHODS: A population-based, stepwise high-risk screening programme was performed in 193 family practices from 2001 to 2006. Individuals aged between 40 and 69 years (N = 163,185) were sent a diabetes risk questionnaire. Of these, 20,916 people at risk of diabetes were stratified by glucose measures (normal glucose tolerance [NGT], impaired fasting glucose [IFG], impaired glucose tolerance [IGT] and diabetes), HbA(1c) (<6%; 6.0-6.4%; or ≥ 6.5%) and cardiovascular risk (heart SCORE <5 or ≥ 5). People were followed for a median of 7 years or until death. Excess mortality was calculated using the Cox hazard ratio (HR).
RESULTS: SCORE ≥ 5 identified 91.7% (95% CI 91.1-92.3%) of those who might benefit from preventive interventions. SCORE ≥ 5 in combination with HbA(1c) ≥ 6.0% identified 96.7% (95% CI 96.3-97.0%), compared with 97.6% (95%CI 97.2-97.9%) in combination with glucose measures. Glucose measures or HbA(1c) alone identified 26.1% (95% CI 25.2-27.0%) and 19.8% (95% CI 19.0-20.6%), respectively. CONCLUSION/
INTERPRETATION: In a population-based high risk screening programme in primary care, HbA(1c) ≥ 6.0% combined with an elevated cardiovascular risk assessment (SCORE ≥ 5) can feasibly be used to identify those who may benefit from preventive lifestyle intervention and/or polypharmacy. TRIAL REGISTRATION: ClinicalTrials.gov NCT 00237549. FUNDING: The study received unrestricted grants from Novo Nordisk, Novo Nordisk Scandinavia, Astra Denmark, Pfizer Denmark, GlaxoSmithKline Pharma Denmark, Servier Denmark and HemoCue Denmark.

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Year:  2011        PMID: 21340624     DOI: 10.1007/s00125-011-2077-9

Source DB:  PubMed          Journal:  Diabetologia        ISSN: 0012-186X            Impact factor:   10.122


  22 in total

1.  Population-based stepwise screening for unrecognised Type 2 diabetes is ineffective in general practice despite reliable algorithms.

Authors:  J O Christensen; A Sandbaek; T Lauritzen; K Borch-Johnsen
Journal:  Diabetologia       Date:  2004-09-08       Impact factor: 10.122

2.  Age at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis.

Authors:  Richard Kahn; Peter Alperin; David Eddy; Knut Borch-Johnsen; John Buse; Justin Feigelman; Edward Gregg; Rury R Holman; M Sue Kirkman; Michael Stern; Jaakko Tuomilehto; Nick J Wareham
Journal:  Lancet       Date:  2010-03-29       Impact factor: 79.321

3.  Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections.

Authors:  H King; R E Aubert; W H Herman
Journal:  Diabetes Care       Date:  1998-09       Impact factor: 19.112

4.  General practitioners' adherence to guidelines on management of dyslipidaemia: ADDITION-Denmark.

Authors:  Lise Graversen; Bo Christensen; Knut Borch-Johnsen; Torsten Lauritzen; Annelli Sandbaek
Journal:  Scand J Prim Health Care       Date:  2010-03       Impact factor: 2.581

5.  Prevalences of diabetes and impaired glucose regulation in a Danish population: the Inter99 study.

Authors:  Charlotte Glümer; Torben Jørgensen; Knut Borch-Johnsen
Journal:  Diabetes Care       Date:  2003-08       Impact factor: 19.112

6.  Diabetic patients detected by population-based stepwise screening already have a diabetic cardiovascular risk profile.

Authors:  Annemieke M W Spijkerman; Marcel C Adriaanse; Jacqueline M Dekker; Giel Nijpels; Coen D A Stehouwer; Lex M Bouter; Robert J Heine
Journal:  Diabetes Care       Date:  2002-10       Impact factor: 19.112

7.  The impact of prevention on reducing the burden of cardiovascular disease.

Authors:  Richard Kahn; Rose Marie Robertson; Robert Smith; David Eddy
Journal:  Circulation       Date:  2008-07-07       Impact factor: 29.690

8.  Effect of a multifactorial intervention on mortality in type 2 diabetes.

Authors:  Peter Gaede; Henrik Lund-Andersen; Hans-Henrik Parving; Oluf Pedersen
Journal:  N Engl J Med       Date:  2008-02-07       Impact factor: 91.245

9.  What determines the cost-effectiveness of diabetes screening?

Authors:  C Glümer; M Yuyun; S Griffin; D Farewell; D Spiegelhalter; A L Kinmonth; N J Wareham
Journal:  Diabetologia       Date:  2006-04-26       Impact factor: 10.122

10.  Stepwise screening for diabetes identifies people with high but modifiable coronary heart disease risk. The ADDITION study.

