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Unlocking Potential: Personalized Lifestyle Therapy for Type 2 Diabetes Through a Predictive Algorithm-Driven Digital Therapeutic.

作者信息

Kannenberg Swantje, Voggel Jenny, Thieme Nils, Witt Oliver, Pethahn Kim Lina, Schütt Morten, Sina Christian, Freckmann Guido, Schröder Torsten

机构信息

Diabetes Plus, Diabetology Medical Practice, Lübeck, Germany.

Research & Development, Perfood GmbH, Lübeck, Germany.

出版信息

J Diabetes Sci Technol. 2024 Jul 30:19322968241266821. doi: 10.1177/19322968241266821.


DOI:10.1177/19322968241266821
PMID:39080863
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11571624/
Abstract

BACKGROUND: We present a digital therapeutic (DTx) using continuous glucose monitoring (CGM) and an advanced artificial intelligence (AI) algorithm to digitally personalize lifestyle interventions for people with type 2 diabetes (T2D). METHOD: A study of 118 participants with non-insulin-treated T2D (HbA ≥ 6.5%) who were already receiving standard care and had a mean baseline (BL) HbA of 7.46% (0.93) used the DTx for three months to evaluate clinical endpoints, such as HbA, body weight, quality of life and app usage, for a pre-post comparison. The study also included an assessment of initial long-term data from a second use of the DTx. RESULTS: After three months of using the DTx, there was an improvement of 0.67% HbA in the complete cohort and -1.08% HbA in patients with poorly controlled diabetes (BL-HbA ≥ 7.0%) compared with standard of care ( < .001). The number of patients within the therapeutic target range (< 7.0%) increased from 38% to 60%, and 33% were on the way to remission (< 6.5%). Patients who used the DTx a second time experienced a reduction of -0.76% in their HbA levels and a mean weight loss of -6.84 kg after six months ( < .001) compared with BL. CONCLUSIONS: These results indicate that the DTx has clinically relevant effects on glycemic control and weight reduction for patients with both well and poorly controlled diabetes, whether through single or repeated usage. It is a noteworthy improvement in T2D management, offering a non-pharmacological, fully digital solution that integrates biofeedback through CGM and an advanced AI algorithm.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/11571624/f57cb37a669b/10.1177_19322968241266821-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/11571624/4207588e71a5/10.1177_19322968241266821-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/11571624/f57cb37a669b/10.1177_19322968241266821-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/11571624/4207588e71a5/10.1177_19322968241266821-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdf7/11571624/f57cb37a669b/10.1177_19322968241266821-fig2.jpg

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Unlocking Potential: Personalized Lifestyle Therapy for Type 2 Diabetes Through a Predictive Algorithm-Driven Digital Therapeutic.

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引用本文的文献

[1]
Integrated Medical and Digital Approaches to Enhance Post-Bariatric Surgery Care: A Prototype-Based Evaluation of the NutriMonitCare System in a Controlled Setting.

Nutrients. 2025-8-2

[2]
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[3]
Future horizons in diabetes: integrating AI and personalized care.

Front Endocrinol (Lausanne). 2025-3-27

本文引用的文献

[1]
The three-year evolution of Germany's Digital Therapeutics reimbursement program and its path forward.

NPJ Digit Med. 2024-5-24

[2]
Machine Learning Models for Blood Glucose Level Prediction in Patients With Diabetes Mellitus: Systematic Review and Network Meta-Analysis.

JMIR Med Inform. 2023-11-20

[3]
Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities.

IEEE Rev Biomed Eng. 2024

[4]
Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021.

Lancet. 2023-7-15

[5]
Management of Hyperglycemia in Type 2 Diabetes, 2022. A Consensus Report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

Diabetes Care. 2022-11-1

[6]
6. Glycemic Targets: Standards of Medical Care in Diabetes-2022.

Diabetes Care. 2022-1-1

[7]
Changing face of healthcare: digital therapeutics in the management of diabetes.

Curr Med Res Opin. 2021-12

[8]
Consensus Report: Definition and Interpretation of Remission in Type 2 Diabetes.

Diabetes Care. 2021-8-30

[9]
Data-based algorithms and models using diabetics real data for blood glucose and hypoglycaemia prediction - A systematic literature review.

Artif Intell Med. 2021-8

[10]
Low health literacy is associated with higher risk of type 2 diabetes: a cross-sectional study in Germany.

BMC Public Health. 2021-3-16

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