European journal of preventive cardiology最新文献

Aims: Infections have been associated with acute myocardial infarction (AMI), but differences in risk between infection types and age groups are unclear. This study aims to investigate whether infections are associated with subsequent AMI and whether the risk differs across infection sites and age groups.

Methods: Nationwide registers were used to include 702596 adults hospitalized between 1987-2018 with either; pneumonia (n=344319), urinary tract infection (UTI) (n=270101), soft tissue/bone infection (n=66718), central nervous system infection (CNS) (n=17025), or endocarditis (n=4433). Patients were sex- and age-matched with two unexposed controls. Outcome was first-time AMI within ten years. A time-dependent cox proportional hazards model with cut-offs at 30 and 90 days was used for calculating adjusted hazard ratios (HR).

Results: Pneumonia, UTI, and soft tissue/bone infection were associated with increased relative rates of AMI compared to matched, unexposed controls. Highest relative rates were found within the first 0-30 days post-exposure; Pneumonia: HR 3.39 (95% CI 3.15-3.65), UTI: HR 2.44 (95% CI 2.21-2.70), Soft tissue/bone infection: HR 1.84 (95% CI 1.45-2.33). Relative rates decreased over time but remained significantly elevated throughout the follow-up period and was increased in all age groups. No association was found for CNS infection and for endocarditis only at 31-90 days, HR 2.28 (95% CI 1.20-4.33).

Conclusion: Acute infections are associated with increased relative rates of AMI across different infection sites and age groups with higher relative rates found for pneumonia. This indicates that some infections may act as a trigger for AMI with a site and/or pathogen specific risk.

Background: Although prior observational studies have suggested that patients with non-alcohol fatty liver disease (NAFLD) may have a higher risk of coronary artery calcification (CAC), these findings remain controversial. This study aimed to explore the causal association between NAFLD and CAC at genetic level by two-sample Mendelian randomization (MR) analysis.

Method: Utilizing summary-level data from multiple large-scale genome-wide association studies (GWAS) in European populations, a two-sample MR analysis was initially conducted to explore the potential causal association between NAFLD and CAC. The results of the MR analysis were pooled through random-effect meta-analysis. The inverse variance weighting (IVW) method served as the primary approach for MR analysis. Additionally, the weighted median, MR-Egger and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods was applied for sensitivity analysis. Summary-level data on liver fatty content was utilized for validation analysis, while summary-level data on cirrhosis served as positive control, further ensuring the validity and robustness of our findings. Reverse MR analysis was performed to assess the association between CAC and NAFLD, employing instrument variables derived from CAC.

Results: The MR analysis indicated that genetically predicted NAFLD had no effects on the risk of CAC (Beta: 0.01, 95% CI: -0.02 to 0.03, P = 0.74). Likewise, the reverse MR analysis found no significant genetic association between CAC and NAFLD (OR: 1.00, 95% CI: 0.96 to 1.06, P = 0.88). Validation analysis yielded consistent results, showing no significant association between fatty liver content and CAC.

Conclusion: Our two-sample MR analysis did not support that there is a causal association between NAFLD and CAC at genetic level. The association between NAFLD and CAC reported in some previous observational studies may rely on NAFLD complicated with metabolic disorders, rather than being directly linked to the hepatic steatosis.

Aims: The 2021 European Society of Cardiology prevention guidelines recommend the use of (lifetime) risk prediction models to aid decisions regarding initiation of prevention. We aimed to update and systematically recalibrate the LIFEtime-perspective CardioVascular Disease (LIFE-CVD) model to four European risk regions for the estimation of lifetime CVD risk for apparently healthy individuals.

Methods and results: The updated LIFE-CVD (i.e. LIFE-CVD2) models were derived using individual participant data from 44 cohorts in 13 countries (687 135 individuals without established CVD, 30 939 CVD events in median 10.7 years of follow-up). LIFE-CVD2 uses sex-specific functions to estimate the lifetime risk of fatal and non-fatal CVD events with adjustment for the competing risk of non-CVD death and is systematically recalibrated to four distinct European risk regions. The updated models showed good discrimination in external validation among 1 657 707 individuals (61 311 CVD events) from eight additional European cohorts in seven countries, with a pooled C-index of 0.795 (95% confidence interval 0.767-0.822). Predicted and observed CVD event risks were well calibrated in population-wide electronic health records data in the UK (Clinical Practice Research Datalink) and the Netherlands (Extramural LUMC Academic Network). When using LIFE-CVD2 to estimate potential gain in CVD-free life expectancy from preventive therapy, projections varied by risk region reflecting important regional differences in absolute lifetime risk. For example, a 50-year-old smoking woman with a systolic blood pressure (SBP) of 140 mmHg was estimated to gain 0.9 years in the low-risk region vs. 1.6 years in the very high-risk region from lifelong 10 mmHg SBP reduction. The benefit of smoking cessation for this individual ranged from 3.6 years in the low-risk region to 4.8 years in the very high-risk region.

Conclusion: By taking into account geographical differences in CVD incidence using contemporary representative data sources, the recalibrated LIFE-CVD2 model provides a more accurate tool for the prediction of lifetime risk and CVD-free life expectancy for individuals without previous CVD, facilitating shared decision-making for cardiovascular prevention as recommended by 2021 European guidelines.