| Title |
Association of high-sensitivity C-reactive protein and uric acid with the metabolic syndrome components
|
|---|---|
| Published in |
SpringerPlus, March 2016
|
| DOI | 10.1186/s40064-016-1933-y |
| Pubmed ID | |
| Authors |
Santosh Kumar Sah, Saroj Khatiwada, Sunil Pandey, Rajendra KC, Binod Kumar Lal Das, Nirmal Baral, Madhab Lamsal |
| Abstract |
Metabolic syndrome (MetS) has been found to be associated with inflammatory molecules. This study was conducted among 125 MetS patients at B P Koirala Institute of Health Sciences, Dharan, Nepal to find an association of high-sensitivity C-reactive protein (hs-CRP) and serum uric acid with MetS components. Anthropometric measurements, blood pressure, medical history and blood samples were taken. Estimation of hs-CRP, serum uric acid, blood glucose, triglyceride and high density lipoprotein (HDL) cholesterol was done. hs-CRP had positive correlation with blood glucose (r = 0.2, p = 0.026) and negative with HDL cholesterol (r = -0.361, p < 0.001). Serum uric acid had positive correlation with waist circumference (r = 0.178, p = 0.047). Patients with elevated hs-CRP and uric acid had higher waist circumference (p = 0.03), diastolic BP (p = 0.002) and lower HDL cholesterol (p = 0.004) than others. Elevated hs-CRP and high uric acid were individually associated with higher odds for low HDL cholesterol (7.992; 1.785-35.774, p = 0.002) and hyperglycemia (2.471; 1.111-5.495, p = 0.029) respectively. Combined rise of hs-CRP and uric acid was associated with severity of MetS (p < 0.001) and higher odds for hyperglycemia (8.036; 2.178-29.647, p = 0.001) as compared to individual rise of hs-CRP or uric acid. The present study demonstrates that hs-CRP and serum uric acid are associated with MetS components, and the combined rise of hs-CRP and uric acid is associated with the increase in severity of MetS. |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 13% |
| Student > Doctoral Student | 4 | 11% |
| Student > Postgraduate | 4 | 11% |
| Other | 3 | 8% |
| Student > Bachelor | 3 | 8% |
| Other | 7 | 18% |
| Unknown | 12 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 32% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 5% |
| Immunology and Microbiology | 2 | 5% |
| Unspecified | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 13 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 March 2016.
All research outputs
#20,313,158
of 22,854,458 outputs
Outputs from SpringerPlus
#1,459
of 1,849 outputs
Outputs of similar age
#252,094
of 298,623 outputs
Outputs of similar age from SpringerPlus
#132
of 161 outputs
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