Diabetic ketoacidosis in adult patients: an audit of factors influencing time to normalisation of metabolic parameters |
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| Authors: | Melissa H. Lee Genevieve L. Calder John D. Santamaria Richard J. MacIsaac |
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| Affiliation: | 1. Department of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia;2. Department of Intensive Care, St Vincent's Hospital Melbourne, Melbourne, Victoria, Australia;3. Department of Medicine, The University of Melbourne, Melbourne, Victoria, Australia |
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| Abstract: | Background Diabetic ketoacidosis (DKA) is an acute life‐threatening metabolic complication of diabetes that imposes substantial burden on our healthcare system. There is a paucity of published data in Australia assessing factors influencing time to resolution of DKA and length of stay (LOS). Aims To identify factors that predict a slower time to resolution of DKA in adults with diabetes. Methods Retrospective audit of patients admitted to St Vincent's Hospital Melbourne between 2010 to 2014 coded with a diagnosis of ‘Diabetic Ketoacidosis’. The primary outcome was time to resolution of DKA based on normalisation of biochemical markers. Episodes of DKA within the wider Victorian hospital network were also explored. Results Seventy‐one patients met biochemical criteria for DKA; median age 31 years (26–45 years), 59% were male and 23% had newly diagnosed diabetes. Insulin omission was the most common precipitant (42%). Median time to resolution of DKA was 11 h (6.5–16.5 h). Individual factors associated with slower resolution of DKA were lower admission pH (P < 0.001) and higher admission serum potassium level (P = 0.03). Median LOS was 3 days (2–5 days), compared to a Victorian state‐wide LOS of 2 days. Higher comorbidity scores were associated with longer LOS (P < 0.001). Conclusions Lower admission pH levels and higher admission serum potassium levels are independent predictors of slower time to resolution of DKA. This may assist to stratify patients with DKA using markers of severity to determine who may benefit from closer monitoring and to predict LOS. |
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| Keywords: | diabetes diabetic ketoacidosis hyperglycaemic emergencies metabolic parameters hyperglycaemia |
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