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Table 1 Patients’ baseline characteristics in training and test cohorts

From: Predicting who has delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage using machine learning approach: a multicenter, retrospective cohort study

Characteristics

Total (n = 1039)

Test cohort (n = 120)

Training cohort (n = 919)

P-value

Demographics

age

57[51, 67]

57 [49, 65]

57 [51, 67]

0.236

sex (Famale)

663(63.811)

67(55.833)

596(64.853)

0.053

Blood type

   

0.89

A

336(32.339)

42(35.000)

294(31.991)

 

B

215(20.693)

24(20.000)

191(20.783)

 

AB

90(8.662)

12(10.000)

78(8.487)

 

O

333(32.050)

36(30.000)

297(32.318)

 

Unknown

65(6.256)

6(5.000)

59(6.420)

 

Medical history

smoking

288(27.719)

35(29.167)

253(27.530)

0.706

drinking

276(26.564)

33(27.500)

243(26.442)

0.805

History of illness

581(55.919)

59(49.167)

522(56.801)

0.113

diabetes

49(4.716)

8(6.667)

41(4.461)

0.284

hypertension

521(50.144)

55(45.833)

466(50.707)

0.315

Atrial fibrillation

9(0.866)

2(1.667)

7(0.762)

0.314

Intracranial parenchymal hematoma

173(16.651)

29(24.167)

144(15.669)

0.019

Ventricular hemorrhage

479(46.102)

38(31.667)

441(47.987)

< 0.001

aneurysm treatment modality

   

0.085

Clipping

644(61.983)

83(69.167)

561(61.045)

 

Coiling

395(38.017)

37(30.833)

358(38.955)

 

Clinical condition on admission

HH

   

< 0.001

0

2(0.2)

2(1.7)

0(0)

 

1

202(19)

15(13)

187(20)

 

2

586(56)

62(52)

524(57)

 

3

182(18)

31(26)

151(16)

 

4

64(6.2)

9(7.5)

55(6.0)

 

5

3(0.3)

1(0.8)

2(0.2)

 

Fisher

   

< 0.001

0

158(15)

2(1.7)

156(17)

 

1

143(14)

19(16)

124(13)

 

2

376(36)

44(37)

332(36)

 

3

214(21)

20(17)

194(21)

 

4

148(14)

35(29)

113(12)

 

WFNS

   

0.007

1

771(74)

73(61)

698(76)

 

2

106(10)

21(18)

85(9.2)

 

3

43(4.1)

8(6.7)

35(3.8)

 

4

75(7.2)

12(10)

63(6.9)

 

5

44(4.2)

6(5.0)

38(4.1)

 

mRS

   

< 0.001

0

603(58)

37(31)

566(62)

 

1

201(19)

45(38)

156(17)

 

2

60(5.8)

8(6.7)

52(5.7)

 

3

41(3.9)

11(9.2)

30(3.3)

 

4

45(4.3)

6(5.0)

39(4.2)

 

5

84(8.1)

12(10)

72(7.8)

 

6

5(0.5)

1(0.8)

4(0.4)

 

GCS

15 [14, 15]

15 [13, 15]

15 [15]

< 0.001

Clinical routine examination data

PT

11.8[11.1, 12.6]

12.4[11.6, 13]

11.7[11.1, 12.5]

< 0.001

APTT

28.3[25.4, 32.5]

30.1[26.7, 33.2]

28.2[25.3, 32.4]

0.032

D-Dimer

2.45[1.09, 44]

289.2[2.53, 682.18]

2.16[1.04,7.47]

< 0.001

WBC

8.37[6.55, 11.03]

9.85[7.75, 12.44]

8.22[6.42, 10.82]

< 0.001

NLR

4.946[3.183, 9.341]

8.788[5.074,15.116]

4.687[3.093,8.523]

< 0.001

PNR

25.930[18.832,36.293]

22.222[15.509,27.393]

26.589[19.203,37.000]

<0.001

DCI

239(23.003)

60(50.000)

179(19.478)

< 0.001