การแยกผขบขและผซอนรถจกรยานยนตจากลกษณะการบาดเจบในจงหวดลำปาง และจงหวดใกลเคยง กำพล เครอคำขาว พ.บ.*, ธรดนย จนตจระนนท**, นนทร คมวชรพงศ**,วรชาต กนธยะ**, ขวญชนก แสนเตชะ** *กลมงานนตเวช โรงพยาบาลลำปาง อำเภอเมอง จงหวดลำปาง 52000 **นกศกษาแพทย ศนยแพทยศาสตรศกษาชนคลนก อำเภอเมอง จงหวดลำปาง 52000 Abstract: Differentiation between Motorcycle Riders and Passengers by Injury Characteristics in Lampang and Neighbouring Provinces Kluakamkao G, Jinjiranun T, Komwatcharapong N, Kantiya W, Saentecha K, *Forensic Medicine group, Lampang Hospital, Mueang Lampang, Lampang, 52000 **Medical student, Lampang Medical Educational Center Mueang Lampang, Lampang, 52000 (E-mail: kkamkao@gmail.com) Background: Motorcycle accidents (MCA) occur very frequently and the numbers are increasing every year. Differentiation between rider and passenger of MCA victims can be important, although this is not possible in many cases which can affect the outcome of the case and the compensation by the insurance company. Knowledge about the comparison of rider and passenger injury characteristics in Thailand is limited. Objective: To compare rider and passenger MCA injury characteristics recorded at Lampang Hospital for admissions and deaths. Method: This retrospective cross-sectional analysis studied 908 MCA victims from January 2016 to December 2017. Data were collected from medical records and autopsies at Lampang Hospital and analyzed, comparing the characteristics of injuries in riders and passengers by multivariate logistic regression and ROC curve analysis. Results: The mean age was 35±19.56 years. Most of the riders were male (70.6%). The mean of The Glasgow Coma Scale in riders was lower (13.68 vs. 14.22, p = 0.023), and the mean of length of stay was longer than in passengers. Characteristics of the injuries in riders were significantly different from those in passengers, including injury to the elbow and forearm, injury to the wrist and hand, open wound of the head, fracture of the skull, facial bones, intracranial injury and any bone fracture. An analysis by multivariate logistic regression and backward elimination found four predictive factors, including male gender (AOR = 2.3, 95% CI 1.7-3.3, P-value < 0.001), elbow and forearm injury (AOR = 1.7, 95% CI 1.1-2.6, P-value=0.018), open wounds of the head (AOR = 1.9, 95%CI 1.2-2.8, P-value = 0.004) and any bone fracture (AOR = 1.6, 95% CI 1.2-2.3, P-value = 0.003). The predictive power to differentiate the rider is 67.03% (ROC area = 0.6703). Conclusion: The results suggest that predictive factors to identify the riders in a MCA could be male gender, elbow and forearm injury, open wound of the head and any bone fracture.