Prevalence and Risk Factors of Mitral, Tricuspid, and Aortic Regurgitation: A Population-Based Study from Rural Northeast China.

The population-based studies on the epidemiologic features of valvular regurgitation in Northeast China are scarce. We aim to estimate the prevalence and risk factors of mitral regurgitation (MR), tricuspid regurgitation (TR), and aortic regurgitation (AR) in a general population from rural Northeast China. Valvular regurgitation was assessed by color flow Doppler echocardiography in a population-based survey of 11,278 participants aged ≥35 years in rural areas of Liaoning Province during 2012 to 2013. The prevalence of mild or greater MR and TR were 1.6% and 1.5%, respectively. Trace or greater AR was present in 4.1% of the participants. In the multivariable regression model, older age, left atrial dimension, low left ventricular (LV) ejection fraction, and fasting plasma glucose were associated with higher risk of MR in men, whereas only older age and left atrial dimension increased the risk in women. Body mass index was found to be a protective factor for MR in women (odds ratio 0.847, 95% confidence interval 0.741 to 0.969). TR was independently associated with age, heart rate, low LV ejection fraction, current drinking status, and high-density lipoprotein cholesterol. The risk for AR significantly increased with age in both genders. LV mass index and aortic dimension increased the risk of AR in males, and females with higher LV mass index and high-density lipoprotein cholesterol had an increased risk for AR. In both genders, systolic blood pressure presented as a risk factor for AR, while diastolic blood pressure as a protective factor. In this large Chinese population-based study, we found remarkably low prevalence of valvular regurgitation, adding evidence for estimating disease burden and making policy strategies in Northeast China.

Predictive value of liver fibrosis scores in cardiovascular diseases among hypertensive population.

PURPOSE: To explore the predictive value of liver fibrosis scores [fibrosis-4, AST/platelet ratio index, BAAT score (BMI Age ALT TG), and BARD score (BMI AST/ALT Ratio Diabetes)] for the risk of cardiovascular disease (CVD) in a hypertensive population. METHODS: A total of 4164 hypertensive participants without history of CVD were enrolled in the follow-up. Four liver fibrosis scores (LFSs) were used, including the fibrosis-4 (FIB-4), APRI, BAAT score, and BARD score. The endpoint was CVD incidence which was defined as stroke or coronary heart disease (CHD) during the follow-up period. Cox regression analyses were used to calculate hazard ratios between LFSs and CVD. Kaplan-Meier curve was used to show the probability of CVD in different levels of LFSs. Restricted cubic spline further explored whether the relationship between LFSs and CVD was linear. Finally, we assessed the discriminatory ability of each LFS for CVD was assessed using C -statistics, net reclassification index (NRI), and integrated discrimination improvement (IDI). RESULTS: During a median follow-up time of 4.66 years, 282 hypertensive participants had CVD. Kaplan-Meier curve showed that four LFSs were associated with CVD and high levels of LFSs significantly increase the probability of CVD in hypertensive population. In the multivariate Cox regression analysis, the adjusted hazard ratios for four LFSs were 3.13 in FIB-4, 1.66 in APRI, 1.47 in BAAT score, and 1.36 in BARD score. Moreover, after adding LFSs to original risk prediction model, we find that all four new models have higher C -statistics of CVD than the traditional model. Furthermore, the results of both NRI and IDI were positive, indicating that LFSs enhanced the effect on the prediction of CVD. CONCLUSIONS: Our study showed that LFSs were associated with CVD in hypertensive populations in northeastern China. Furthermore, it suggested that LFSs could be a new tool for identifying patients at high risk of primary CVD in a hypertensive population.

The association between liver fibrosis scores and chronic kidney disease.

Purpose: This study aimed to clarify the relationship between liver fibrosis scores (Fibrosis-4, BARD score, and BAAT score) and chronic kidney disease (CKD). Methods: We collected a range of data from 11,503 subjects (5,326 men and 6,177 women) from the rural regions of Northeastern China. Three liver fibrosis scores (LFSs) including fibrosis-4 (FIB-4), BARD score, and BAAT score were adopted. A logistic regression analysis was used to calculate odds ratios and the 95% confidence interval. A subgroup analysis showed the association between LFSs and CKD under different stratifications. Restricted cubic spline could further explore whether there is a linear relationship between LFSs and CKD. Finally, we used C-statistics, Net Reclassification Index (NRI), and Integrated Discrimination Improvement (IDI) to assess the effect of each LFS on CKD. Results: Through the baseline characteristics, we observed that LFSs were higher in the CKD population than in non-CKD. The proportion of participants with CKD also increased with LFSs. In a multivariate logistic regression analysis, the ORs of CKD were 6.71 (4.45-10.13) in FIB-4, 1.88 (1.29-2.75) in the BAAT score, and 1.72 (1.28-2.31) in the BARD score by comparing the high level with the low level in each LFSs. Moreover, after adding LFSs to the original risk prediction model, which consisted of age, sex, drinking, smoking, diabetes, low-density lipoprotein cholesterol, total cholesterol, triglycerides, and mean waist circumference, we found the new models have higher C-statistics. Furthermore, NRI and IDI both indicate LFSs had a positive effect on the model. Conclusions: Our study showed that LFSs are associated with CKD among middle-aged populations in rural areas of northeastern China.

