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Health-related quality of life (HRQoL) is considered an important outcome measure in chronic diseases, in particular cardiovascular disease (CVD), which is known to be associated with impaired HRQoL. However, few studies have examined HRQoL in individuals at high risk of CVD.
Using the Fifth Korea National Health and Nutrition Examination Survey 2010-2012, we analyzed data from 10,307 adults aged ≥30 years. The study subjects were stratified into 3 groups on the basis of their Framingham risk score-a 10-year estimate of CVD risk: <10.0% (low risk), 10.0%-19.9% (moderate risk), and ≥20.0% (high risk). The EuroQol-5D (EQ-5D) was used to evaluate HRQoL.
A significantly higher proportion of high-risk subjects than low-risk participants had impaired HRQoL (defined as the lowest quartile of the EQ-5D index); this held true even after adjustment for confounding factors in multivariable logistic regression analysis (men: odds ratio [OR], 1.62; 95% confidence interval [CI], 1.24-2.11; women: OR, 1.46; 95% CI, 1.02-2.08). In terms of the 5 EQ-5D dimensions, a 10-year CVD risk ≥20.0% was significantly associated with self-reported problems of mobility in men (OR, 3.15; 95% CI, 2.02-4.90), and of mobility (OR, 1.56; 95% CI, 1.09-2.24), self-care (OR, 2.14; 95% CI, 1.09-4.22), and usual activity problems (OR, 1.80; 95% CI, 1.17-2.78) in women.
A high CVD risk is associated with impaired HRQoL. After adjustment for demographic and clinical factors, a 10-year CVD risk ≥20.0% is an independent predictor of impaired HRQoL in the general population; in particular, of mobility problems in men, and of mobility, self-care, and usual activity problems in women.
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The aim of this study was to investigate the relationship between heart rate variability (HRV), the Framingham risk score (FRS), and the 10-year risk of coronary heart disease (CHD) development among Korean adults.
The subjects were 85 healthy Korean adults recruited from a health check-up center. The FRS and 10-year risk of CHD development were calculated.
The FRS in men was inversely correlated with the standard deviation of all normal to normal RR-intervals (SDNN); the root mean square successive difference (RMSSD); the percentage of successive normal cardiac inter-beat intervals greater than 20 ms, 30 ms, and 50 ms (pNN20, pNN30, pNN50); the low frequency (LF); and the high frequency (HF) (P < 0.05). There was no significant relationship between the FRS and HRV in women. Overall, in the receiver operating characteristic (ROC) analysis, the RMSSD, HF, SDNN, LF, LF/HF ratio, and pNN30 predicted an increased 10-year CHD risk. After adjusting for sex and body mass index, those with greater than one standard deviation in the RMSSD, HF, and LF had a 52-59% reduction in their 10-year risk of CHD development ≥ 10%.
This study therefore indicates that the HRV indices, particularly SDNN, RMSSD, pNN30, LF, and HF may be useful parameters for the assessment of CHD risk. Most notably, the usefulness of these HRV measures as indicators for CHD risk evaluation may be greater among men than among women.
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To compare the predictability of the Framingham Risk Score (FRS), United Kingdom Prospective Diabetes Study (UKPDS) risk engine, and the Systematic Coronary Risk Evaluation (SCORE) for carotid atherosclerosis and peripheral arterial disease in Korean type 2 diabetic patients.
Among 1,275 registered type 2 diabetes patients in the health center, 621 subjects with type 2 diabetes participated in the study. Well-trained examiners measured the carotid intima-media thickness (IMT), carotid plaque, and ankle brachial index (ABI). The subject's 10-year risk of coronary heart disease was calculated according to the FRS, UKPDS, and SCORE risk scores. These three risk scores were compared to the areas under the curve (AUC).
The odds ratios (ORs) of all risk scores increased as the quartiles increased for plaque, IMT, and ABI. For plaque and IMT, the UKPDS risk score provided the highest OR (95% confidence interval) at 3.82 (2.36, 6.17) and at 6.21 (3.37, 11.45). For ABI, the SCORE risk estimation provided the highest OR at 7.41 (3.20, 17.18). However, no significant difference was detected for plaque, IMT, or ABI (P = 0.839, 0.313, and 0.113, respectively) when the AUCs of the three risk scores were compared. When we graphed the Kernel density distribution of these three risk scores, UKPDS had a higher distribution than FRS and SCORE.
No significant difference was observed when comparing the predictability of the FRS, UKPDS risk engine, and SCORE risk estimation for carotid atherosclerosis and peripheral arterial disease in Korean type 2 diabetic patients.
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