Using a Clinical Decision Support System to Improve Anticoagulation in Patients with Nonvalve Atrial Fibrillation in China’s Primary Care Settings: A Feasibility Study
Table 3
Basic demographics of subjects lost to follow-up.
Completed follow-up(n = 84)
Loss to follow-up (n = 22)
Total (n = 106)
2/t
Group, n (%)$
0.119
0.730
Software
53 (63.1)
13 (59.1)
66 (62.3)
Control
31 (36.9)
9 (40.9)
40 (37.7)
Gender, n (%)$
0.000
0.986
Male
46 (54.8)
12 (54.5)
58 (54.7)
Female
38 (45.2)
10 (45.5)
48 (45.3)
Age (y), mean (SD)#
75.71 (7.237)
75.91 (7.322)
75.75 (7.220)
−0.112
0.911
Hypertension, n (%)$
76 (90.5)
20 (90.9)
96 (90.6)
0.004
0.951
Heart failure, n (%)$
9 (11.3)
5 (22.7)
14 (13.2)
2.195
0.138
Diabetes, n (%)$
28 (33.3)
7 (31.8)
35 (34.0)
0.057
0.811
Stroke/TIA/thromboembolism history, n (%)$
16 (20.0)
0 (0.0)
16 (15.1)
4.935
0.026
Antiplatelets or NSAIDs, n (%)$
28 (35.0)
6 (30.0)
34 (32.7)
0.082
0.775
CHA2DS2-VASc score, n (%)$
6.034
0.012
2
81 (96.4)
18 (81.8)
99 (93.4)
<2
3 (3.6)
4 (18.2)
7 (6.6)
HAS-BLED score, n (%)$
11.221
0.001
3
45 (53.6)
3 (13.6)
48 (45.3)
<3
39 (46.4)
19 (86.4)
58 (54.7)
Note. $Chi-square test; #Two-tailed unpaired student’s t-test. Values in bold were statistically significant.
