Multi-Biomarker-Based Risk Assessment Model: Implications in Patients with Hypertensive Heart Disease
Asian Journal of Cardiology Research · pp. 224–229 · Published 2 Aug 2021
Abstract
Systemic hypertension is a leading cause of morbidity and mortality worldwide. Primary and secondary prevention of cardiovascular adverse events are limited by the generally poor predictive value of traditional risk factors assessment models. The use of tissue-specific cardiac biomarkers that can reliably assess pathologic conditions is important for early detection and prevention of target organ damage. This review article highlights the role of multi-biomarker models in providing insight to greater understanding of the pathophysiological mechanisms and their implications on cardiovascular morbidity in systemic hypertension.
Cited by 0
No indexed citations yet.
Related research
- Dietary Pattern and Prevalence of High Blood Pressure among Adult Traders in Port Harcourt, Nigeria — shares topic coverage
- Impact of the Diet Profile and Alcohol Consumption on Cardiometabolic Risks in Dschang Health District-Cameroon — shares topic coverage
- Gender Specific Predictive Performance and Optimal Threshold of Anthropometric Indices for the Prediction of Hypertension among a Ghanaian Population in Kumasi — shares topic coverage
- Metabolic Syndrome and Kidney Damage: Prevalence and Assessment of Risk among Apparently Healthy Resident of Ado Ekiti, South West Nigeria — shares topic coverage
- Analysis of Risk Factors among Diabetic Patients Visiting Diabetic Research Clinic at Nishtar Hospital Multan-Pakistan — shares topic coverage
Article metrics
Real usage data collected on this platform.
0
Page views
0
PDF downloads
0
Outbound clicks
0
Citations
Views by country
Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".
No views recorded yet.
Traffic sources
Referring site, by host.
No traffic recorded yet.
Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.