RESUMEN
Aim: The SCORE2 algorithm is recommended to estimate risk of cardiovascular disease (CVD). Coronary artery calcification (CAC) score is expensive but improves the risk prediction. This study aims to determine and compare the additive value of CAC-score and 19 biomarkers in risk prediction. Methods: Traditional cardiovascular (CV) risk factors, CAC-score, and a wide range of biomarkers (including lipids, calcium-phosphate metabolism, troponin, inflammation, kidney function and ankle brachial index (ABI)) were collected from 1211 randomly selected middle-aged men and women in this multicenter prospective cohort in 2009-2010. 10-year follow-up data on CV-events were obtained via the Danish Health Registries. CV-event was defined as stroke, myocardial infarction, hospitalization for heart failure, coronary artery revascularization or death from CVD. The association between SCORE2, CAC-score, biomarkers, and CV-events was assessed using cox proportional hazard rates (HR) and compared using AUC-calculation of ROC-curves. Finally, net reclassification improvement (NRI) was calculated. Results: 92 participants had CV-events. Adjusted for risk factors, CAC-score was significantly associated with events (adjusted HR 1.9 (95%CI:1.1; 3.3), 3.6 (95%CI:1.9; 6.8), and 5. (95%CI:2.6; 10.3) for CAC-score 1-99, CAC-score 100-399 and CAC-score ≥400, respectively. HR for the highest quartile of CRP was 2.3 (95%CI:1.2; 4.5), while none of the remaining biomarkers improved HR. Adjusted for SCORE2, the CAC-score improved AUC (AUCCAC: 0.72, AUCSCORE2: 0.67, p<0.01). A combination of selected biomarkers (total cholesterol, low-density lipoprotein, phosphate, troponin, CRP, and creatinine) borderline improved AUC (AUCBiomarkers + SCORE2: 0.71, AUCSCORE2: 0.67, p=0.06). NRI for CAC score was 63 % (p<0.0001). Conclusion: CAC-score improved prediction of CV-events, however the selected biomarkers did not.
RESUMEN
BACKGROUND: Due to its location very close to the bundle of His, mitral annulus calcification (MAC) might be associated with the development of atrioventricular (AV) conduction disturbances. This study assessed the association between MAC and AV conduction disturbances identified by cardiac implantable electronic device (CIED) use and electrocardiographic parameters. The association between MAC and traditional cardiovascular risk factors was also assessed. METHODS: This cross-sectional study analyzed 14,771 participants, predominantly men aged 60-75 years, from the population-based Danish Cardiovascular Screening trial. Traditional cardiovascular risk factors were obtained. Using cardiac non-contrast computed tomography imaging, MAC scores were measured using the Agatston method and divided into absent versus present and score categories. CIED implantation data were obtained from the Danish Pacemaker and Implantable Cardioverter Defibrillator Register. A 12-lead electrocardiogram was available for 2,107 participants. Associations between MAC scores and AV conduction disturbances were assessed using multivariate regression analyses. RESULTS: MAC was present in 22.4% of the study subjects. Participants with pacemakers for an AV conduction disturbance had significantly higher MAC scores (odds ratio [OR], 1.11; 95% confidence interval [CI], 1.01-1.23) than participants without a CIED, whereas participants with a CIED for other reasons did not. Prolonged QRS-interval was significantly associated with the presence of MAC (OR, 1.45; 95% CI, 1.04-2.04), whereas prolonged PQ-interval was not. Female sex and most traditional cardiovascular risk factors were significantly associated with high MAC scores. CONCLUSIONS: MAC was associated with AV conduction disturbances, which could improve our understanding of the development of AV conduction disturbances.