The Finnish Cardiovascular Study (FINCAVAS): characterising patients with high risk of cardiovascular morbidity and mortality

• Published in: BMC cardiovascular disorders Vol. 6; no. 1; p. 9
• Main Authors: Nieminen, Tuomo, Lehtinen, Rami, Viik, Jari, Lehtimäki, Terho, Niemelä, Kari, Nikus, Kjell, Niemi, Mari, Kallio, Janne, Kööbi, Tiit, Turjanmaa, Väinö, Kähönen, Mika
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 03.03.2006; BioMed Central; BMC
• Subjects: Cardiovascular Diseases - etiology; Cardiovascular Diseases - genetics; Cardiovascular Diseases - mortality; Electrocardiography; Exercise Test; Female; Humans; Male; Polymorphism, Genetic; Risk Factors; Study Protocol
• ISSN: 1471-2261; 1471-2261
• DOI: 10.1186/1471-2261-6-9

The purpose of the Finnish Cardiovascular Study (FINCAVAS) is to construct a risk profile--using genetic, haemodynamic and electrocardiographic (ECG) markers--of individuals at high risk of cardiovascular diseases, events and deaths. All patients scheduled for an exercise stress test at Tampere University Hospital and willing to participate have been and will be recruited between October 2001 and December 2007. The final number of participants is estimated to reach 5,000. Technically successful data on exercise tests using a bicycle ergometer have been collected of 2,212 patients (1,400 men and 812 women) by the end of 2004. In addition to repeated measurement of heart rate and blood pressure, digital high-resolution ECG at 500 Hz is recorded continuously during the entire exercise test, including the resting and recovery phases. About 20% of the patients are examined with coronary angiography. Genetic variations known or suspected to alter cardiovascular function or pathophysiology are analysed to elucidate the effects and interactions of these candidate genes, exercise and commonly used cardiovascular medications. FINCAVAS compiles an extensive set of data on patient history, genetic variation, cardiovascular parameters, ECG markers as well as follow-up data on clinical events, hospitalisations and deaths. The data enables the development of new diagnostic and prognostic tools as well as assessments of the importance of existing markers.