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Sodium-glucose cotransporter inhibitor (SGLTi) use is not uncommon in type 1 diabetes (T1D). Not much is known about possible risks or benefits when combining SGLTi with advanced hybrid closed-loop (aHCL). This report describes in detail the daily insulin dosing by the MiniMed™ 780G algorithm in a patient with T1D after SGLTi initiation leading to diabetic ketoacidosis (DKA). Within a few days after start of SGLTi, the aHCL algorithm reduced autobasal and autocorrection doses, whereas meal bolus insulin doses were reduced mainly due to frequent activation of the "safe meal bolus." Taken together, there was a significant 49% reduction in total daily insulin dose after start of SGLTi, leading to insulin doses below the minimum needed to prevent ketone formation. Until more is known about the influence of SGLTi on aHCL algorithm functioning, we recommend caution with SGLTi use in people with T1D on aHCL systems to avoid increased DKA risk. ispartof: DIABETES TECHNOLOGY & THERAPEUTICS vol:24 issue:7 pages:516-519 ispartof: location:United States status: published

Background/purpose: Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach.Methods: We estimate the probability of occurrence of each attribute as a function of the skin diseases. We use the distribution of this probability across the studied diseases and its entropy to define the discriminative power of the attribute. The discriminative power has a maximum value for attributes that occur (or do not occur) for only one disease and a minimum value for those which are equally likely to be observed among all diseases.Results: Verrucous surface, red and brown colors, and the presence of more than 10 lesions are among the most informative attributes. A ranking of attributes is also carried out and used together with a naive Bayesian classifier, yielding results that confirm the soundness of the proposed method.Conclusion: The proposed measure is proven to be a reliable way of assessing the discriminative power of dermatological attributes, and it also helps generate a condensed dermatological lexicon. Therefore, it can be of added value to the manual or computer-aided diagnostic process.