Iván Gutierrez Moctezuma

Iván Gutierrez Moctezuma


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 September 2023 in Biomedicines
Verified
Journal Article
Open access
PDF file
EAEmanuel Amezcua-Castillo
Emanuel Amezcua-Castillo
HGHéctor Gonzalez-Pacheco
Héctor Gonzalez-Pacheco
AMArturo Sáenz-San Martín
Arturo Sáenz-San Martín
PMPablo Méndez-Ocampo
Pablo Méndez-Ocampo
IMIván Gutierrez Moctezuma
Iván Gutierrez Moctezuma
LALuis M Amezcua-Guerra
Luis M Amezcua-Guerra
Atherosclerotic cardiovascular disease (CVD) remains the leading cause of mortality worldwide. While conventional risk factors have been studied and managed, CVD continues to pose a global threat. Risk scoring systems based on these factors have been developed to predict acute coronary syndromes and guide therapeutic interventions. However, traditional risk algorithms may not fully capture the complexities of individual patients. Recent research highlights the role of inflammation, particularly chronic low-grade inflammation, in the pathogenesis of coronary artery disease (CAD). C-reactive protein (CRP) is an inflammatory molecule that has demonstrated value as a predictive marker for cardiovascular risk assessment, both independently and in conjunction with other parameters. It has been incorporated into risk assessment algorithms, enhancing risk prediction and guiding therapeutic decisions. Pharmacological interventions with anti-inflammatory properties, such as statins, glucagon-like peptide-1 agonists, and interleukin-1 inhibitors, have shown promising effects in reducing both cardiovascular risks and CRP levels. This manuscript provides a comprehensive review of CRP as a marker of systemic inflammation in CAD. By exploring the current knowledge surrounding CRP and its implications for risk prediction and therapeutic interventions, this review contributes to the advancement of personalized cardiology and the optimization of patient care.