Dentists At The Front Line In Diabetes Epidemic

Dentists at the Front Line in Diabetes Epidemic

HealthDay Reporter
THURSDAY, Feb. 23, 2017 (HealthDay News) -- You'd probably be surprised if your dentist said you might have type 2 diabetes. But new research finds that severe gum disease may be a sign the illness is present and undiagnosed.
The study found that nearly one in five people with severe gum disease (periodontitis) had type 2 diabetes and didn't know it. The researchers said these findings suggest that the dentist's office may be a good place for a prediabetes or type 2 diabetes screening.
"Be aware that worsened oral health -- in particular, periodontitis -- can be a sign of an underlying [condition], such as diabetes," said study author Dr. Wijnand Teeuw. He's the chief of the periodontology clinic at the Academic Center for Dentistry Amsterdam in the Netherlands.
"Early diagnosis and treatment of both periodontitis and diabetes will benefit the patient by preventing further complications," Teeuw added.
Diabetes is a worldwide epidemic. In 2010, it was estimated that 285 million adults worldwide had diabetes. By 2030, that number is expected to rise to 552 million, according to the study authors. It's suspected that as many as one-third of people who have diabetes are unaware they have the disease.
Untreated, diabetes can lead to a number of serious complications, such as vision problems, serious kidney disease, heart trouble and infections that take a long time to heal, according to the American Diabetes Association.
Periodontitis -- an infection that causes inflammation of the gums and destruction of the bones that support the teeth -- is often considered Continue reading

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Thiamine Deficiency and Sugar in Diabetes

Thiamine Deficiency and Sugar in Diabetes
Author: Derrick Lonsdale MD, FACN, CNS No Comments Share:
Thiamine is one of the B vitamins and I need to explain its action. To put it as simply as possible, it regulates sugar metabolism in every cell within the body and has a special importance in the brain. About four years ago a researcher in England reported that there was a mild deficiency of thiamine (vitamin B1) in diabetic patients, a disease that affects sugar metabolism. He said that all diabetics should have a supplement of thiamine because he had anticipated that it will prevent complications in this devastating disease. If that is not enough to make a diabetic sit up and take notice I would be very surprised. I will try to explain this a little further.
A program on PBS television called The Quiet Revolution reported that there were 29 million patients in the United States with type two diabetes and as many as 70 million with pre-diabetes, meaning that they were on their way to contract the disease. If we had 29 million cases of flu it would be called a pandemic. Most people with type 2 diabetes have no idea that their health before the onset of the disease is within their own responsibility. Our culture says go ahead, do what you like, eat what you like, drink what you like; if you get sick, it is just bad luck and you go to one of those clever characters called Dr. who will produce the magic bullet that cures you because of the wonders of modern scientific medicine.
Although both types one and two have different causative factors, I want to emphasize very stro Continue reading

The Most Common Hassle For Type 1 Diabetes Patients

Home / Conditions / Type 1 Diabetes / The Most Common Hassle For Type 1 Diabetes Patients
The Most Common Hassle For Type 1 Diabetes Patients
Barrier means more work including monitoring more often and making more adjustments.
Changing the perception of hassle is most likely the most common barrier we can deal with for type 1 patients who do not choose to wear pumps and CGMs.
Findings from a survey of more than 1,500 participants in the T1D Exchange were published online November 29 in Diabetes Care by Molly L. Tanenbaum, PhD, of the department of pediatrics, Stanford University School of Medicine, Palo Alto, California, and colleagues.
In the survey, which includes data for more than 28,000 type 1 diabetes patients at 75 specialty clinics around the United States, about two-thirds were wearing insulin pumps, but in 20132014 only about 9% were using CGMs.
Cost is the most common reason for those who dont have insurance. This was the most often-cited reasons for not wearing insulin pumps or CGMs.
But the studys main focus was on potentially modifiable barriers for which interventions could be developed to improve uptake. Of those, hassle and cosmetic concerns about wearing a device on the body all the time topped the list, and these reasons were most often cited by younger patients.
Having a discussion with your patients about the use of these technologies can help clear the air and provide possible financial assistance.
Since the data shows quite a variety of different barriers and reasons people may have for not using devices, some of which are modifiable, those Continue reading

Baths ward-off diabetes, but showers are more hygienic! | Daily Mail Online

Research suggests it might even help athletes and improve fitness levels.Scientists at Bangor University have discovered that a hot bath can even stimulate the immune system.
Professor Neil Walsh, an exercise scientist at the university, explains: This may be helpful for heavy exercisers, as hard exercise temporarily decreases immune function.
Here are the health facts you need to weigh up when deciding whether you should bath or shower
Last year, experts at Loughborough University discovered that sitting for an hour in a hot bath (40c/104f) lowered blood sugar levels more effectively than spending the same amount of time cycling. This could, in turn, lower the risk of type 2 diabetes.
There are two reasons why baths might affect blood sugar levels, says Dr Steve Faulkner, an exercise physiologist and the studys author, now based at Nottingham Trent University.
First, heat increases blood flow around the body as the body tries to cool itself down, and this increased blood flow is thought to increase the amount of blood sugar taken up by the muscles, which thereby reduces the amount in the blood.
Health boost: Experts recently conducted a study which claimed taking baths could lower the risk of type 2 diabetes, which is increasingly-common
We also suspect substances called heat shock proteins play a role, says Dr Faulkner. As the name suggests, these are produced by cells in response to heat, and they play a role in blood sugar regulation.
Its unlikely that heat shock proteins will be produced to the same extent if you opt for a shower.
You are fully submerged in Continue reading

Machine Learning forDiabetes

The above plot shows the training and test set accuracy on the y-axis against the setting of n_neighbors on the x-axis. Considering if we choose one single nearest neighbor, the prediction on the training set is perfect. But when more neighbors are considered, the training accuracy drops, indicating that using the single nearest neighbor leads to a model that is too complex. The best performance is somewhere around 9 neighbors.
The plot suggests that we should choose n_neighbors=9. Here we are:
knn = KNeighborsClassifier(n_neighbors=9)
print('Accuracy of K-NN classifier on training set: {:.2f}'.format(knn.score(X_train, y_train)))
print('Accuracy of K-NN classifier on test set: {:.2f}'.format(knn.score(X_test, y_test)))
Accuracy of K-NN classifier on training set: 0.79
Accuracy of K-NN classifier on test set: 0.78
Logistic Regression is one of the most common classification algorithms.
from sklearn.linear_model import LogisticRegression
print("Training set score: {:.3f}".format(logreg.score(X_train, y_train)))
print("Test set score: {:.3f}".format(logreg.score(X_test, y_test)))
The default value of C=1 provides with 78% accuracy on the training and 77% accuracy on the test set.
logreg001 = LogisticRegression(C=0.01).fit(X_train, y_train)
print("Training set accuracy: {:.3f}".format(logreg001.score(X_train, y_train)))
print("Test set accuracy: {:.3f}".format(logreg001.score(X_test, y_test)))
Using C=0.01 results in lower accuracy on both the training and the test sets.
logreg100 = LogisticRegression(C=100).fit(X_train, y_train)
print("Training set accuracy Continue reading