Tirzepatide for the Maintenance of Body Weight Reduction: Rationale, Design, and Baseline Characteristics of <scp>SURMOUNT</scp>‐<scp>MAINTAIN</scp>
Bibliographic record
Abstract
ABSTRACT Objective SURMOUNT‐MAINTAIN aims to evaluate the efficacy and safety of reducing the tirzepatide dose and/or continuing the maximum tolerated dose (MTD) versus placebo in maintaining body weight (BW) reduction achieved with tirzepatide MTD. Methods This Phase 3b, multicenter, randomized, parallel‐arm, double‐blinded, placebo‐controlled, 52‐week clinical trial is in progress comparing treatment with once weekly tirzepatide (5 mg and/or MTD of 15 mg or 10 mg) versus placebo in achieving BW reduction maintenance from the initial 60‐week open‐label weight‐loss period on tirzepatide MTD, in adults with obesity (BMI ≥ 30 kg/m2 or ≥ 27 kg/m2 with ≥ 1 obesity‐related comorbidity, excluding type 2 diabetes). The primary endpoint is percent maintenance of BW reduction achieved during the weight‐loss period at Week 112 among those who reached a BW plateau (i.e., < 5% BW change) between Weeks 48 and 60. Results Participants are mostly female (65%) with a mean ± SD age of 47 ± 13 years, BW 114 ± 27 kg, BMI 40 ± 8 kg/m2, and waist circumference 119 ± 18 cm. Conclusions The SURMOUNT‐MAINTAIN trial will evaluate whether reducing or continuing the tirzepatide dose as a long‐term treatment option may help maintain the reduced BW initially achieved with tirzepatide MTD versus switching to placebo. Combined, this study may provide additional evidence to help tailor patient‐centered strategies for maintenance of BW reduction in adults living with obesity. Trial Registration ClinicalTrials.gov identifier: NCT06047548 image
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".