Observational studyScientific reports2024
One-year outcomes of a digital twin intervention for type 2 diabetes: a retrospective real-world study.
Observational study in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Twins and Health Care: an Umbrella Review.Journal of medical systems · 2025Pooled it
- A digital twin-enhanced decision support system improves time-in-range in type 1 diabetes: a randomized clinical trial.Scientific reports · 2025Trial
- From metabolites to membrane vesicles: Unifying gut microbial signals in obesity, t2dm, and MASLD.World journal of microbiology & biotechnology · 2026Review
- Hybrid Digital Twin Framework for Personalized Diabetes Management Using Mathematical Modelling and Machine Learning.Diagnostics (Basel, Switzerland) · 2026Article
- Physiological Data Integration and Predictive Modeling in Intensive Care.Life (Basel, Switzerland) · 2026Review
- Article
- App-Based Digital Therapeutics Integrating Continuous Glucose Monitoring for Glycemic Control in Type 2 Diabetes: Prospective Observational Cohort Study.JMIR diabetes · 2026Article
- Navigating the AI era in dietetics: a qualitative analysis of professional identity, ethical concerns, and future projections in Türkiye.BMC health services research · 2026Article
- The Programmable Microbiome: Integrative AI and Multi-Omics Frameworks for Precision T2DM Management.Biology · 2026Review
- Digital Twin Applications in Diabetes Management: Scoping Review.JMIR diabetes · 2026Review
- Digital Health Solutions for Type 2 Diabetes and Prediabetes: Systematic Review of Engagement Barriers, Facilitators, and Outcomes.JMIR diabetes · 2026Review
- A multimodal, risk-stratified framework for AI-driven early risk prediction and personalised prevention in obesity.Frontiers in artificial intelligence · 2026Article
- Cross-fusion of digital twins and artificial intelligence in diabetes: from mechanistic elucidation to full-cycle precision management.Frontiers in endocrinology · 2026Review
- Machine learning and engagement insights for personalized blood glucose management.Frontiers in digital health · 2026Article
- Multi-scale digital twins for personalized medicine.Frontiers in digital health · 2026Review
- A digital twin framework for predicting and simulating type 2 diabetes onset using retrospective lifestyle data.Frontiers in digital health · 2026Article
- Clinical efficacy, safety, and predictors of treatment response to SGLT2 versus DPP-4 inhibitors in type 2 diabetes: a retrospective comparative study.Frontiers in endocrinology · 2026Article
- Therapeutic Patient Education in the Digital Era: Opportunities and Challenges in Diabetes Care.Mayo Clinic proceedings. Digital health · 2025Review
- A Step-by-Step Workflow for Performing In Silico Clinical Trials With Nonlinear Mixed Effects Models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Cardiometabolic risk reduction with digital twinning in patients with type 2 diabetes.Cardiovascular diabetology. Endocrinology reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This retrospective observational study, building on prior research that demonstrated the efficacy of the Digital Twin (DT) Precision Treatment Program over shorter follow-up periods, aimed to examine glycemic control and reduced anti-diabetic medication use after one-year in a DT commercial program. T2D patients enrolled had adequate hepatic and renal function and no recent cardiovascular events. DT intervention powered by artificial intelligence utilizes precision nutrition, activity, sleep, and deep breathing exercises. Outcome measures included HbA1c change, medication reduction, anthropometrics, insulin markers, and continuous glucose monitoring (CGM) metrics. Of 1985 enrollees, 132 (6.6%) were lost to follow-up, leaving 1853 participants who completed one-year. At one-year, participants exhibited significant reductions in HbA1c [mean change: -1.8% (SD 1.7%), p < 0.001], with 1650 (89.0%) achieving HbA1c below 7%. At baseline, participants were on mean 1.9 (SD 1.4) anti-diabetic medications, which decreased to 0.5 (SD 0.7) at one-year [change: -1.5 (SD 1.3), p < 0.001]. Significant reductions in weight [mean change: -4.8 kg (SD 6.0 kg), p < 0.001], insulin resistance [HOMA2-IR: -0.1 (SD 1.2), p < 0.001], and improvements in β-cell function [HOMA2-B: +21.6 (SD 47.7), p < 0.001] were observed, along with better CGM metrics. These findings suggest that DT intervention could play a vital role in the future of T2D care.
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Registered trials
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 Socratic graph.