Validation of an Algorithm to Predict the Ventilatory Threshold

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

COMPLETED

Total Enrollment

3000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-03-01

Study Completion Date

2021-04-01

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

The aim of the current study was to develop an algorithm which has the ability to accurately predict the first and second ventilatory threshold and in cardiovascular disease patients and to guide in proper exercise intensity determination. This would then help, at least in part, to overcome the lack of access to metabolic carts or cardiopulmonary exercise test, and/or methodological difficulties with ventilatory threshold determination in these patients.

Related Clinical Trials

Explore similar clinical trials based on study characteristics and research focus.

Assessing Force-velocity Profile: an Innovative Approach to Optimize Cardiac Rehabilitation in Coronary Patients

NCT04102410

Acute Coronary Syndrome

COMPLETED NA

Activity at Pulse Pressure Above an Individual Threshold in Patients With LVAD

NCT02304965

Heart Failure

COMPLETED NA

Optimization of Interval Exercise Based-intensity on Ventilatory Anaerobic Threshold in Coronary Artery Disease

NCT02313831

Coronary Artery Disease Cardiovascular Risk Factors

UNKNOWN NA

Cardiac Rehabilitation and Noninvasive Ventilation in Heart Failure

NCT02811146

Heart Failure

COMPLETED NA

Is Threshold-based Training Superior in Cardiac Rehabilitation

NCT04114929

Cardiac Rehabilitation

WITHDRAWN NA

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

Design

This study is composed out of two sub studies: 1. Generation/creation of VT prediction algorithm, and 2. Validation of this algorithm in independent laboratories.

Sub study 1: Generation/creation of VT prediction algorithm

From April 2015 up to July 2020, data from CVD (risk) patients (e.g. obesity, diabetes, coronary artery disease or heart failure) were collected from in light of research studies. All participants signed an informed consent explaining the nature and risks of CPET, and allowing us to use anonymized data for the analyses of their CPET at entry of cardiovascular rehabilitation or an exercise intervention. These data have been published in previous publications.

Sub study 2: Validation of the algorithm in independent laboratories

From April 2015 up to July 2020, data from CVD (risk) patients (e.g. obesity, diabetes, coronary artery disease or heart failure) were collected in light of research studies. All participants signed an informed consent (approved by the ethics committees of the local hospitals or research laboratories) explaining the nature and risks of CPET, and allowing us to use anonymized data for the analyses of their CPET at entry of CR or an exercise intervention. These data have been published in previous publications