Scientists Develop Tool To Identify Patients With Low Blood Sugar Risk

By Staff

Scientists have developed a tool for identifying diabetes patients who are at the highest risk for being admitted to a hospital due to very low blood sugar.

"Sometimes a person with diabetes is unaware that their blood sugar is dropping and can progress quickly into severe hypoglycemia, which has been associated with falls, automobile accidents, heart attacks, coma, and even death," said Andrew J Karter from the Kaiser Permanente Division of Research in the US.

"Hypoglycemia is often preventable with the proper clinical attention, and we believe this tool will help focus that attention on the patients who most need it," said Karter, lead author of the study published in the journal JAMA Internal Medicine.

The researchers developed the hypoglycemia risk stratification tool by identifying 156 possible risk factors for hypoglycemia and collecting data from more than 200,000 patients with type 2 diabetes.

diabetes risk

Using machine-learning analytical techniques, they developed a model to predict a patient's 12-month risk of hypoglycemia-related emergency department or hospital use.

The final model was based on six variables: number of prior episodes of hypoglycemia-related hospitalisations; use of insulin; use of sulfonylurea (an oral medication commonly used to treat diabetes); severe kidney disease; number of emergency visits for any reason in the past year; and age.

Based on the model, the researchers created a practical tool to categorise patients into high (greater than five per cent), intermediate (1 to 5 per cent) or low (less than 1 per cent) annual risk of hypoglycemia-related emergency department or hospital utilisation.

"The tool was then validated with data from more than 1.3 million members of the US Veterans Health Administration and nearly 15,000 Kaiser Permanente members in Washington state with type 2 diabetes," researchers said.

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    Read more about: diabetes blood sugar
    Story first published: Tuesday, August 22, 2017, 23:00 [IST]
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