Authors:  A Sandbaek; S J Griffin; G Rutten; M Davies; R Stolk; K Khunti; K Borch-Johnsen; N J Wareham; T Lauritzen
Journal:  Diabetologia       Date:  2008-04-29       Impact factor: 10.122

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  11 in total

Review 1.  The worldwide epidemiology of type 2 diabetes mellitus--present and future perspectives.

Authors:  Lei Chen; Dianna J Magliano; Paul Z Zimmet
Journal:  Nat Rev Endocrinol       Date:  2011-11-08       Impact factor: 43.330

2.  Prognostic value of haemoglobin A1c and fasting plasma glucose for incident diabetes and implications for screening.

Authors:  Ben Schöttker; Elke Raum; Dietrich Rothenbacher; Heiko Müller; Hermann Brenner
Journal:  Eur J Epidemiol       Date:  2011-09-27       Impact factor: 8.082

3.  Fasting plasma glucose and HbA1c in cardiovascular risk prediction: a sex-specific comparison in individuals without diabetes mellitus.

Authors:  B Schöttker; H Müller; D Rothenbacher; H Brenner
Journal:  Diabetologia       Date:  2012-09-19       Impact factor: 10.122

4.  Making Inroads in Addressing Population Health in Underserved Communities With Type 2 Diabetes.

Authors:  Luigi F Meneghini; Addie L Fortmann; Taylor L Clark; Kellie Rodriguez
Journal:  Diabetes Spectr       Date:  2019-11

5.  Screening for type 2 diabetes mellitus.

Authors:  Nasheeta Peer; Yusentha Balakrishna; Solange Durao
Journal:  Cochrane Database Syst Rev       Date:  2020-05-29

6.  Risk of dementia and cognitive dysfunction in individuals with diabetes or elevated blood glucose.

Authors:  I K Wium-Andersen; J Rungby; M B Jørgensen; A Sandbæk; M Osler; M K Wium-Andersen
Journal:  Epidemiol Psychiatr Sci       Date:  2019-08-28       Impact factor: 6.892

7.  Protocol for ADDITION-PRO: a longitudinal cohort study of the cardiovascular experience of individuals at high risk for diabetes recruited from Danish primary care.

Authors:  Nanna B Johansen; Anne-Louise S Hansen; Troels M Jensen; Annelotte Philipsen; Signe S Rasmussen; Marit E Jørgensen; Rebecca K Simmons; Torsten Lauritzen; Annelli Sandbæk; Daniel R Witte
Journal:  BMC Public Health       Date:  2012-12-14       Impact factor: 3.295

8.  HbA₁c versus oral glucose tolerance test as a method to diagnose diabetes mellitus in vascular surgery patients.

Authors:  Iren D Hjellestad; Marianne C Astor; Roy M Nilsen; Eirik Søfteland; Torbjørn Jonung
Journal:  Cardiovasc Diabetol       Date:  2013-05-25       Impact factor: 9.951

9.  Stratified patient-centered care in type 2 diabetes: a cluster-randomized, controlled clinical trial of effectiveness and cost-effectiveness.

Authors:  Annabelle S Slingerland; William H Herman; William K Redekop; Rob F Dijkstra; J Wouter Jukema; Louis W Niessen
Journal:  Diabetes Care       Date:  2013-08-15       Impact factor: 19.112

Review 10.  HbA1c for diagnosis of type 2 diabetes. Is there an optimal cut point to assess high risk of diabetes complications, and how well does the 6.5% cutoff perform?

Authors:  Bernd Kowall; Wolfgang Rathmann
Journal:  Diabetes Metab Syndr Obes       Date:  2013-11-29       Impact factor: 3.168

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