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ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2020

Looping with Do-It-Yourself Artificial Pancreas Systems During Ramadan Fasting in Type 1 Diabetes Mellitus: Perspectives of a User and a Physician.

Syed Haris Ahmed, Saira Gallo

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Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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2 authors.

Syed Haris AhmedDepartment of Endocrinology and Metabolic Medicine, Countess of Chester Hospital NHS Foundation Trust, Chester, UK.ORCID 0000-0002-7815-2907
Saira GalloTustin, California USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hybrid closed-loop automated insulin delivery systems have helped type 1 diabetes (T1D) users close the loop between glucose monitoring and insulin delivery, a very important step in efforts to simulate the glucose-responsive insulin secretory function of a healthy pancreas. Do-It-Yourself Artificial Pancreas Systems (DIY APS) are a form of hybrid closed-loop system that use open-source algorithms, which govern the delivery of insulin in response to interstitial glucose and other variables that are personalized to an individual. The flexibility and customization afforded by these systems make them amenable for use in different worldly circumstances, one of which is fasting during the annual occurrence of Ramadan for observant Muslims. Here, we present the views of a DIY APS user who was able to fast successfully on most days of Ramadan after adopting this system, and the overview of a physician on these systems, with a focus on fasting during Ramadan with T1D.

Indexed as

Artificial pancreas systemsDo-it-yourselfHybrid closed-loop systemsIftaarLoopingRamadanSuhoorTime-in-rangeType 1 diabetes#WeAreNotWaiting

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.