scholarly journals Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study

2018 ◽  
Vol 49 (3) ◽  
pp. 834-844
Author(s):  
Yuheng Chen ◽  
Wenna Duan ◽  
Parshant Sehrawat ◽  
Vaibhav Chauhan ◽  
Freddy J Alfaro ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Pilot Study ◽  
Pipeline Pilot ◽  
Diabetes Severity

1158-P: Type 2 Diabetes Patients Subtype Analysis: Unbiased Machine Learning for Future Personalized T2D Care

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1158-P
Author(s):  
LI CHEN ◽  
LINGGE FENG ◽  
CUI TANG ◽  
YI ZHANG
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
P Type ◽  
Diabetes Patients

1311-P: Machine Learning (ML) Application to Predict Patient Risk of Nonadherence in Type 2 Diabetes Management Using U.S. Claims Databases

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1311-P
Author(s):  
XIN CHEN ◽  
GAIL FERNANDES ◽  
JIE CHEN ◽  
ZHIWEN LIU ◽  
RICHARD BAUMGARTNER
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Diabetes Management ◽  
Patient Risk

1131-P: Endoscopic Duodenal Submucosal Laser Ablation for the Treatment of Type 2 Diabetes Mellitus: Results of First-in-Human Pilot Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1131-P ◽  
Author(s):  
MILOS MRAZ ◽  
IDAN MARCOVITCH ◽  
IVANA LANKOVA ◽  
HELENA KRATOCHVILOVA ◽  
ANNA CINKAJZLOVA ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Laser Ablation ◽  
Pilot Study

973-P: The Feasibility of Continuous Glucose Monitoring in Youth with Type 2 Diabetes Mellitus: A Pilot Study

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 973-P
Author(s):  
ALLISON LAROCHE ◽  
KRISTINA UTZSCHNEIDER ◽  
CATHERINE PIHOKER
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Pilot Study ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring

1552-P: Machine Learning Approach to Decision-Making for Initial Insulin Use in Japanese Patients with Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1552-P
Author(s):  
KAZUYA FUJIHARA ◽  
MAYUKO H. YAMADA ◽  
YASUHIRO MATSUBAYASHI ◽  
MASAHIKO YAMAMOTO ◽  
TOSHIHIRO IIZUKA ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Decision Making ◽  
Japanese Patients ◽  
Learning Approach ◽  
Machine Learning Approach ◽  
Insulin Use

Personalized Behavioral Nutrition Intervention in Older Asian Americans with Type 2 Diabetes during COVID-19 Pandemic: Study Protocol for a Pilot, Hybrid, Randomized Controlled Trial (Preprint)

2020 ◽  
Author(s):  
Jisook Ko ◽  
Yan Du ◽  
Rozmin Jiwani ◽  
Chengdong Li ◽  
Jing Wang
Keyword(s):  
Type 2 Diabetes ◽  
Clinical Trials ◽  
Pilot Study ◽  
Glycemic Control ◽  
Asian Americans ◽  
Control Group ◽  
Management Approach ◽  
Self Monitoring ◽  
Behavioral Nutrition

BACKGROUND The COVID-19 pandemic has challenged the in-person-based self-management approach (i.e., face-to-face or group approach) of type 2 diabetes (T2D). Older adults with T2D, including Asian Americans (AAs), have experienced worsening of diabetes control due to various reasons, including uncertainty of continuous access to essential diabetes medications, devices, education, limited health literacy, as well as constant anxiety and stress. Hybrid clinical trials that incorporate virtual elements into the in-person-based study could provide these vulnerable populations with accessible and timely interventions OBJECTIVE The primary aims of this pilot study are to determine (1) the effect of personalized behavioral nutrition (PBN) intervention on glycemic control, weight control, and metabolites profiles; and (2) the acceptability of PBN. to enhance glycemic control using personalized behavioral nutrition. METHODS Participants will be recruited with a web-based registry, advertisements in ethnic newspapers, and social network services popular among AAs. A total of 60 AAs, aged 65 years or older, who are descendants of Chinese, Korean, or South Asian, and have a diagnosis of T2D will be randomized into two groups: a PBN group (n=30) and a control group (n=30). A 4-week PBN intervention comprises three components: 1) digital self-monitoring; 2) personal nutrition change goals and recommendations; and 3) diabetes nutrition educations. All participants will complete digital self-monitoring on diet, physical activity, and blood glucose. In addition, all participants will access an interactive digital platform to track their self-monitoring data and communicate with the research team. The effectiveness and acceptability of implementing the intervention will be assessed. RESULTS Funding support and institutional review board approval for this study have been secured. Data collection started in August 2020 and is ongoing. CONCLUSIONS To our knowledge, this is the first study to determine the effectiveness and acceptability of PBN utilizing a metabolomics approach and digital-assisted intervention with hybrid RCT among older AAs. The findings of this pilot study will inform the development of a full-scale PBN protocol and hybrid clinical trials that can be adapted for people with T2D in the ongoing pandemic.

scholarly journals Treatment with a DPP-4 inhibitor at time of hospital admission for COVID-19 is not associated with improved clinical outcomes: data from the COVID-PREDICT cohort study in The Netherlands

2021 ◽  
Author(s):  
Rick I. Meijer ◽  
Trynke Hoekstra ◽  
Niels C. Gritters van den Oever ◽  
Suat Simsek ◽  
Joop P. van den Bergh ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cohort Study ◽  
Hospital Admission ◽  
Clinical Outcomes ◽  
Primary Outcome ◽  
Infectious Complications ◽  
Glucose Lowering ◽  
Diabetes Severity ◽  
Outcome Mortality

Abstract Purpose Inhibition of dipeptidyl peptidase (DPP-)4 could reduce coronavirus disease 2019 (COVID-19) severity by reducing inflammation and enhancing tissue repair beyond glucose lowering. We aimed to assess this in a prospective cohort study. Methods We studied in 565 patients with type 2 diabetes in the CovidPredict Clinical Course Cohort whether use of a DPP-4 inhibitor prior to hospital admission due to COVID-19 was associated with improved clinical outcomes. Using crude analyses and propensity score matching (on age, sex and BMI), 28 patients using a DPP-4 inhibitor were identified and compared to non-users. Results No differences were found in the primary outcome mortality (matched-analysis = odds-ratio: 0,94 [95% confidence interval: 0,69 – 1,28], p-value: 0,689) or any of the secondary outcomes (ICU admission, invasive ventilation, thrombotic events or infectious complications). Additional analyses comparing users of DPP-4 inhibitors with subgroups of non-users (subgroup 1: users of metformin and sulphonylurea; subgroup 2: users of any insulin combination), allowing to correct for diabetes severity, did not yield different results. Conclusions We conclude that outpatient use of a DPP-4 inhibitor does not affect the clinical outcomes of patients with type 2 diabetes who are hospitalized because of COVID-19 infection.

An alcohol-free beer enriched with isomaltulose and a resistant dextrin modulates gut microbiome in subjects with type 2 diabetes mellitus and overweight or obesity: a pilot study

2021 ◽  
Author(s):  
Rocío Mateo-Gallego ◽  
Isabel Moreno-Indias ◽  
Ana M. Bea ◽  
Lidia Sánchez-Alcoholado ◽  
Antonio J. Fumanal ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Pilot Study ◽  
Gut Microbiota ◽  
Gut Microbiome ◽  
Low Doses ◽  
Resistant Dextrin ◽  
Overweight Or Obesity

An alcohol-free beer including the substitution of regular carbohydrates for low doses of isomaltulose and maltodextrin within meals significantly impacts gut microbiota in diabetic subjects with overweight or obesity.

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