Effect of Tirzepatide on the Risk of Developing Type 2 Diabetes Mellitus Among the People Living With Obesity or Overweight: A Systematic Review
Bibliographic record
Abstract
Tirzepatide provides superior efficacy in weight reduction and metabolic control compared to existing therapies. The present systematic review assessed the effect of Tirzepatide on the risk of developing type 2 diabetes mellitus (T2DM) among people living with obesity or overweight. Six major databases [MEDLINE (PubMed), ClinicalTrials.gov, EMBASE, Scopus, Web of Science and Cochrane Library] were searched for potential studies published till 10 July 2025. Two-stage dual screening with third-person adjudication was adopted for screening of studies. PROSPERO ID: CRD42024614466. RoB 2.0 and the Newcastle-Ottawa Scale were used to assess the quality of randomised controlled trials (RCTs) and cohort studies, respectively. Database search yielded 2601 studies, among which three studies were eligible (one RCT and two cohort studies) for systematic review. The hazard ratio (HR) for the new-onset diabetes at 12 months following the Tirzepatide intake was significantly lower than that of the Semaglutide group of patients (HR = 0.73, p < 0.001 [95% CI: 0.58-0.92]). The risk of the new-onset diabetes for 176 weeks (HR = 0.07, p < 0.001 [95% CI: < 0.01-0.1]) and 193 weeks (HR = 0.12, p < 0.001 [95% CI: 0.1-0.2]) following the Tirzepatide intake was significantly lower than that of the placebo group of patients. Tirzepatide might have significant efficacy in the prevention of T2DM in patients with obesity or overweight.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".