Evidence map›Paper›PMID 42395096›Full record

ArticleAmerican journal of preventive cardiology2026

Design and rationale of the my heart counts cardiovascular health study: a large-scale, fully digital biobank, and randomized trial of large language model-driven coaching of physical activity.

Paul Schmiedmayer, Anders Johnson, Narayan Schuetz, Lukas Kollmer, Paul Goldschmidt, Juan Delgado-SanMartin, Kelly W Zhang, Sriya D Mantena, Alexander Tolas, Samuel Montalvo and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in American journal of preventive cardiology, 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

5 · Who and what money

Authors and funding

18 authors.

Paul SchmiedmayerStanford Mussallem Center for Biodesign, Stanford University, Stanford, CA, USA.
Anders JohnsonDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Narayan SchuetzDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Lukas KollmerStanford Mussallem Center for Biodesign, Stanford University, Stanford, CA, USA.
Paul GoldschmidtStanford Mussallem Center for Biodesign, Stanford University, Stanford, CA, USA.
Juan Delgado-SanMartinNational Heart and Lung Institute, Imperial College London, London, UK.
Kelly W ZhangDivision of Statistics, Department of Mathematics, Imperial College London, London, UK.
Sriya D MantenaDepartment of Computer Science, Stanford University, Stanford, CA, USA.
Alexander TolasDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Samuel MontalvoDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Mariana Ramirez-PosadaCenter for Digital Health, Stanford University, Stanford, CA, USA.
Jack W O'SullivanDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Marily OppezzoWu Tsai Human Performance Alliance, Stanford University, Stanford, CA, USA.
Abby C KingStanford Prevention Research Center, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Fatima RodriguezDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Euan AshleyDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Allan LawrieNational Heart and Lung Institute, Imperial College London, London, UK.
Daniel Seung KimDivision of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cardiovascular disease remains the leading cause of global morbidity and mortality. The original Methods: The next-generation Planned analysis: The primary endpoint of the randomized crossover trial is change in daily step count between LLM-driven and generic text-based intervention arms, analyzed using mixed-effects models. Secondary endpoints include change in mean active minutes and calorie burn over each intervention week. Other exploratory analyses include the changes in submaximal (6-minute walk test) and maximal (Cooper 12-minute run test) cardiorespiratory fitness, changes to sensor-derived biomarkers (e.g., sleep quality, resting heart rate, and heart rate variability), and association of sensor-derived biomarkers with EHR-confirmed clinical outcomes. Conclusions: By utilizing autonomous, LLM-driven coaching, modular software design, and cross-platform accessibility, our smartphone application-based study will provide a scalable model for inclusive and decentralized preventive care of patients with cardiovascular disease. Trial Status: Recruitment commenced in March 2026 and is ongoing.

Indexed as

Behavioral interventionDigital healthLarge language modelsmHealthOpen-source softwarePhysical activityRandomized controlled trialSmartphone applications

Identifiers

PMID42395096
PMCPMC13325983

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.