In:
Arteriosclerosis, Thrombosis, and Vascular Biology, Ovid Technologies (Wolters Kluwer Health), Vol. 41, No. Suppl_1 ( 2021-09)
Abstract:
Introduction: Inflammation contributes to the pathogenesis of major adverse cardiovascular events (MACE) after an acute myocardial infarction (AMI). However, the optimal way to characterise inflammation and predict risk is unclear. While various biomarkers have been used to examine the relationship between acute inflammation and MACE risk, results are inconsistent between studies. Using a range of inflammatory markers, we assessed their utility to predict MACE in AMI patients. Hypothesis: A combined inflammatory biomarker approach is superior to individual biomarkers for predicting MACE risk in AMI patients. Methods: We conducted a systematic review of multi-marker approaches to characterise inflammation following AMI. Through cohort studies, a case control study, and a time series, we also examined the relationship between inflammatory markers and MACE. The studies ranged in size from 23 to 860 patients, with an average MACE rate of 13 in 100 at one year follow up. Results: Our systematic review found four studies that attempted various combined cytokine approaches. All found statistical associations with MACE, and performed better than single markers. In our studies, we first explored simple methods of combining biomarkers (ratios of leukocyte counts, and simple addition of C-reactive protein, IL-6 and TNF-alpha). We found no independent associations with MACE when biomarkers were combined via simple methods. We then examined a more sophisticated approach for combining cytokines. We chose to use a mathematical technique (principal component analysis, PCA) that could deal with co-linearity within individual cytokine measurements and combine individual cytokine measurements into a score. We selected six cytokines, and a PCA score derived from these markers was associated with MACE on univariate analysis. Individually, IL-6 and IL-8 levels were univariate predictors of MACE. Combining these two into a PCA-derived score resulted in a stronger, independent association with MACE (odds ratio 2.77, p 〈 0.05) than seen with either marker alone. Conclusion: Multi-marker inflammatory scores may produce more consistent associations with MACE than single biomarkers. We suggest that PCA is a useful mathematical method for creating this type of score.
Type of Medium:
Online Resource
ISSN:
1079-5642
,
1524-4636
DOI:
10.1161/atvb.41.suppl_1.P133
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2021
detail.hit.zdb_id:
1494427-3
