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Table 3 Table of Descriptive Statistics for Data Features with P-Value Analysis for the External Validation dataset: This table presents the descriptive statistics for each feature, comparing the external validation and internal development datasets

From: Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures

Feature

Mean (Ext.)

St.Dev (Ext.)

Mean (Int.)

St.Dev (Int.)

Missing (Ext.)

Missing (Int.)

P-value

Age

68.809

10.867

66.720

10.546

0%

0%

< 0.001*

VAS (Preop)

7.229

2.187

7.125

2.123

0.1%

1.2%

0.085

SF12 Physical (Preop)

32.098

7.719

33.024

7.878

0%

0%

0.004*

SF12 Mental (Preop)

49.669

12.552

50.917

11.859

0%

0%

0.028*

EQ5D (Preop)

0.704

0.121

0.722

0.117

0.3%

0.2%

0.001*

Height

166.114

9.080

167.440

9.048

0.8%

1%

0.001*

Weight

75.795

15.432

77.033

15.212

0.8%

1%

0.085

BMI

27.387

4.719

27.387

4.455

0.8%

1%

0.916

Hemoglobin (Preop)

13.832

1.408

14.027

1.387

0.4%

0.5%

0.002*

Feature

Categories (Ext.)

Categories (Int.)

P-value

Sex

Female (39.6%), Male (60.4%)

Female (46.7%), Male (53.3%)

0.001*

Hip/Knee

Hip (57%), Knee (43%)

Hip (57%), Knee (43%)

0.800

Intervention

First intervention (91.8%), Revision (8.2%)

First Intervention (96.2%), Revision (2.8%)

< 0.001*

ASA

1 (11.2%), 2(82.0%), 3 (6.8%)

1 (13.6%), 2 (82.8%), 3 (3.6%)

1 (0.095), 2 (0.547), 3 (0.001*)

  1. For all features we evaluated the presence of differences with respect to the internal development dataset. For continuous and ordinal features, differences were assessed using the Mann-Whitney U test, while for categorical features, the Fisher’s exact test was utilized to determine statistical significance
  2. Asterisk denotes a significant difference between the two cohorts, at the 95% confidence level
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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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