학술논문
Development of a prediction model for emergency medical service witnessed traumatic out-of-hospital cardiac arrest: A multicenter cohort study
Document Type
article
Author
Shao-An Wang; Chih-Jung Chang; Shan Do Shin; Sheng-En Chu; Chun-Yen Huang; Li-Min Hsu; Hao-Yang Lin; Ki Jeong Hong; Sabariah Faizah Jamaluddin; Do Ngoc Son; T.V. Ramakrishnan; Wen-Chu Chiang; Jen-Tang Sun; Matthew Huei-Ming Ma; Participating Nation Investigators; Hideharu Tanaka; Bernadett Velasco; Jen Tang Sun; Pairoj Khruekarnchana; Saleh Fares; Participating Site Investigators; Ramana Rao; George P. Abraham; Mohd Amin Bin Mohidin; Al-Hilmi Saim; Lim Chee Kean; Cecilia Anthonysamy; Shah Jahan Din Mohd Yssof; Kang Wen Ji; Cheah Phee Kheng; Shamila bt Mohamad Ali; Periyanayaki Ramanathan; Chia Boon Yang; Hon Woei Chia; Hafidahwati Binti Hamad; Samsu Ambia Ismail; Wan Rasydan B. Wan Abdullah; Akio Kimura; Carlos D. Gundran; Pauline Convocar; Nerissa G. Sabarre; Patrick Joseph Tiglao; Kyoung Jun Song; Joo Jeong; Sung Woo Moon; Joo-yeong Kim; Won Chul Cha; Seung Chul Lee; Jae Yun Ahn; Kang Hyeon Lee; Seok Ran Yeom; Hyeon Ho Ryu; Su Jin Kim; Sang Chul Kim; Ray-Heng Hu; Ruei-Fang Wang; Shang-Lin Hsieh; Wei-Fong Kao; Sattha Riyapan; Parinya Tianwibool; Phudit Buaprasert; Osaree Akaraborworn; Omer Ahmed Al Sakaf; Le Bao Huy; Nguyen Van Dai
Source
Journal of the Formosan Medical Association, Vol 123, Iss 1, Pp 23-35 (2024)
Subject
Language
English
ISSN
0929-6646
Abstract
Background/Purpose: To develop a prediction model for emergency medical technicians (EMTs) to identify trauma patients at high risk of deterioration to emergency medical service (EMS)-witnessed traumatic cardiac arrest (TCA) on the scene or en route. Methods: We developed a prediction model using the classical cross-validation method from the Pan-Asia Trauma Outcomes Study (PATOS) database from 1 January 2015 to 31 December 2020. Eligible patients aged ≥18 years were transported to the hospital by the EMS. The primary outcome (EMS-witnessed TCA) was defined based on changes in vital signs measured on the scene or en route. We included variables that were immediately measurable as potential predictors when EMTs arrived. An integer point value system was built using multivariable logistic regression. The area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow (HL) test were used to examine discrimination and calibration in the derivation and validation cohorts. Results: In total, 74,844 patients were eligible for database review. The model comprised five prehospital predictors: age 20/minute, pulse oximetry