Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes
Abstract
Since there is a high prevalence of type 2 diabetes mellitus (DM2), as well as CVD in Montenegro, we aimed to estimate CVD risk by United Kingdom Prospective Diabetes Study (UKPDS) risk engine algorithm in individuals with DM2. Furthermore, we aimed to explore whether non-traditional biomarker such as high sensitivity C-reactive protein (hsCRP) is superior for CVD risk prediction over old traditional risk factors. A total of 180 participants with DM2 (of them 50% females) were included in the current cross-sectional study. Biochemical and anthropometric parameters, and blood pressure were obtained. More males than females were classified at high UKPDS risk category (p lt 0.001). Also, about one third of diabetic patients (29.4%) were classified into the high-risk category. In multivariate regression analysis, triglycerides [Odds ratio (OR) =1.703, p=0.001] and creatinine concentration (OR=1.040, p lt 0.001) were independent predictors of CVD risk, whereas hsCRP was not correlated with ...CVD risk. HsCRP is not superior for CVD risk prediction by UKPDS risk engine algorithm over high triglyceride and creatinine levels in diabetic population, which suggests that the old traditional markers must not be underestimated when examining CVD risk in population with diabetes.
Keywords:
Cardiovascular risk / Type 2 diabetes / UKPDS risk engineSource:
Open Medicine, 2018, 13, 1, 610-617Publisher:
- Sciendo, Warsaw
Funding / projects:
DOI: 10.1515/med-2018-0086
ISSN: 2391-5463
PubMed: 30847393
WoS: 000474884700001
Scopus: 2-s2.0-85062549051
Collections
Institution/Community
PharmacyTY - JOUR AU - Kavarić, Nebojša AU - Klisić, Aleksandra AU - Ninić, Ana PY - 2018 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3139 AB - Since there is a high prevalence of type 2 diabetes mellitus (DM2), as well as CVD in Montenegro, we aimed to estimate CVD risk by United Kingdom Prospective Diabetes Study (UKPDS) risk engine algorithm in individuals with DM2. Furthermore, we aimed to explore whether non-traditional biomarker such as high sensitivity C-reactive protein (hsCRP) is superior for CVD risk prediction over old traditional risk factors. A total of 180 participants with DM2 (of them 50% females) were included in the current cross-sectional study. Biochemical and anthropometric parameters, and blood pressure were obtained. More males than females were classified at high UKPDS risk category (p lt 0.001). Also, about one third of diabetic patients (29.4%) were classified into the high-risk category. In multivariate regression analysis, triglycerides [Odds ratio (OR) =1.703, p=0.001] and creatinine concentration (OR=1.040, p lt 0.001) were independent predictors of CVD risk, whereas hsCRP was not correlated with CVD risk. HsCRP is not superior for CVD risk prediction by UKPDS risk engine algorithm over high triglyceride and creatinine levels in diabetic population, which suggests that the old traditional markers must not be underestimated when examining CVD risk in population with diabetes. PB - Sciendo, Warsaw T2 - Open Medicine T1 - Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes VL - 13 IS - 1 SP - 610 EP - 617 DO - 10.1515/med-2018-0086 ER -
@article{ author = "Kavarić, Nebojša and Klisić, Aleksandra and Ninić, Ana", year = "2018", abstract = "Since there is a high prevalence of type 2 diabetes mellitus (DM2), as well as CVD in Montenegro, we aimed to estimate CVD risk by United Kingdom Prospective Diabetes Study (UKPDS) risk engine algorithm in individuals with DM2. Furthermore, we aimed to explore whether non-traditional biomarker such as high sensitivity C-reactive protein (hsCRP) is superior for CVD risk prediction over old traditional risk factors. A total of 180 participants with DM2 (of them 50% females) were included in the current cross-sectional study. Biochemical and anthropometric parameters, and blood pressure were obtained. More males than females were classified at high UKPDS risk category (p lt 0.001). Also, about one third of diabetic patients (29.4%) were classified into the high-risk category. In multivariate regression analysis, triglycerides [Odds ratio (OR) =1.703, p=0.001] and creatinine concentration (OR=1.040, p lt 0.001) were independent predictors of CVD risk, whereas hsCRP was not correlated with CVD risk. HsCRP is not superior for CVD risk prediction by UKPDS risk engine algorithm over high triglyceride and creatinine levels in diabetic population, which suggests that the old traditional markers must not be underestimated when examining CVD risk in population with diabetes.", publisher = "Sciendo, Warsaw", journal = "Open Medicine", title = "Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes", volume = "13", number = "1", pages = "610-617", doi = "10.1515/med-2018-0086" }
Kavarić, N., Klisić, A.,& Ninić, A.. (2018). Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes. in Open Medicine Sciendo, Warsaw., 13(1), 610-617. https://doi.org/10.1515/med-2018-0086
Kavarić N, Klisić A, Ninić A. Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes. in Open Medicine. 2018;13(1):610-617. doi:10.1515/med-2018-0086 .
Kavarić, Nebojša, Klisić, Aleksandra, Ninić, Ana, "Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes" in Open Medicine, 13, no. 1 (2018):610-617, https://doi.org/10.1515/med-2018-0086 . .