scholarly journals Traditional risk factors may not explain increased incidence of myocardial infarction in MS

Neurology ◽  
2019 ◽  
Vol 93 (11) ◽  
pp. 518.2-518
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Traditional Risk Factors

P1755Plasma proteomics in healthy individuals predict myocardial infarction

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
R Hoogeveen ◽  
J P Belo Pereira ◽  
V Zampoleri ◽  
M J Bom ◽  
W Koenig ◽  
...  
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Plasma Proteins ◽  
Risk Model ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Traditional Risk Factors

Abstract Background Currently used models to predict cardiovascular event risk have limited value. It has been shown repetitively that the addition of single biomarkers has modest impact. Recently we observed that a model consisting of a larger array of plasma proteins performed very well in predicting the presence of vulnerable plaques in primary prevention patients. However, the validation of this protein panel in predicting cardiovascular outcomes remains to be established. Purpose This study investigated the ability of a 384 preselected protein biomarkers to predict acute myocardial infarction, using state-of-the-art machine learning techniques. Secondly, we compared the performance of this multi-protein risk model to traditional risk engines. Methods We selected 822 subjects from the EPIC-Norfolk prospective cohort study, of whom 411 suffered a myocardial infarction during follow-up (median 15 years) compared to 411 controls who remained event-free (median follow-up 20 years). The 384 proteins were measured using proximity extension assay technology. Machine learning algorithms (random forests) were used for the prediction of acute myocardial infarction (ICD code I21–22). Performance of the model was tested against and on top of traditional risk factors for cardiovascular disease (refit Framingham). All performance measurements were averaged over several stability selection routines. Results Prediction of myocardial infarction using a machine-learning model consisting of 50 plasma proteins resulted in a ROC AUC of 0.74±0.14, in comparison to 0.69±0.17 using traditional risk factors (refit Framingham. Combining the proteins and refit Framingham resulted in a ROC AUC of 0.74±0.15. Focussing on events occurring within 3 years after baseline blood withdrawal, the ROC AUC increased to 0.80±0.09 using 50 plasma proteins, as opposed to 0.67±0.22 using refit Framingham (figure). Combining the protein model with refit Framingham resulted in a ROC AUC of 0.82±0.11 for these events. Diagnostic performance events <3yrs Conclusion High-throughput proteomics outperforms traditional risk factors in prediction of acute myocardial infarction. Prediction of myocardial infarction occurring within 3 years after inclusion showed highest performance. Availability of affordable proteomic approaches and developed machine learning pave the path for clinical implementation of these models in cardiovascular risk prediction. Acknowledgement/Funding This study was funded by an ERA-CVD grant (JTC2017) and EU Horizon 2020 grant (REPROGRAM, 667837)

scholarly journals Traditional Risk Factors and Subclinical Disease Measures as Predictors of First Myocardial Infarction in Older Adults

1999 ◽  
Vol 159 (12) ◽  
pp. 1339 ◽  
Author(s):  
Bruce M. Psaty ◽  
Curt D. Furberg ◽  
Lewis H. Kuller ◽  
Diane E. Bild ◽  
Pentti M. Rautaharju ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Older Adults ◽  
Subclinical Disease ◽  
Traditional Risk Factors ◽  
First Myocardial Infarction

Incident myocardial infarction associated with major types of arthritis in the general population: a systematic review and meta-analysis

2017 ◽  
Vol 76 (8) ◽  
pp. 1396-1404 ◽  
Author(s):  
Orit Schieir ◽  
Cedomir Tosevski ◽  
Richard H Glazier ◽  
Sheilah Hogg-Johnson ◽  
Elizabeth M Badley
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Meta Analysis ◽  
Population Based ◽  
Case Control Studies ◽  
Increased Risk ◽  
Traditional Risk Factors ◽  
Meta Analyses ◽  
Review Criteria ◽  
Age And Sex

ObjectiveTo synthesise, quantify and compare risks for incident myocardial infarction (MI) across five major types of arthritis in population-based studies.MethodsA systematic search was performed in MEDLINE, EMBASE and CINAHL databases with additional manual/hand searches for population-based cohort or case-control studies published in English of French between January 1980 and January 2015 with a measure of effect and variance for associations between incident MI and five major types of arthritis: rheumatoid arthritis (RA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), gout or osteoarthritis (OA), adjusted for at least age and sex. All search screening, data abstraction quality appraisals were performed independently by two reviewers. Where appropriate, random-effects meta-analysis was used to pool results from studies with a minimum of 10 events.ResultsWe identified a total of 4, 285 articles; 27 met review criteria and 25 criteria for meta-analyses. In studies adjusting for age and sex, MI risk was significantly increased in RA (pooled relative risk (RR): 1.69, 95% CI 1.50 to 1.90), gout (pooled RR: 1.47, 95% CI 1.24 to 1.73), PsA (pooled RR: 1.41, 95% CI 1.17 to 1.69), OA (pooled RR: 1.31, 95% CI 1.01 to 1.71) and tended towards increased risk in AS (pooled RR: 1.24, 95% CI 0.93 to 1.65). Traditional risk factors were more prevalent in all types of arthritis. MI risk was attenuated for each type of arthritis in studies adjusting for traditional risk factors and remained significantly increased in RA, PsA and gout.ConclusionsMI risk was consistently increased in multiple types of arthritis in population-based studies, and was partially explained by a higher prevalence of traditional risk factors in all types of arthritis. Findings support more integrated cardiovascular (CV) prevention strategies for arthritis populations that target both reducing inflammation and enhancing management of traditional CV risk factors.

