A bedside-to-outside model of human nutrition research.

Aaron Hengist, Stephanie T Chung, Valerie L Darcey, Kong Chen, Juen Guo, Gary Frost, Javier T Gonzalez, Kevin D Hall

Abstract readReview

In one paragraph

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

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

8 authors.

Aaron HengistDiabetes, Endocrinology, & Obesity Branch, NIDDK, National Institutes of Health, Bethesda, MD, USA. Electronic address: aaron.hengist@nih.gov.

Stephanie T ChungDiabetes, Endocrinology, & Obesity Branch, NIDDK, National Institutes of Health, Bethesda, MD, USA.

Valerie L DarceyDiabetes, Endocrinology, & Obesity Branch, NIDDK, National Institutes of Health, Bethesda, MD, USA.

Kong ChenDiabetes, Endocrinology, & Obesity Branch, NIDDK, National Institutes of Health, Bethesda, MD, USA.

Juen GuoDiabetes, Endocrinology, & Obesity Branch, NIDDK, National Institutes of Health, Bethesda, MD, USA.

Gary FrostDepartment of Metabolism, Digestion and Reproduction, Imperial College, London, London, UK.

Javier T GonzalezCentre for Nutrition, Exercise and Metabolism, Department for Health, University of Bath, Bath, UK.

Kevin D HallKensington, MD, USA.

Funding

Intramural NIH HHS Z99 DK999999

6 · The paper itself

Abstract

One of the fundamental challenges with human nutrition research is the difficulty of knowing what people actually eat. Asking people to live in the laboratory enables precise control and measurement of food intake, but the environment does not reflect real-world conditions. Here, we present a bedside-to-outside model, which aims to address this gap by combining controlled feeding studies (prioritizing efficacy) with free-living intervention studies (incorporating effectiveness) within the same cohort. This approach will enable translation of the efficacy and effectiveness of dietary interventions with causal inference within the same cohort, offering novel insights into the real-world impact of controlled dietary interventions.

Indexed as

clinical trialsdieteffectivenessefficacyinterventionnutritionrandomization

Identifiers

PMID42580343

DOI10.1016/j.cmet.2026.07.010

PMCPMC13463385

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.