Doctors warn people without diabetes should not use blood sugar monitors

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No need for a blood glucose meter people without it Diabetes may lead to eating disorder, doctor I warned you.

Devices manufactured by company Similar to ZOE, these Social media This allows users to monitor their nutritional levels.

The £300 program will allow participants to record their actions. food intake You will wear a blood sugar monitor for two weeks to measure your blood sugar levels.

but NHS National Diabetes Adviser Professor Partha Kerr said there was no strong evidence that the device would help people without diabetes.

He warned that using the technology without a medical reason could lead to an obsessive focus on numbers and, in the most extreme cases, “could lead to eating disorders.”

Meanwhile, eating disorders charity Beat told BBC News: “People with eating disorders often become obsessed with numbers as part of their illness, so we never recommend the use of blood sugar monitors to those affected. ” he said.

ZOE said in a statement: “ZOE takes a scientifically rigorous approach that is unrivaled in the industry in terms of clinical trials, robust research, a dedicated team of scientists and nutrition experts, and is based on positive evidence. We aim to improve your health through the advice we provide.”

This comes after scientists discovered a way to test whether you have diabetes by having your smartphone say just a few sentences.

Founded by the US-based Klick Labs team AI model that can identify if a person has type 2 diabetes Analyzing 6 to 10 seconds of audio, the test found an 89 percent correct answer rate for women and 86 percent for men.

“Our study highlights significant differences in vocalizations between patients with type 2 diabetes and non-diabetics, and could change the way the medical community screens for diabetes,” said Jaycee Kaufman, a researcher at the Crick Institute. ” he said.

“Current detection methods can take a lot of time, travel, and cost. Voice technology has the potential to completely remove these barriers.”

The study involved analyzing 18,000 recordings to identify acoustic features that differentiate non-diabetic patients from diabetic patients. Using signal processing, they were able to detect subtle changes in pitch and intensity that are imperceptible to the human ear.

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