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Table 1 Baseline characteristics [n (%), \(\overline{x }\)±s]

From: Comparison of the effectiveness of different machine learning algorithms in predicting new fractures after PKP for osteoporotic vertebral compression fractures

Characteristics

 

Patients number

529

Age

71.185 ± 10.012

Gender (Male/Female)

135 (25.5)/394 (74.5)

BMI (kg/m2)

23.394 ± 3.299

BMD

− 2.811 ± 0.270

Hypertension

200 (37.8)/329 (62.2)

Diabetes

45 (8.5)/484 (91.5)

Heart disease

28 (5.3)/501 (94.7)

Respiratory system disease

7 (1.3)/522 (98.7)

Cerebrovascular disease

21 (4.0)/508 (96.0)

Injury time(days)

26.718 ± 67.426

Time from admission to surgery (days)

3.010 ± 2.552

Number of fractured vertebral

1.327 ± 0.693

Fracture vertebral location

 

 Thoracic/thoracolumbar/lumbar

72 (13.6)/347 (65.6)/110 (20.8)

Approach

 

 Unilateral/bilateral

147 (27.8)/382 (72.2)

Fracture history(Y/N)

90 (17.0)/439 (83.0)

New fracture(Y/N)

56 (10.6)/473 (89.4)

Paravertebral leakage

74 (14)/455 (86)

Intervertebral leakage

63 (11.9)/466 (88.1)

Spinal leakage

12 (2.3)/517 (97.7)

Postoperative Cobb

12.508 ± 8.293

Cement distribution

 

 Unilateral/bilateral fusion/ bilateral separation

119 (22.5)/285 (53.9)/125 (23.6)

Cement-endplate contact (Y/N)

417 (78.8)/417 (21.2)

Fracture type

 

 Wedge/biconcave/compression

208 (39.3)/264 (49.9)/57 (10.8)

Anti-osteoporosis(Y/N)

429 (81.1)/429 (18.9)

Vertebral height recovery rate

14.393 ± 13.441