Predictive Value of the Age, Creatinine, and Ejection Fraction (ACEF) Score in Cardiovascular Disease among Middle-Aged Population.

PURPOSE: To explore the predictive value of ACEF scores for identifying the risk of cardiovascular disease (CVD) in the general population. METHODS: A total of 8613 participants without a history of CVD were enrolled in the follow-up. The endpoint was CVD incidence, defined as stroke or coronary heart disease (CHD) diagnosed during the follow-up period. Cox regression analyses were used to calculate hazard ratios (HRs) with respect to the age, creatinine, and ejection fraction (ACEF) scores and CVD. A Kaplan-Meier curve was used to analyze the probability of CVD in different quartiles of ACEF. Restricted cubic spline was used to further explore whether the relationship between ACEF and CVD was linear. Finally, we assessed the discriminatory ability of ACEF for CVD using C-statistics, net reclassification index, and integrated discrimination improvement (IDI). RESULTS: During a median follow-up period of 4.66 years, 388 participants were diagnosed with CVD. The Kaplan-Meier curve showed that ACEF was associated with CVD, and participants with high ACEF scores were significantly more likely to be diagnosed with CVD compared to participants with low ACEF scores in the general population. In the multivariate Cox regression analysis, the adjusted HRs for four quartiles of ACEF were as follows: the first quartile was used as a reference; the second quartile: HR = 2.33; the third quartile: HR = 4.81; the fourth quartile: HR = 8.00. Moreover, after adding ACEF to the original risk prediction model, we observed that new models had higher C-statistic values of CVD than the traditional model. Furthermore, the results of both NRI and IDI were positive, indicating that ACEF enhanced the prediction of CVD. CONCLUSIONS: Our study showed that the ACEF score was associated with CVD in the general population in northeastern China. Furthermore, ACEF could be a new tool for identifying patients at high risk of primary CVD in the general population.

Impact of liver fibrosis score on the incidence of stroke: A cohort study.

PURPOSE: The purpose was to explore the value of liver fibrosis scores (fibrosis-4, BAAT score and BARD score) for incidence risk of stroke in a cohort study. METHODS: A total of 9088 participants without stroke history enrolled the follow-up. Three liver fibrosis scores (LFSs) including FIB-4, BARD score and BAAT score were adopted. The end point was stroke. Cox regression analysis was used to calculate hazard ratios and 95% confidence interval. Kaplan-Meier curve was used to show the probability of stoke in different levels of LFSs. Subgroup analysis showed the association between LFSs and stroke under different stratification. Restricted cubic spline could further explore whether there is a linear relationship between LFSs and stroke. Finally, we used C-statistics, Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) to assess the discriminatory power of each LFS for stroke. RESULTS: During a median follow-up time of 4.66 years, 272 participants had a stroke. Through the baseline characteristics, we observed that the stroke incidence population tends to be male and older. It was shown by Kaplan-Meier that three LFSs were associated with stroke and high levels of LFSs significantly increase the probability of stroke. In the univariate Cox regression analysis, the HR of stroke risk was 6.04 (4.14-8.18) in FIB-4, 2.10 (1.45-3.04) in BAAT score and 1.81 (1.38-2.38) in BARD score by comparing the high level with the low level at each LFSs. The adjusted HRs for three LFSs were 2.05 (1.33-3.15) in FIB-4, 1.61 (1.10-2.35) in BAAT score and 1.54 (1.17-2.04) in BARD score by comparing the high group with low group. We found that multivariable-adjusted HRs of three LFSs still increased for stroke when stratified by various factors in subgroup analysis. Moreover, after adding LFSs to original risk prediction model which consist of age, sex, drinking, smoking, hypertension, diabetes, low-density lipoprotein cholesterol, total cholesterol and triglycerides, we found that new models have higher C-statistics of stroke. Furthermore, we calculated Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) to show the ability of LFSs to predict stroke. CONCLUSIONS: Our study showed that three LFSs were associated with stroke amongst middle-aged populations in rural areas of Northeast China. Furthermore, it suggests that LFSs can be used as a risk stratification tool to predict stroke.