Use of basal insulin in the management of adults with type 2 diabetes: An <scp>Asia‐Pacific</scp> evidence‐based clinical practice guideline
Bibliographic record
Abstract
The objective of this study was to provide recommendations regarding effectiveness, safety, optimal starting dose, optimal maintenance dose range, and target fasting plasma glucose of five basal insulins (glargine U-300, degludec U-100, glargine U-100, detemir, and insulin protamine Hagedorn) in insulin-naïve adult patients with type 2 diabetes in the Asia-Pacific region. Based on evidence from a systematic review, we developed an Asia-Pacific clinical practice guideline through comprehensive internal review and external review processes. We set up and used clinical thresholds of trivial, small, moderate, and large effects for different critical and important outcomes in the overall certainty of evidence assessment and balancing the magnitude of intervention effects when making recommendations, following GRADE methods (Grading of Recommendations, Assessment, Development, and Evaluation). The AGREE (Appraisal of Guidelines, Research and Evaluation) and RIGHT (Reporting Items for practice Guidelines in HealThcare) guideline reporting checklists were complied with. After the second-round vote by the working group members, all the recommendations and qualifying statements reached over 75% agreement rates. Among 44 contacted external reviewers, we received 33 clinicians' and one patient's comments. The overall response rate was 77%. To solve the four research questions, we made two strong recommendations, six conditional recommendations, and two qualifying statements. Although the intended users of this guideline focused on clinicians in the Asia-Pacific region, the eligible evidence was based on recent English publications. We believe that the recommendations and the clinical thresholds set up in the guideline can be references for clinicians who take care of patients with type 2 diabetes worldwide.
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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 | 0.052 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".