Evidence map›Paper›PMID 42820241›Full record

ArticleObesity pillars2026

Fat and lean mass changes during incretin-based therapy with structured exercise and nutritional support: A retrospective real-world pilot study.

Meral Kucuk Yetgin, Nana Gletsu-Miller, Robert R Chapman, Eitan Gelber, John Snyder, Donny Gregg, Dustin Nabhan

Abstract read
In one paragraph

Article in Obesity pillars, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Meral Kucuk YetginDepartment of Applied Health Science, School of Public Health - Bloomington, Indiana University, Bloomington, IN, USA.
Nana Gletsu-MillerDepartment of Applied Health Science, School of Public Health - Bloomington, Indiana University, Bloomington, IN, USA.
Robert R ChapmanDepartment of Kinesiology, School of Public Health - Bloomington, Indiana University, Bloomington, IN, USA.
Eitan GelberApeiron Life, Menlo Park, CA, USA.
John SnyderApeiron Life, Menlo Park, CA, USA.
Donny GreggApeiron Life, Menlo Park, CA, USA.
Dustin NabhanApeiron Life, Menlo Park, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Incretin-based therapies are highly effective for weight reduction, but changes in lean mass during treatment remain a clinical concern. This study evaluated changes in fat mass and lean mass in individuals receiving structured exercise and nutritional support during incretin-based therapies. Methods: In this single-center retrospective observational chart-review study, 11 adults who underwent 9-12 months of incretin-based therapy and were offered a program providing supervised exercise and individualized nutritional support were analyzed. No control group was included. Treatments included glucagon-like peptide-1 (GLP-1) receptor agonists and glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor co-agonists. Body composition was assessed using dual-energy X-ray absorptiometry (DXA). Data were assessed for parametric assumptions, and pre- and post-intervention comparisons were performed using paired-samples t tests. Results: Significant reductions were observed in body weight (mean change: -4.99 kg [95% CI: -7.65 to -2.34]; p = 0.002) and fat mass (-4.37 kg [95% CI: 6.36 to -2.39]; p < 0.001), corresponding to a mean total weight reduction of 4.71% and a mean fat mass reduction of 11.06% Conclusion: Incretin-based therapy delivered within a structured exercise and nutritional support program was associated with fat-dominant weight reduction without a statistically significant change in lean mass. These findings are hypothesis-generating and warrant confirmation in adequately powered prospective controlled studies.

Indexed as

Body compositionExerciseGlucagon-like peptide-1 receptor agonistLean massNutritional supportObesity

Identifiers

PMID42820241
PMCPMC13626787

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.