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Cold-Heat and Excess-Deficiency Pattern Identification Based on Questionnaire, Pulse, and Tongue in Cancer Patients: A Feasibility Study

Article information

J Korean Med. 2021;42(1):1-11
Publication date (electronic) : 2021 March 01
doi : https://doi.org/10.13048/jkm.21001
Yujin Choi1,†orcid_icon, Soo-Dam Kim2,†orcid_icon, Ojin Kwon1orcid_icon, Hyo-Ju Park1orcid_icon, JiHye Kim1orcid_icon, Woosu Choi3orcid_icon, Myung-Hyun Ko2orcid_icon, Su-Jeung Ha2orcid_icon, Si-Yeon Song2orcid_icon, So-Jung Park2orcid_icon, Hwa-Seung Yoo4,orcid_icon, Mi-Kyung Jeong1,orcid_icon
1Clinical Medicine Division, Korea Institute of Oriental Medicine
2East West Cancer Center, Daejeon Korean Medicine Hospital of Daejeon University
3Future Medicine Division, Korea Institute of Oriental Medicine
4East West Cancer Center, Seoul Korean Medicine Hospital of Daejeon University
Correspondence to: 유화승 서울시 송파구 법원로 11길 32 대전대학교 서울한방병원 Tel：+82-2-2222-8100, Fax：+82-2-2222-8111, E-mail: altyhs@dju.kr
Correspondence to: 정미경 대전광역시 유성구 유성대로 1672 한국한의학연구원 임상의학부 Tel：+82-42-868-9475, Fax：+82-42-869-2724, E-mail: oiny2000@kiom.re.kr
†

Y Choi and SD Kim contributed equally this work

Received 2020 September 01; Revised 2020 October 27; Accepted 2020 November 12.

Abstract

Objectives

This pilot study aimed to evaluate the agreement between traditional face-to-face Korean medicine (KM) pattern identification and non-face-to-face KM pattern identification using the data from related questionnaires, tongue image, and pulse features in patients with cancer.

Methods

From January to June 2020, 16 participants with a cancer diagnosis were recruited at the one Korean medicine hospital. Three experienced Korean medicine doctors independently diagnosed the participants whether they belong to the cold pattern or not, heat pattern or not, deficiency pattern or not, and excess pattern or not. Another researcher collected KM pattern related data using questionnaires including Cold-Heat Pattern Identification (CHPI), tongue image analysis system, and pulse analyzer. Collected KM pattern related data without participants’ identifier was provided for the three Korean medicine doctors in random order, and non-face-to-face KM pattern identification was carried out. The kappa value between face-to-face and non-face-to-face pattern identification was calculated.

Results

From the face-to-face pattern identification, there were 13/3 cold/non-cold pattern, 4/12 heat/non-heat pattern, 14/2 deficiency/non-deficiency pattern, and 0/16 excess/non-excess pattern participants. In cold/non-cold pattern, kappa value was 0.455 (sensitivity: 0.85, specificity: 0.67, accuracy: 0.81). In heat/non-heat pattern, the kappa value was 0.429 (sensitivity: 0.75, specificity: 0.72, accuracy: 0.75). The kappa value of deficiency/non-deficiency and excess/non-excess pattern was not calculated because of the few participants of non-deficiency, and excess pattern.

Conclusions

The agreement between traditional face-to-face pattern identification and non-face-to-face pattern identification seems to be moderate. The non-face-to-face pattern identification using questionnaires, tongue, and pulse features may feasible for the large clinical study.

Keywords: Pattern identification; Syndrome differentiation; Cold-Heat pattern; Deficiency-Excess pattern; Telemedicine; Non-face-to-face pattern identification

General Characteristics of the Participants

The Pulse and Tongue Features and Questionnaire Score according to Face-To-Face (FTF) Cold-Heat Pattern Identification

The Agreement Between Face-To-Face (FTF) Pattern Identification and CHPI Questionnaire

The Agreement between Face-To-Face (FTF) and non FTF Pattern Identification

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Article information Continued

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Table 1

General Characteristics of the Participants

Male (N=4) Female (N=12) Total (N=16)
Age (year) 58.5 ± 8.50 54.42 ± 11.82 55.44 ± 10.97
Age Group, n (%)
 ~39 - 1 (8) 1 (6)
 40~49 1 (25) 3 (25) 4 (25)
 50~59 1 (25) 4 (33) 5 (31)
 60~69 2 (50) 2 (17) 4 (25)
 70~79 - 2 (17) 2 (13)
Height (cm) 168.5 ± 9.47 158.36 ± 4.69 160.89 ± 7.39
Weight (kg) 65.65 ± 14.53 54.35 ± 6.99 57.18 ± 10.18
Cancer Type, n (%)
 Breast Cancer - 5 (42) 5 (31)
 Colon Cancer - 2 (17) 2 (13)
 Gastric Cancer 1 (25) 1 (8) 2 (13)
 Other Cancer* 3 (75) 4 (33) 7 (44)
Treatment History, n (%)
 Surgery 1 (25) 10 (83) 11 (69)
 Chemotherapy 2 (50) 7 (58) 9 (56)
 Radiation - 1 (8) 1 (6)

Data are presented as n (%) or mean ± standard deviation.

*

Other cancer includes: Prostate cancer, Thyroid cancer, Ampullar of vater cancer, lymphoma, Endometrial cancer, Lung cancer, Uterine sarcoma.

Table 2

The Pulse and Tongue Features and Questionnaire Score according to Face-To-Face (FTF) Cold-Heat Pattern Identification

Cold Heat
Yes (N=13) No (N=3) P value Yes (N=4) No (N=12) P value
Sex 0.999 0.505
 Male 3 (23.1) 1 (33.3) 2 (50.0) 2 (16.7)
 Female 10 (76.9) 2 (66.7) 2 (50.0) 10 (83.3)
Age 57.7 ± 10.7 45.7 ± 6.1 0.086 48.8 ± 7.9 57.7 ± 11.2 0.166
BMI 21.6 ± 1.5 22.0 ± 6.2 0.947 22.3 ± 4.4 21.5 ± 1.5 0.765
Pulse Features
SBP 125.8 ± 10.5 107.5 ± 7.8 0.035 117.0 ± 17.3 125.0 ± 10.5 0.312
DBP 78.5 ± 10.7 61.5 ± 4.9 0.050 69.3 ± 14.0 77.9 ± 11.0 0.268
Pulse rate 77.4 ± 11.4 85.5 ± 7.8 0.354 88.3 ± 7.4 76.0 ± 10.7 0.084
Pulse size 123.8 ± 23.3 120.0 ± 14.1 0.827 130.0 ± 20.0 121.7 ± 22.9 0.575
Pulse depth 76.9 ± 21.4 90.0 ± 14.1 0.425 80.0 ± 20.0 78.3 ± 21.7 0.906
Pulse shape 93.1 ± 11.8 105.0 ± 21.2 0.241 103.3 ± 15.3 92.5 ± 12.2 0.209
Tongue Features
Tongue body color 0.330 0.202
 Pale 1 (7.7) 0 (0.0) 0 (0.0) 1 (8.3)
 Light red 7 (53.8) 3 (100.0) 4 (100.0) 6 (50.0)
 Red 5 (38.5) 0 (0.0) 0 (0.0) 5 (41.7)
Tongue coating 0.986 0.641
 Thin 4 (30.8) 1 (33.3) 2 (50.0) 3 (25.0)
 Normal 4 (30.8) 1 (33.3) 1 (25.0) 4 (33.3)
 Thick 5 (38.5) 1 (33.3) 1 (25.0) 5 (41.7)
Tongue coating color 0.999 0.999
 Normal 13 (100.0) 3 (100.0) 4 (100.0) 12 (100.0)
 Yellow 0 (0.0) 0 (0.0) 0 (0.0) 0 (0.0)
Tooth mark 0.620 0.999
 Normal 9 (69.2%) 1 (33.3%) 2 (50.0%) 8 (66.7%)
 Yes 4 (30.8%) 2 (66.7%) 2 (50.0%) 4 (33.3%)
Questionnaires*
Cold 27.2 ± 4.8 19.7 ± 5.5 0.032 20.8 ± 5.0 27.4 ± 4.9 0.034
Heat 16.2 ± 4.1 24.0 ± 2.6 0.009 23.5 ± 2.4 15.8 ± 3.9 0.003
Deficiency 84.6 ± 17.9 79.0 ± 8.7 0.611 81.2 ± 8.4 84.3 ± 18.6 0.758
Excess 68.5 ± 16.3 66.7 ± 10.1 0.860 68.8 ± 9.3 67.9 ± 16.9 0.928
Qi-De 12.3 ± 4.8 12.0 ± 3.0 0.918 12.5 ± 2.6 12.2 ± 5.0 0.902
Blood-De 7.8 ± 2.4 6.0 ± 1.7 0.23 6.5 ± 1.7 7.8 ± 2.5 0.340
Yin-De 7.0 [6.0; 9.0] 6.0 [5.0; 7.0] 0.191 6.0 ± 1.6 8.2 ± 2.2 0.091
Yang-De 7.7 ± 2.5 4.0 ± 1.7 0.031 4.5 ± 1.7 7.8 ± 2.6 0.031

Data are presented as n (%) or mean ± standard deviation.

FTF: Face to face

*

Questionnaires: Cold (8 items), Heat (7 items), Deficiency (20 items), Excess (20 items), Qi-Deficiency (5 items), Blood-Deficiency (3 items), Yin-Deficiency (4 items), Yang-Deficiency (3 items)

Table 3

The Agreement Between Face-To-Face (FTF) Pattern Identification and CHPI Questionnaire

CHPI Yes No Sensitivity Specificity Accuracy Kappa
FTF
Cold Yes 11 2 0.85 0.67 0.81 0.455
No 1 2
Heat Yes 4 0 1.00 0.83 0.88 0.714
No 2 10

CHPI: Cold-Heat Pattern Identification (15 items), FTF: Face to face

Table 4

The Agreement between Face-To-Face (FTF) and non FTF Pattern Identification

Non FTF Yes No Sensitivity Specificity Accuracy Kappa
FTF
Cold Yes 11 2 0.85 0.67 0.81 0.455
No 1 2
Heat Yes 3 1 0.75 0.75 0.75 0.429
No 3 9
Deficiency Yes 14 0 1.00 0.00 0.88 -
No 2 0
Excess Yes 0 0 - 0.69 0.69 -
No 5 11
Qi-Deficiency Yes 12 0 1.00 0.50 0.88 0.600
No 2 2
Yin-Deficiency Yes 5 2 0.71 0.78 0.71 0.492
No 2 7

FTF: Face to face