[Predictive value of four score systems on the bleeding risk in atrial fibrillation patients treated with dabigatran].

Objective: To compare the predictive value of HAS-BLED, HEMORR2HAGES, ATRIA and ORBIT scores on the bleeding risk in nonvalvular atrial fibrillation (NVAF) patients treated with dabigatran. Methods: Data of 942 NVAF patients participating a non-interventional prospective study of anticoagulant therapy with dabigatran, which was conducted in 12 centers from February 2015 to December 2017 in China, were analyzed. Complete HAS-BLED HEMORR2HAGES, ATRIA and ORBIT bleeding risk scores data and follow-up data were available in the enrolled patients. The endpoint of the study was bleeding events occurred during a 6 months follow-up. Cox proportional hazards models were constructed to analyze the associations between HAS-BLED, HEMORR2HAGES, ATRIA and ORBIT scores and risk of bleeding, and the area under the curve (AUC) of receiver operating characteristics curves (ROC) of each score was used to set the predictive value for bleeding risk. Results: Among the 942 patients, the mean age was (65.3±11.2) years old, 542 (57.5%) were males. A total of 93 (9.9%) bleeding events occurred during follow up, 89 (9.4%) events were minor bleeding, and 4 (0.4%) events were major bleeding. Patients with a high-risk HAS-BLED score had a 1.87-fold increased risk of bleeding compared with low-risk patients (HR = 2.87, 95% CI:1.26-6.51, P = 0.012). There was no statistically significant difference between low-medium-high-risk grading in other scoring systems and bleeding risk (all P>0.05). The AUC (95%CI) of HAS-BLED, HEMORR2HAGES, ATRIA and ORBIT bleeding risk scores were 0.558 (0.525-0.590), 0.520 (0.487-0.553), 0.513(0.480-0.545), 0.523(0.490-0.555), respectively. The AUC of all bleeding score systems were of ≤ 0.700. Conclusion: Among the NVAF patients taking dabigatran in China, the HAS-BLED bleeding risk score is superior to other 3 bleeding risk score on predicting the bleeding risk in these patients, but its predictive value is still relatively low.

[Prevalence and influential factors of stroke in Jiangxi Province in 2014].

Objective: To discuss the prevalence and influential factors of stroke among population in Jiangxi Province. Methods: Four cities in urban areas and four counties in rural areas were selected firstly, in which two districts or townships were selected; and then three communities or villages were chosen from each district and township, respectively, using the simple random sampling (SRS) method. Finally 15 269 subjects aging 15 years old or above, living in Jiangxi Province ≥6 months were randomly selected to participate in this survey from November 2013 to August 2014. Information of population characteristics, life behavior way, individual disease history were collected through questionnaire survey, and height, weight, waist circumference, blood pressure, body fat rate, visceral fat index and so on were measured by instruments. Risk factors of stroke prevalence were analyzed by the unconditioned logistic regression analysis. Results: A total of 15 269 participants (6 267 males) from 15 364 eligible participants were included in the statistical analysis. Out of which, 7 793 participants came from urban areas, and their average age was (53.04±17.91) years old. In this study, 226 stroke patients (117 males) were found among15 269 participants, including 122 urban participants and 104 rural participants, whose average age was (67.76±9.74) years old. The prevalence of stroke was 1 480.12/100 000 in 2014, which was separately 1 866.92/100 000 and 1 210.84/100 000 among males and females. The prevalence of people aging (45-49) years old was 413.79/100 000 (6/1 450) , while which among people aging 75 years old and above was 3 311.62/100 000 (61/1 842) . The prevalence of stroke among residents in Jiangxi presented an uprising tendency with age increasing (linear-by-linear association χ(2)=62.23, P<0.01). The research showed that when other influencing factors including gender, BMI, waist circumference, pulse-pressure difference, VAI, and sleeping time in non-working days were controlled, hypertensive patients had a higher risk of stroke than people without hypertension (OR=6.88, 95%CI: 4.90-9.67), drinkers had a higher risk of stroke than non-drinkers (OR=1.56, 95%CI: 1.17-2.08), compared with people <65 years old, people aged 65-74 years old and ≥75 years old had a higher risk of stroke, the value of OR (95%CI) were 1.88 (1.36-2.59) and 1.97 (1.39-2.80), respectively, compared with people with normal body fat percentage, people whose body fat percentage on high side and people who with high body fat percentage had a higher risk of stroke, the value of OR (95%CI) were 1.71 (1.18-2.48) and 1.74 (1.18-2.56), respectively, people with sleep time >8 h had a higher risk of stroke than those with sleep time of 6-8 h. Conclusion: There was a high stroke prevalence among residents in Jiangxi province. Hypertension, drinking, age, BFP and sleep duration were associated with stroke prevalence. Corresponding measures for high-risk population and risk factors should be strengthened to prevent and control the stroke.