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Table 2 Baseline Patient Characteristics

From: Development and internal validation of machine learning algorithms to predict patient satisfaction after total hip arthroplasty

Variables

Training set

(n = 1206)

Test set

(n = 302)

P-value

Age

62.8 (12.1)

63.2 (11.8)

0.623

Sex (Female)

841 (69.7%)

211 (69.9%)

0.964

BMI

25.9 (4.8)

25.3 (4.3)

0.075

BMI (categorical)

  

0.488

  < 18.5

39 (3.2%)

14 (4.6%)

–

 18.5–29.9

982 (81.4%)

241 (79.8%)

–

  ≥ 30

185 (15.3%)

47 (15.6%)

–

Comorbidities

 Number of comorbidities

1.0 (1.1)

0.9 (1.1)

0.417

 Diabetes

133 (11.0%)

30 (9.9%)

0.584

 Hypertension

518 (43.0%)

115 (38.1%)

0.125

 High cholesterol

389 (32.3%)

93 (30.8%)

0.626

 IHD

52 (4.3%)

16 (5.3%)

0.460

 Stroke

17 (1.4%)

7 (2.3%)

0.259

 Renal disease

22 (1.8%)

7 (2.3%)

0.576

 Back pain

35 (2.9%)

7 (2.3%)

0.581

 Depression

7 (0.6%)

2 (0.6%)

0.999

Surgical History

 Previous knee surgery

133 (11.0%)

37 (12.3%)

0.548

 Previous hip surgery

236 (19.6%)

64 (21.2%)

0.527

 Previous lumbar spine surgery

69 (5.7%)

28 (9.3%)

0.025*

Preop PROMs

 SF-36 PCS

27.4 (8.9)

26.7 (9.8)

0.233

 SF-36 MCS

49.1 (12.1)

49.2 (12.2)

0.899

 WOMAC

49.5 (20.9)

48.5 (20.9)

0.473

 OHS

40.0 (9.2)

40.8 (9.3)

0.190

2-year PROM Improvement

 SF-36 PCS

+ 20.2 (12.0)

+ 19.8 (12.4)

0.601

 SF-36 MCS

+ 6.9 (12.1)

+ 6.7 (12.6)

0.804

 WOMAC

+ 41.4 (20.9)

+ 41.6 (22.1)

0.921

 OHS

−24.1 (9.7)

−24.4 (10.2)

0.658

2-year Satisfaction

 Satisfied

69 (5.7%)

17 (5.6%)

0.951

  1. Continuous outcomes are reported as mean (standard deviation) while categorical outcomes are presented as number (percentage)
  2. P-values are calculated using two-sample t-tests for continuous variables and Chi-squared test/Fisher’s exact test for categorical variables
  3. *: P-value < 0.05