April 28, 2018 : Issue #935

• Everything You Need To Know To Prescribe An SGLT-2 Inhibitor (Part 2)
• Treatment With Diabetes Drugs Causes Early Worsening of Renal Function
• Point: FDA Approves Artificial Intelligence (AI) To Detect Retinopathy
• Counterpoint: The Pros and Cons of AI-based ‘Diagnosis’ of Diabetic Retinopathy
  • By A. Paul Chous, MA, OD, FAAO, CDE
• Treating Hypoglycemia With A Needle-Free Glucagon
• Prediabetes Diagnosis Linked to increased Risk for CVD, Renal Disease

I was having dinner with a group of cycling couples recently We are all participating in the Bike Virginia 6-day riding event in late June and we were discussing travel plans. One of the participants is an optometrist and we got into a discussion about prescription sunglasses for the ride. One of the riders pointed out that looking at his GPS tracking unit was a lot harder in the full sun than in the house and wondered which color lenses would be best. This brought about a conversation on how we as the patients are asked to decide which lenses are the best when the eye doctor is getting our prescription.

Our optometrist friend pointed out that he did not really have to do this because there are devices that they can use to evaluate our eyes and produce the “perfect” prescription. When someone asked him why he tortures us with the “is this better” routine, he answered that there is a human component missing; even though the device can see the lens, it can’t see what the patient is seeing.

This week, we have an article on the new Idx-DR. This device uses artificial intelligence (AI) to detect retinopathy. According to the company there is no need to have an eye professional involved. This means that many more patients could have an earlier diagnosis if the device was in a clinic or medical office. However, just like the device that can determine a patient’s eyeglass prescription, this device lacks the human element that our optometrist-riding friend described.

Please check out Item 3 on this new device and then read an editorial opinion on why the human element is needed, by Dr. Paul Chous.

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We can make a difference!

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Dave Joffe

Editor-in-chief

Do you recommend less fruit or no fruit in the diet of your patients with type 2 who have excessive high blood glucose?

Follow the link to share your opinion.

Roche announced this week that they are going to launch the Solo Tubeless Patch pump, which will be operated through a remote control which will have its own blood glucose meter. The Solo patch pump will be in direct competition to the Omnipod tubeless insulin pump.

This new tool can help your patients determine the best CGM for their use.  Because each patient is different, we are told to individualize each patient to determine the best treatment. The same has to be said for the different CGM systems. Each patient needs to have the information that best describes which CGM system is best for them. This comparison of the two most popular CGM system provides all the information that your patients can use to choose the CGM best for them. Libre Vs. DexCom CGM(pdf)

In which of the examples can HbA1c be inaccurate? (When presented to 200 medical professionals, 20% got it wrong.)

A. Recent blood transfusion
B. Renal failure
C. G6PD deficiency
D. Medication Uwe (e.g. aspirin)
E. All of the above

Follow the link for the answer.

For those starting later in the day to eat their first meal of the day, the risk for having a higher BMI is increased, but research is lacking regarding this phenomenon. So, researchers from the University of Illinois at Chicago College of Medicine led by Dr. Sirimon Reutakul, associate professor of endocrinology, diabetes and metabolism, wanted to determine if morning or evening preference among people with type 2 diabetes was associated with an increased risk for a higher BMI and if so, what specific factors about evening preference contributed to the increased risk? They recruited 210 non-shift workers with type 2 diabetes for their study. Morning/evening preference was assessed using a questionnaire that focused on preferred time for waking up and going to bed; time of day spent exercising; and time of day spent engaged in mental activity (working, reading, etc.). Scores on the questionnaire can range from 13, indicating extreme evening preference, to 55 indicating extreme morning preference. Participants with an evening preference were those who scored less than 45 on the questionnaire, while those with morning preference scored a 45 or higher. Participants were interviewed regarding their meal timing, and daily caloric intake was determined via self-reported one-day food recalls. Weight measurements were taken and BMI was calculated for each participant. Sleep duration and quality were measured by self-report and questionnaire. Self-reported average sleep duration was 5.5 hours/night. On average, participants consumed 1,103 kcal/day. The average BMI among all participants was 28.4 kg/m2, which is considered overweight. Of the participants, 97 had evening preference and 113 had morning preference. Participants with morning preference ate breakfast between 7 a.m. and 8:30 a.m., while participants with evening preference ate breakfast between 7:30 a.m. and 9 a.m. Participants with morning preference had earlier meal timing, including breakfast, lunch, dinner and the last meal.  The researchers found that having more evening preference was associated with higher BMI. Caloric intake and lunch and dinner times were not associated with having a higher BMI.

Morning preference was associated with earlier breakfast time and lower BMI by 0.37 kg/m2.  Reutrakul added that, “Later breakfast time is a novel risk factor associated with a higher BMI among people with type 2 diabetes.”  Reutrakul speculates that later meal times may misalign the internal biological clock, which plays a role in circadian regulation. Circadian misalignment can lead to dysregulation of energy metabolism according to previous studies. — Materials provided by University of Illinois at Chicago published April 2018 in journal Diabetic Medicine

Surprise findings for treatment class and appropriate patient selection

In results of five trials, effects of antihyperglycemic drug found to occur during first few months or years.

Software provides screening decision without need for a clinician to interpret image or results.

By A. Paul Chous, MA, OD, FAAO, CDE

The FDA just gave first approval to an artificial intelligence (AI) algorithm for the detection of diabetic retinopathy in the offices of non-ophthalmic health care practitioners. Dubbed the IDx-DR (IDx, LLC, Coralville, Iowa), and paired with a Topcon NW400 non-mydriatic retinal camera, captured images are sent to a cloud-based server that utilizes the IDx-DR software and a ‘deep learning’ algorithm to detect retinal findings consistent with diabetic retinopathy based on autonomous comparison with a large dataset of representative fundus images.

Prospective study evaluates use of nasal glucagon for treatment of moderate to severe hypoglycemia in adults with type 2 diabetes.

New study shows patients with diabetes receiving more treatment thus reducing complications

Quote of the Week!

“No winter lasts forever; no spring skips its turn.”

…Hal Borland

Diabetes in Control gratefully acknowledges the assistance of the following pharmacy doctoral candidates in the preparation of this week’s newsletter:

Vidhi Patel, Pharm. D. Candidate 2018, LECOM College of Pharmacy

Your Friends in Diabetes Care
Steve and Dave
Diabetes In Control
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