Deep Learning Model for Predicting Rhythm Outcomes after Radiofrequency Catheter Ablation in Patients with Atrial Fibrillation
Table 1
Baseline characteristics of patients with and without late recurrence following catheter ablation.
Without late recurrence (n = 130)
With late recurrence (n = 47)
P value
Age (years)
59 10
60 10
0.626
Age > 65 years
35 (27)
16 (34)
0.356
Female sex
16 (12)
11 (23)
0.070
Height (cm)
167 7
166 8
0.604
Body weight (kg)
72 11
71 12
0.552
BMI (kg/m2)
26 3
26 4
0.686
Persistent atrial fibrillation
58 (45)
30 (64)
0.024
AF duration (month)
23 25
36 41
0.054
Heart failure
4 (3)
7 (15)
0.009
Hypertension
49 (38)
13 (28)
0.217
Diabetes mellitus
21 (16)
9 (19)
0.639
Prior stroke or TIA or SE
11 (8.5)
9 (19)
0.047
Vascular disease
8 (6)
4 (9)
0.582
TTE findings
LA diameter (mm)
41 6
43 7
0.090
LA diameter 43 mm
49 (38)
23 (49)
0.179
LVEF (%)
69 9
68 13
0.515
LVEF < 50%
3 (2.3)
4 (8.5)
0.082
LV mass index (g/m2)
87 19
90 28
0.452
Laboratory findings
eGFR (ml/min/1.73 m2)
95 21
88 22
0.055
eGFR < 60 ml/min/1.73 m2
5 (4)
3 (6)
0.359
CHA2DS2-VASc score, median (IQR)
1 (0–2)
1 (0–2)
0.299
APPLE score, median (IQR)
1 (0–2)
1 (1–2)
0.026
Results are presented as n (%) or means with standard deviation. AF, atrial fibrillation; BMI, body mass index; eGFR, estimated glomerular filtration rate; LA, left atrium; LV, left ventricle, LVEF, left ventricular ejection fraction; SE, systemic embolism; TIA, transient ischemic attack; TTE, transthoracic echocardiography.
