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NCT07011108: FitML-O

Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity

Active, enrolled Last updated 8 June 2025
What this trial tests

trial testing No intervention (observational study) in Obesity; Overweight in 1,700 participants. Participants enrolled and being followed up; not accepting new ones.

Timeline
30 May 2025
Primary endpoint
10 December 2027
24 December 2027

Quick facts

Lead sponsorSykehuset i Vestfold HF
StatusActive, enrolled
Study typeOBSERVATIONAL
Enrollment1,700
Start date30 May 2025
Primary completion10 December 2027
Estimated completion24 December 2027

Drugs / interventions tested

Conditions studied

Sponsor

Sykehuset i Vestfold HF — full company profile →

Who can join

Adults 18 to 100, any sex, with Obesity; Overweight. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The primary aim of this study is to develop an obesity-specific machine learning (ML) model capable of accurately estimating VO2max, a key indicator of cardiovascular fitness.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity: Protocol for a Retrospective and Prospective Multicenter Cohort Study.
    Berge J, Nunavath V, Asbjørnsen RA, Borgeraas H, et al · · 2026 · PMID 41773679 · DOI 10.2196/85069

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Other Sykehuset i Vestfold HF trials

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Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT07011108.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing