Title Page

Contents

국문요약 8

Ⅰ. Introduction 10

Ⅱ. Patients and Methods 13

A. Study Design 13

B. Patients 13

C. Risk factor designation 13

D. Statistics 15

Ⅲ. Result 17

A. Patient characteristics 17

B. Comparison of risk factor 17

C. Comparison of five classification and DIRECT coding systems 18

Ⅳ. Discussion 21

Ⅴ. Conclusion 26

참고 문헌 27

ABSTRACT 45

〈Table 1A〉 Baseline Characteristics (continuous variables) 38

〈Table 1B〉 Baseline Characteristics (categorical variables) 39

〈Table 2〉 Logistic Regression Analysis for Amputation of Risk Factor (covariates) 40

〈Table 3〉 Logistic Regression Analysis of Components for D.I.R.E.C.T Coding System 41

〈Table 4〉 Classification Score per Group 42

〈Table 5〉 Logistic Regression Analysis for Amputation in 5 Existing Classification System 43

〈Table 6〉 Diagnostic Performance of 5 Existing Classification System and DRIECT System 44

〈Figure 1〉 Diagnostic algorithm of DIRECT coding system. Adapted from Shin et al. D+WOUND SOLUTION 2014 :19. 32

〈Figure 2〉 Components of the DIRECT coding system. 33

〈Figure 3〉 Flowgram describing patient selection for prediction of LEA amputation risk factor of DFU 34

〈Figure 4〉 ROC curves of the DIRECT algorithm (Including DIRECT1 to 3) and five classification systems. ROC, receive operating characteristic 35

〈Figure 5〉 ROC curves of the Wagner, UT on wound depth, DEPA, and DIRECT3 system, which demonstrate high AUC values, are distinguished and highlighted. 36

〈Figure 6〉 Clinical application of DIRECT coding system. (A) DFU of the left foot with necrotic tissue in a 61-year-old male. According to the DIRECT1... 37