New screening algorithm identifies new risk factors for type 2 diabetes

by Barbara Hewitt on February 19, 2016

Previously unknown risk factors for type 2 diabetes have been identified by research in the United States due to a new screening algorithm.

A study conducted by researchers at the University of California’s Semel Institute for Neuroscience and Human Behaviour in Los Angeles says that the algorithm provides a cheaper and more accurate way to identify people with undiagnosed type 2 diabetes.

Previously unknown risk factors found included a history of sexual and gender identity disorders, intestinal infections and Chlamydia which increases the risk of type 2 diabetes by 82%.


The researchers examined the electronic records of 9,948 people from hospitals, clinics and doctor’s offices throughout the US, evaluating vital signs, prescription medications taken by each patient, and their reported ailments.

Half of the data was used to develop an algorithm that could predict the likelihood of type 2 diabetes in a person. Once this had been developed, the researchers used the other half of the data to test it.

Through testing the algorithm, the researchers found several previously undiscovered risk factors for type 2 diabetes, including the sexual and gender identity disorders, which increased the risk by 130% and intestinal infections such as colitis, enteritis and gastroenteritis which increased the risk by 88%.

By comparison, having high body mass index (BMI), a known risk factor for type 2 diabetes, increased the risk by 101% and other factors linked to type 2 diabetes included herpes, chicken pox and shingles.

They also found that several factors which were previously thought to have no effect on type 2 diabetes risk, were found to decrease the risk, such as being prone to migraines and taking anti-anxiety medication.

The researchers said that further studies are now needed to find out why these factors have such a high likelihood of increasing the risk of developing type 2 diabetes and how these can be assessed alongside other known risk factors such as weight, family history and age.

“With widespread implementation, these discoveries have the potential to dramatically decrease the number of undetected cases of type 2 diabetes, prevent complications from the disease and save lives,” said Ariana Anderson, assistant research professor and statistician at the Semel Institute for Neuroscience and Human Behaviour.

“Given that one in four people with diabetes don’t know they have the disease, it’s very important to be able to say this person has all these other diagnoses, so we’re a little bit more confident that she is likely to have diabetes. We need to be sure to give her the formal laboratory test, even if she’s asymptomatic,” she explained.

She pointed out that the study does not suggest that current screening methods don’t work as generally, they are accurate, but it does suggest that they could be made even more accurate and also cheaper.

“There’s so much information available in the medical record that could be used to determine whether a patient needs to be screened, and this information isn’t currently being used. This is a treasure trove of information that has not begun to be exploited to full extent possible,” said Mark Cohen, a Semel Institute professor in residence.

“The overall message is that ordinary record keeping that doctors do is a very, very rich source of information. If you use a computerised approach to studying patterns in that data, you can greatly improve diagnosis and medical care,” he added.

The opinions expressed in this article do not necessarily reflect the views of the Community and should not be interpreted as medical advice. Please see your doctor before making any changes to your diabetes management plan.

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