Pulse lineResearch With Heart Logo

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

TitleRisk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study.
Publication TypeJournal Article
Year of Publication2016
AuthorsParrinello CM, Matsushita K, Woodward M, Wagenknecht LE, Coresh JJ
Secondary AuthorsSelvin E
JournalDiabetes Obes Metab
Volume18
Issue9
Pagination899-906
Date Published2016 09
ISSN1463-1326
KeywordsAged, Alanine Transaminase, Aspartate Aminotransferases, beta 2-Microglobulin, Biomarkers, C-Reactive Protein, Cohort Studies, Coronary Disease, Creatinine, Cystatin C, Diabetes Complications, Diabetes Mellitus, Diabetic Angiopathies, Diabetic Nephropathies, Female, Fructosamine, gamma-Glutamyltransferase, Glomerular Filtration Rate, Glycated Hemoglobin A, Heart Failure, Hospitalization, Humans, Male, Middle Aged, Natriuretic Peptide, Brain, Peptide Fragments, Prospective Studies, Renal Insufficiency, Chronic, Risk Assessment, Self Report, Serum Albumin, Stroke, Troponin T
Abstract

AIMS: To develop a prediction equation for 10-year risk of a combined endpoint (incident coronary heart disease, stroke, heart failure, chronic kidney disease, lower extremity hospitalizations) in people with diabetes, using demographic and clinical information, and a panel of traditional and non-traditional biomarkers.

METHODS: We included in the study 654 participants in the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort study, with diagnosed diabetes (visit 2; 1990-1992). Models included self-reported variables (Model 1), clinical measurements (Model 2), and glycated haemoglobin (Model 3). Model 4 tested the addition of 12 blood-based biomarkers. We compared models using prediction and discrimination statistics.

RESULTS: Successive stages of model development improved risk prediction. The C-statistics (95% confidence intervals) of models 1, 2, and 3 were 0.667 (0.64, 0.70), 0.683 (0.65, 0.71), and 0.694 (0.66, 0.72), respectively (p 

CONCLUSIONS: These biomarkers, particularly those of kidney filtration, may help distinguish between people at low versus high risk of long-term major complications.

DOI10.1111/dom.12686
Alternate JournalDiabetes Obes Metab
PubMed ID27161077
PubMed Central IDPMC4993670
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
HHSN268201100009I / HL / NHLBI NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
HHSN268201100005G / HL / NHLBI NIH HHS / United States
HHSN268201100008I / HL / NHLBI NIH HHS / United States
R01 DK089174 / DK / NIDDK NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
T32 HL007024 / HL / NHLBI NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
HHSN268201100005I / HL / NHLBI NIH HHS / United States
K24 DK106414 / DK / NIDDK NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
HHSN268201100007I / HL / NHLBI NIH HHS / United States