A risk score including body mass index, glycated haemoglobin and triglycerides predicts future glycaemic control in people with type 2 diabetes

Autor: Mirela Popa, Steven H. Hendriks, Arianne M. J. Elissen, Dirk Ruwaard, Martijn C. G. J. Brouwers, Dorijn F. L. Hertroijs, Sebastian Köhler, Henk J. G. Bilo, Nicolaas C. Schaper, Stylianos Asteriadis
Přispěvatelé: Promovendi PHPC, Health Services Research, RS: CAPHRI - R2 - Creating Value-Based Health Care, Interne Geneeskunde, MUMC+: MA Endocrinologie (9), RS: CARIM - R3.01 - Vascular complications of diabetes and the metabolic syndrome, RS: CARIM - R3.02 - Hypertension and target organ damage, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, Psychiatrie & Neuropsychologie, DKE Scientific staff, RS: FSE DACS, Lifestyle Medicine (LM)
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Blood Glucose
Male
Pediatrics
Endocrinology
Diabetes and Metabolism
Type 2 diabetes
Body Mass Index
MELLITUS
0302 clinical medicine
Endocrinology
Triglycerides/metabolism
030212 general & internal medicine
Netherlands
database research
OUTCOMES
Framingham Risk Score
diabetes
Middle Aged
glycaemic control
Treatment Outcome
type 2
Cohort
Original Article
Female
Diabetes Mellitus
Type 2/blood
Risk assessment
Cohort study
medicine.medical_specialty
Glycated Hemoglobin A/metabolism
030209 endocrinology & metabolism
Hypoglycemic Agents/therapeutic use
ALL-CAUSE
Risk Assessment
PATIENT
03 medical and health sciences
primary care
Diabetes mellitus
Internal Medicine
medicine
cohort study
Diabetes Mellitus
Hypoglycemic Agents
Humans
Risk Assessment/methods
Triglycerides
Retrospective Studies
Type 2/blood
Glycated Hemoglobin
Blood Glucose/metabolism
business.industry
MIXTURE
MEDICINE
MORTALITY
Retrospective cohort study
Original Articles
CARE
medicine.disease
DISEASE MANAGEMENT
Diabetes Mellitus
Type 2
Physical therapy
TRAJECTORIES
business
Body mass index
Zdroj: Diabetes, Obesity & Metabolism
Diabetes, Obesity and Metabolism, 20(3), 681-688. Wiley
Diabetes obesity & metabolism, 20(3), 681-688. Wiley
ISSN: 1463-1326
1462-8902
Popis: AimTo identify, predict and validate distinct glycaemic trajectories among patients with newly diagnosed type 2 diabetes treated in primary care, as a first step towards more effective patient-centred care.MethodsWe conducted a retrospective study in two cohorts, using routinely collected individual patient data from primary care practices obtained from two large Dutch diabetes patient registries. Participants included adult patients newly diagnosed with type 2 diabetes between January 2006 and December 2014 (development cohort, n=10528; validation cohort, n=3777). Latent growth mixture modelling identified distinct glycaemic 5-year trajectories. Machine learning models were built to predict the trajectories using easily obtainable patient characteristics in daily clinical practice.ResultsThree different glycaemic trajectories were identified: (1) stable, adequate glycaemic control (76.5% of patients); (2) improved glycaemic control (21.3% of patients); and (3) deteriorated glycaemic control (2.2% of patients). Similar trajectories could be discerned in the validation cohort. Body mass index and glycated haemoglobin and triglyceride levels were the most important predictors of trajectory membership. The predictive model, trained on the development cohort, had a receiver-operating characteristic area under the curve of 0.96 in the validation cohort, indicating excellent accuracy.ConclusionsThe developed model can effectively explain heterogeneity in future glycaemic response of patients with type 2 diabetes. It can therefore be used in clinical practice as a quick and easy tool to provide tailored diabetes care.
Databáze: OpenAIRE
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