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REVIEW ARTICLE
Year : 2015  |  Volume : 142  |  Issue : 3  |  Page : 261-268

High sensitivity C-reactive protein (hsCRP) & cardiovascular disease: An Indian perspective


1 Division of Clinical Research & Training, St. John's Research Institute, St. John's National Academy of Health Sciences, Bengaluru, India
2 Department of Pharmacology, St. John's Medical College, Bengaluru, India

Correspondence Address:
Prem Pais
Department of Medicine, St. John's Medical College & Division of Clinical Research & Training, St. John's Research Institute, Bengaluru 560 034, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0971-5916.166582

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The role of low grade systemic inflammation as evidenced by elevated high sensitivity C-reactive protein (hsCRP) levels in the pathogenesis of atherosclerotic vascular disease has been intensely investigated through observational studies and clinical trials in the past two decades. On the basis of evidence that has accrued, hsCRP measurement has been integrated into the Reynolds risk scoring system to predict cardiovascular risk. The JUPITER trial proved the benefit of statins in cardiovascular risk reduction in patients with low grades of systemic inflammation and 'normal' cholesterol levels. However, substantial evidence has been generated from western studies. We, therefore, conducted a scoping review for studies done in India with a view to identify gaps in evidence and make further recommendations. Most Indian studies had small sample sizes and short term follow ups. There were no large population based prospective studies where patients were followed up for long periods of time for major cardiovascular end points. An analysis of the hsCRP level from the control arms of case-control studies derived a mean hsCRP value of 1.88 mg/l, which is higher than the western population where values < 1 mg/l are classified as low cardiovascular risk. Further large prospective cohort studies with longer term follow ups are essential before we can make further recommendations to integrate hsCRP into risk prediction models for cardiovascular disease prevention.


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