Machine Learning for Estimating Cardiorespiratory Fitness... | NCT07011108

Studies
Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity

NCT07011108

Sponsor

Sykehuset i Vestfold HF

Status

Active, not recruiting

Last Update Posted

Jun 8, 2025Actual

Enrollment

1,700Estimated

Phase

Not provided

Conditions

Obesity; Overweight

Interventions

No intervention (observational study)

Countries

Not provided

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

May 2025

Overall Recruitment Status or Expanded Access Status

Active, not recruiting

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

May 30, 2025Actual

Primary Completion Date

Dec 10, 2027Estimated

Completion Date

Dec 24, 2027Estimated

First Submitted Date

May 30, 2025

First Submission Date that Met QC Criteria

May 30, 2025

First Posted Date

Jun 8, 2025Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

May 30, 2025

Last Update Posted Date

Jun 8, 2025Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

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.

Detailed Description

Not provided

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Yes

Target Follow-Up Duration

1 Day

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

1,700Estimated

Name	Type	Description	Arm Group Labels	Other Names
No intervention (observational study)	Other	no intervention

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
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	The project will be completed in 2027

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

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

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

100 Years

Standard Ages

AdultOlder Adult

Study Population

Patients with obesity from Norway

Sampling Method

Non-Probability Sample

IPD Sharing Statement Module

Plan to Share IPD

Description

IPD will not be shared due to confidentiality concerns, lack of participant consent for data sharing, or institutional policy restrictions.

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D009765	Obesity
D050177	Overweight

Ancestor Terms

ID	Term
D044343	Overnutrition
D009748	Nutrition Disorders
D009750	Nutritional and Metabolic Diseases
D001835	Body Weight

Browse Leaves

Not provided

Browse Branches

Not provided

Intervention Browse Module

MeSH Terms

ID	Term
D019370	Observation

Ancestor Terms

ID	Term
D008722	Methods
D008919	Investigative Techniques

Browse Leaves

Not provided

Browse Branches

Not provided