scholarly journals Mediterranean Diet, Traditional Risk Factors, and the Rate of Cardiovascular Complications After Myocardial Infarction

Circulation ◽  
1999 ◽  
Vol 99 (6) ◽  
pp. 779-785 ◽  
Author(s):  
Michel de Lorgeril ◽  
Patricia Salen ◽  
Jean-Louis Martin ◽  
Isabelle Monjaud ◽  
Jacques Delaye ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Mediterranean Diet ◽  
Cardiovascular Complications ◽  
Traditional Risk Factors

scholarly journals Electrocardiographic unrecognized myocardial infarction does not improve prediction of cardiovascular events beyond traditional risk factors. The Tromsø Study

2017 ◽  
Vol 25 (1) ◽  
pp. 78-86 ◽  
Author(s):  
Andrea Milde Øhrn ◽  
Henrik Schirmer ◽  
Inger Njølstad ◽  
Ellisiv B Mathiesen ◽  
Anne E Eggen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Cardiovascular Risk ◽  
General Population ◽  
Cardiovascular Risk Factors ◽  
Cardiovascular Events ◽  
Hazard Ratio ◽  
Risk Of Death ◽  
All Cause Mortality ◽  
Traditional Risk Factors

Background Unrecognized myocardial infarction (MI) is a frequent and intriguing entity associated with a similar risk of death as recognized MI. Previous studies have not fully addressed whether the poor prognosis is explained by traditional cardiovascular risk factors. We investigated whether electrocardiographically detected unrecognized MI was independently associated with cardiovascular events and death and whether it improved prediction for future MI in a general population. Design Prospective cohort study. Methods We studied 5686 women and men without clinically recognized MI at baseline in 2007–2008. We assessed the risk of future MI, stroke and all-cause mortality in persons with unrecognized MI compared with persons with no MI during 31,051 person-years of follow-up. Results In the unadjusted analyses, unrecognized MI was associated with increased risk of future recognized MI (hazard ratio 1.84, 95% confidence interval (CI) 1.15–2.96) and all-cause mortality (hazard ratio 1.78, 95% CI 1.21–2.61), but not stroke (hazard ratio 1.09, 95% CI 0.56–2.17). The associations did not remain significant after adjustment for traditional risk factors (hazard ratio 1.25, 95% CI 0.76–2.06 and hazard ratio 1.38, 95% CI 0.93–2.05) for MI and all-cause mortality respectively. Unrecognized MI did not improve risk prediction for future recognized MI using the Framingham Risk Score ( p = 0.96) or the European Systematic COronary Risk Evaluation ( p = 0.65). There was no significant sex interaction regarding any of the endpoints. Conclusion Electrocardiographic unrecognized MI was not significantly associated with future risk of MI, stroke or all-cause mortality in the general population after adjustment for the traditional cardiovascular risk factors, and it did not improve prediction of future MI.

scholarly journals Non-traditional risk factors for myocardial infarction and systolic heart failure following kidney transplantation

2013 ◽  
Vol 34 (suppl 1) ◽  
pp. P1593-P1593
Author(s):  
A. Guha ◽  
W. R. Maddox ◽  
R. A. Sorrentino ◽  
A. Ghaffari ◽  
R. Colombo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Heart Failure ◽  
Kidney Transplantation ◽  
Systolic Heart Failure ◽  
Traditional Risk Factors

scholarly journals Dexamethasone Associated ST Elevation Myocardial Infarction Four Days after an Unremarkable Coronary Angiogram—Another Reason for Cautious Use of Steroids: A Case Report and Review of the Literature

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Mohamed Shokr ◽  
Ahmed Rashed ◽  
Kusum Lata ◽  
Ashok Kondur
Keyword(s):  
Risk Factors ◽  
Myocardial Infarction ◽  
Coronary Spasm ◽  
St Elevation Myocardial Infarction ◽  
Coronary Angiogram ◽  
Review Of The Literature ◽  
Drug Induced ◽  
St Elevation ◽  
Traditional Risk Factors ◽  
Artery Disease

Drug induced myocardial infarction is a known entity with different forms of steroids linked to coronary artery disease (CAD) either through promoting its traditional risk factors, inducing coronary spasm, or by other unidentified mechanisms. Dexamethasone is known to promote an atherogenic and hypercoagulable state. We report a case of a 75-year-old woman who had ST elevation myocardial infarction (STEMI) associated with dexamethasone use just 4 days following an angiogram showing minor luminal irregularities.

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