D
Diederick E. Grobbee
Researcher at Utrecht University
Publications - 1108
Citations - 136069
Diederick E. Grobbee is an academic researcher from Utrecht University. The author has contributed to research in topics: Population & Risk factor. The author has an hindex of 155, co-authored 1051 publications receiving 122748 citations. Previous affiliations of Diederick E. Grobbee include National Heart Foundation of Australia & Radboud University Nijmegen Medical Centre.
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Journal ArticleDOI
Prevalence of incidental findings in computed tomographic screening of the chest: a systematic review.
TL;DR: In this review, 7.7% and 14.2% of patients undergoing either CAD or lung cancer screening with CT were found to have clinically significant incidental findings requiring additional investigations.
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Contemporary model for cardiovascular risk prediction in people with type 2 diabetes
Andre Pascal Kengne,Anushka Patel,Michel Marre,F. Travert,Michel Lievre,Sophia Zoungas,John Chalmers,Stephen Colagiuri,Diederick E. Grobbee,Pavel Hamet,Simon Heller,Bruce Neal,Mark Woodward +12 more
TL;DR: Major cardiovascular events in contemporary populations with type 2 diabetes can be predicted on the basis of routinely measured clinical and biological variables and can be used to quantify risk and guide the intensity of treatment in people with diabetes.
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Prevalence of Stroke in the General Population The Rotterdam Study
Michiel L. Bots,Sophia J. Looman,Peter J. Koudstaal,Albert Hofman,A. W. Hoes,Diederick E. Grobbee +5 more
TL;DR: The present study provides valid age- and sex-specific estimates of prevalence of stroke and the degree to which the event had led to hospitalization and a substantial proportion of patients with stroke is not hospitalized.
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Variability in clinical phenotype of severe haemophilia: the role of the first joint bleed.
TL;DR: The onset of joint bleeding is inversely related with treatment requirement and arthropathy and may serve as an indicator of clinical phenotype, providing a starting point for aetiological research and individualization of treatment.
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Dealing with Missing Predictor Values When Applying Clinical Prediction Models
Kristel J.M. Janssen,Yvonne Vergouwe,A. Rogier T. Donders,Frank E. Harrell,Qingxia Chen,Diederick E. Grobbee,Karel G.M. Moons +6 more
TL;DR: A prediction model to predict the risk of deep venous thrombosis and the effect of the strategies on the slope differed between the 3 scenarios, suggesting multiple imputation is preferred if a predictor value is missing.