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Table 1 Descriptive characteristics of the sample

From: The efficacy of machine learning models in forecasting treatment failure in thoracolumbar burst fractures treated with short-segment posterior spinal fixation

Variable

Frequency (%)

Sex

Male

204 (61.4)

Female

128(38.6)

Failure of treatment

Yes

44(13.3)

No

288(86.7)

Cause of Injury

Road Traffic crashes

181(54.5)

Fall

106 (31.9)

Sport

12 (3.6)

Assault/violence related

29 (8.7)

Other

4 (1.2)

Level of Vertebra

T10

15 (4.5)

T11

27 (8.1)

T12

127 (38.3)

L1

112 (33.7)

L2

51 (15.4)

Smoking

Yes

58 (17.5)

No

274 (82.5)

Diabetes

Yes

54 (16.3)

No

278(83.7)

Use of crosslinks

Yes

102 (30.7)

No

230 (69.3)

Index level instrumentation

Yes

108 (32.5)

No

224(67.5)

Posterolateral fusion

Yes

158 (47.6)

No

174 (52.4)