Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity

N/AActive Not RecruitingNCT07011108

Sykehuset i Vestfold HF1,700 enrolled

Overview

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.

Study Type

OBSERVATIONAL

Enrollment

1,700

Conditions

Obesity; Overweight

Interventions

No intervention (observational study)OTHER

no intervention

Eligibility

Sex: ALLMin age: 18 YearsMax age: 100 Years

Medical Language ↔ Plain English

Inclusion Criteria: * diagnosed with severe obesity * body mass index (BMI) ≥40.0 kg •m-2, or 35.0-39.9 kg •m-2 with at least one obesity-related comorbidity Exclusion Criteria: * not obese

Outcomes

Primary Outcomes

Machine learning model to estimate vo2max

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

Time frame: The project will be completed in 2027

Data from ClinicalTrials.gov

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