Journal article

Clinical Prediction Tool To Identify Adults With Type 2 Diabetes at Risk for Persistent Adverse Glycemia in Hospital

Mervyn Kyi, Alexandra Gorelik, Jane Reid, Lois M Rowan, Paul R Wraight, Peter G Colman, Spiros Fourlanos



OBJECTIVES: Given the high incidence of hyperglycemia and hypoglycemia in hospital and the lack of prediction tools for this problem, we developed a clinical tool to assist early identification of individuals at risk for persistent adverse glycemia (AG) in hospital. METHODS: We analyzed a cohort of 594 consecutive adult inpatients with type 2 diabetes. We identified clinical factors available early in the admission course that were associated with persistent AG (defined as ≥2 days with capillary glucose 15 mmol/L during admission). A prediction model for persistent AG was constructed using logistic regression and internal validation was performed using a split-sample approach. RESULTS: Persi..

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Funding Acknowledgements

The authors are grateful for the enthusiasm of the nursing managers and staff on the participating wards during the RAPIDS study. We acknowledge support from Australasian Medical and Scientific, Ltd, for installation, training and technical support of networked blood glucose metres. This investigator-initiated study was conducted with the grant support from the Australian Diabetes Society,Sanofi Diabetes and the Royal Melbourne Hospital Lottery. M.K. was supported by a postgraduate scholarship from the National Health and Medical Research Council. The funders had no role in the study design, recruitment, data collection, analysis, interpretation or writing of the report. The de identified patientlevel data set analyzed in this study is available from the corresponding author on reasonable request. Data from this study were presented as a poster at the 78th meeting of the American Diabetes Association, Orlando, Florida, United States, in June 2018.