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Aldo Lorenzetti M.D, Internal Medicine & Hepatology, Milano - SIMEDET Delegate
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Food sources of #fructose-containing sugars and #glycaemic control: systematic review and meta-analysis of controlled intervention studies

https://www.bmj.com/content/363/bmj.k4644

Total fructose-containing sugars had no harmful effect on any outcome in substitution or subtraction studies, with a decrease seen in HbA1c in substitution studies (mean difference −0.22% (95% confidence interval to −0.35% to −0.08%), −25.9 mmol/mol (−27.3 to −24.4)), but a harmful effect was seen on fasting insulin in addition studies (4.68 pmol/L (1.40 to 7.96)) and ad libitum studies (7.24 pmol/L (0.47 to 14.00)). There was interaction by food source, with specific food sources showing beneficial effects (fruit and fruit juice) or harmful effects (sweetened milk and mixed sources) in substitution studies and harmful effects (sugars-sweetened beverages and fruit juice) in addition studies on at least one outcome. Most of the evidence was low quality.

Conclusions

Energy control and food source appear to mediate the effect of fructose-containing sugars on glycaemic control. Although most food sources of these sugars (especially fruit) do not have a harmful effect in energy matched substitutions with other macronutrients, several food sources of fructose-containing sugars (especially sugars-sweetened beverages) adding excess energy to diets have harmful effects. However, certainty in these estimates is low, and more high quality randomised controlled trials are needed.
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How effective are trained #dogs at alerting their owners to changes in blood #glycaemic levels?: Variations in performance of glycaemia alert dogs

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210092

Dogs varied in their performance, with median sensitivity to out-of-range episodes at 70% (25th percentile = 50, 75th percentile = 95). To hypoglycaemic episodes the median sensitivity was 83% (66–94%) while to hyperglyaemic episodes it was 67% (17–91%). The median positive predictive value (PPV) was 81% (68–94%), i.e. on average 81% of alerts occurred when glucose levels were out of target range. For four dogs, PPV was 100%. Individual characteristics of the dog, the partnership and the household were significantly associated with performance (e.g., whether the dog was previously a pet, when it was trained, whether its partner was an adult or child).

Conclusions
The large sample shows that the individual performance of dogs is variable, but overall their sensitivity and specificity to OOR episodes are better than previous studies suggest. Results show that optimal performance of glycaemic alert dogs depends not only on good initial and ongoing training, but also careful selection of dogs for the conditions in which they will be working