Clinical Utility of Abdominal-Peripheral Temperature Difference Measured via Infrared Thermography as an Objective Biomarker for Cold-Heat Pattern Identification

Objectives : To evaluate abdominal-peripheral acupoint temperature differences measured by infrared thermography (IRT) as objective biomarkers for Cold-Heat pattern identification.Methods : In this cross-sectional study, 1,045 adults (280 men, 765 women; mean age 42.7±10.5years) examined at Pusan National University Yangsan Hospital (2021∼2024) completed the Cold-Heat Pattern Identification Questionnaire (CHPIQ) and underwent IRT.After 15∼20 minutes of acclimation under standardized conditions (23∼ 25℃; 30∼75% relative humidity), skin temperatures at the abdominal acupoint (CV12) and peripheral acupoints (PC8 and ST42) were recorded.Regions of interest (ROIs) with a 5-pixel radius were automatically extracted using Mediapipe PoseLandmarker and OpenCV, and mean temperatures were computed.∆T values were calculated as the temperature difference between CV12 and the peripheral acupoints.Group differences (Cold vs Heat) were analysed by independent-samples t-tests.Multivariable logistic regression evaluated the predictive value of each temperature and ∆T variable, and receiver-operating characteristic (ROC) curve analysis quantified discriminative performance (area under the curve, AUC) by sex.Results : In both sexes, peripheral temperatures at PC8 and ST42 were significantly higher in the Heat group (p＜0.001),while CV12 did not differ.∆T was greater in the Cold group (men: 1.5±2.0 vs. 0.3±1.5℃;women: 1.9±2.0 vs. 0.9±1.7℃;p＜0.001).After adjustment for age and body-mass index, men's PC8 temperature showed strong Heat-pattern prediction (OR 1.262; p=0.001) with AUC 0.864, while ∆T(CV12-PC8) predicted Cold pattern (OR 0.702; p=0.001) with AUC 0.859.In women, PC8 temperature predicted Heat pattern (OR 1.202; p＜0.001;AUC 0.784), and ∆T (CV12-PC8) predicted Cold pattern (OR 0.810; p＜0.001;AUC 0.774).Sequential adjustment for age and BMI steadily improved AUCs for both absolute and ∆T metrics.Conclusions : Abdominal-peripheral ∆T measured by IRT, alongside absolute peripheral temperatures, offers objective, reproducible biomarkers for Cold-Heat pattern identification that complement the CHPIQ.Both the absolute temperature indicators and the temperature-difference indicators (e.g., ∆T (CV12-PC8), ∆T (CV12-ST42)) retained high discriminative performance after full covariate adjustment.Future studies should adopt machine-learning models and longitudinal multi-centre designs to refine predictive accuracy and externally validate these biomarkers.