Algorithms for the capture and adjudication of prevalent and incident diabetes in UK Biobank

PLoS ONE

Volumn 11, Issue 9, 2016, Pages

  Eastwood, Sophie V ^a   Mathur, Rohini ^b   Atkinson, Mark ^c   Brophy, Sinead ^c   Sudlow, Cathie ^d,g   Flaig, Robin ^d,g   De Lusignan, Simon ^e   Allen, Naomi ^f,g   Chaturvedi, Nishi ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

^c SWANSEA UNIVERSITY   (United Kingdom)

^d UNIVERSITY OF EDINBURGH   (United Kingdom)

^e UNIVERSITY OF SURREY   (United Kingdom)

^f UNIVERSITY OF OXFORD   (United Kingdom)

^g United Kingdom   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ALGORITHM; ARTICLE; BIOBANK; BLOOD ANALYSIS; DISEASE CLASSIFICATION; DRUG USE; FEMALE; HUMAN; ICD-10; INCIDENCE; MAJOR CLINICAL STUDY; MALE; MEDICAL HISTORY; NON INSULIN DEPENDENT DIABETES MELLITUS; PREVALENCE; PRIMARY MEDICAL CARE; SECONDARY HEALTH CARE; SELF REPORT; UNITED KINGDOM; DIABETES MELLITUS, TYPE 2; MIDDLE AGED;

AGED; ALGORITHMS; BIOLOGICAL SPECIMEN BANKS; DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; INCIDENCE; MALE; MIDDLE AGED; PREVALENCE; UNITED KINGDOM;

EID: 84992416977     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0162388     Document Type: Article

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