<scp>IMpact</scp> of flash glucose Monitoring in <scp>pEople</scp> with type 2 Diabetes Inadequately controlled with non‐insulin Antihyperglycaemic <scp>ThErapy</scp> ( <scp>IMMEDIATE</scp> ): A randomized controlled trial
Bibliographic record
Abstract
AIM: To examine the efficacy and patient satisfaction of intermittently scanned continuous glucose monitoring (isCGM) in adults using non-insulin therapies for the management of type 2 diabetes. MATERIALS AND METHODS: The IMMEDIATE study was a multisite, open label, randomized controlled trial with follow-up at 16 weeks. Adults with type 2 diabetes using at least one non-insulin therapy, with an HbA1c of 7.5% or higher (≥ 58 mmol/mol), were randomized 1:1 to receive an isCGM device plus diabetes self-management education (isCGM + DSME) or DSME alone. Enrolment occurred from 8 September 2020 to 24 December 2021. The primary outcome was percentage mean time in range (TIR), in the final 2-week period, measured via blinded CGM. RESULTS: One hundred and sixteen participants were randomized (mean age, 58 years; diabetes duration, 10 years; mean HbA1c, 8.6% [70 mmol/mol]). At 16 weeks of follow-up, the isCGM and DSME arm had a significantly greater mean TIR by 9.9% (2.4 hours) (95% CI, -17.3% to -2.5%; P < .01), significantly less time above range by 8.1% (1.9 hours) (95% CI, 0.5% to 15.7%; P = .037), and a greater reduction in mean HbA1c by 0.3% (3 mmol/mol) (95% CI, 0% to 0.7%; P = .048) versus the DSME arm. Time below range was low and not significantly different between groups and hypoglycaemic events were few in both groups. Glucose monitoring satisfaction was higher among isCGM users (adjusted difference -0.5 [95% CI, -0.7 to -0.3], P < .01). CONCLUSIONS: The IMMEDIATE study has shown that among non-insulin-treated individuals with type 2 diabetes, use of isCGM is associated with an improvement in glycaemic outcomes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".