Effects of Incretin-based Therapies on Weight-related Indicators among Patients with Type 2 Diabetes: A Network Meta-analysis.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of incretin-based therapies on body weight as the primary outcome, as well as on body mass index (BMI) and waist circumference (WC) as secondary outcomes. METHODS: Databases including Medline, Embase, the Cochrane Library, and clinicaltrials.gov (www.clinicaltrials.gov) were searched for randomized controlled trials (RCTs). Standard pairwise meta-analysis and network meta-analysis (NMA) were both carried out. The risk of bias (ROB) tool recommended by the Cochrane handbook was used to assess the quality of studies. Subgroup analysis, sensitivity analysis, meta-regression, and quality evaluation based on the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) were also performed. RESULTS: : -1.69, -0.86), respectively. CONCLUSION: GLP-1 RAs were more effective than DPP-4Is in lowering the three indicators. Overall, the effects of GLP-1 RAs on weight, BMI, and WC were favorable.
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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 | 0.022 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.057 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".