Pre‐prandial vs. post‐prandial capillary glucose measurements as targets for repaglinide dose titration in people with diet‐treated or metformin‐treated Type 2 diabetes: a randomized controlled clinical trial
Bibliographic record
Abstract
OBJECTIVE: Repaglinide is an oral anti-diabetic agent that has a short duration of action, and is suitable for preventing post-prandial rises in glucose levels. Targeting post-prandial glucose levels may lead to lower HbA(1c) levels and rates of hypoglycaemia than targeting pre-prandial glucose levels. RESEARCH DESIGN AND METHODS: In 42 centres, 193 drug-naive (n = 122) or metformin-treated (n = 71) individuals with Type 2 diabetes were randomly allocated to a 40-day period of repaglinide dose-titration (starting at 0.5 mg three times daily) based on either self-measured pre-prandial or post-prandial glucose levels. They were followed for a further 12 weeks and HbA(1c) and hypoglycaemia rates were recorded. RESULTS: Repaglinide reduced HbA(1c) by 1.25 and 1.07% in the post-prandial and pre-prandial groups, respectively (P for difference = 0.6), and achieved target glucose levels in 80.7 and 66.7%, respectively (P = 0.16). The effect of titration strategy differed by baseline drug therapy, and was more effective in the metformin-treated individuals who experienced a HbA(1c) fall of 0.6 vs. 1.10% with pre-prandial vs. post-prandial titration (P for metformin-allocated group interaction = 0.043). The rate of hypoglycaemia did not differ by group. CONCLUSIONS: In drug-naive individuals with Type 2 diabetes, similar HbA(1c) levels are achieved with repaglinide when dosing is adjusted according to either post-prandial or pre-prandial levels. Conversely, in metformin-treated individuals, repaglinide dosing according to post-prandial levels may lead to better glycaemic control than dosing according to pre-prandial levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".