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
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.