Characterization of individuals achieving type 2 diabetes remission in real-world settings: bridging clinical evidence and patient experiences
Bibliographic record
Abstract
The objectives of the study were to (1) describe characteristics and lifestyle factors of individuals who have achieved type 2 diabetes (T2D) remission (sub-diabetes glucose levels without glucose-lowering medications for ≥3 months) through changes to diet and exercise behaviour in real-world settings; (2) investigate continuous glucose monitoring (CGM) profiles of these individuals and explore how dietary pattern may influence glucose regulation metrics. This cross-sectional study recruited individuals living with T2D who achieved remission via changes to diet or exercise behaviours. Various questionnaires were used to assess overall health and participants wore a blinded CGM for 14 days to assess glucose profiles and filled out 3-day food records. A total of 21 adults (57 ± 8 years of age) who were recently diagnosed with T2D (4 ± 3 years) with a A1c of 5.7 ± 0.4% volunteered to participate. Participants achieved remission through various means (e.g., combination of diet and exercxise/physical activity) and self-reported following different diets, including 52% following a low-carbohydrate or very low carbohydrate diet, 14% following a “ketovore/carnivore” diet, 10% using a meal replacement diet, 5% following Weight Watcher’s diet, and 19% no defined dietary pattern. The 24 h average CGM glucose value was 5.0 [4.8–5.6] mmol/L (median [IQR]) with 92 [85–97]% of time spent in range (between 4.0 and 9.9 mmol/L). The 24 h average CGM glucose ( r = 0.692; P = 0.001) and A1c ( r = 0.470; P = 0.049) were correlated with the daily percentage of energy intake from carbohydrate. Remission of T2D appears achievable through various means, including adoption of different dietary approaches and a more active lifestyle underpinning the importance of a patient-centred care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".