Methods: The National Societies for Emergency Medicine of Hong Kong, India, Japan, Malaysia, Philippines, Singapore, South Korea, Taiwan, Thailand and Turkey participated in the joint Japanese Association of Acute Medicine (JAAM) and Asian Conference of Emergency Medicine (ACEM) Special Symposium held in October 2013 at Tokyo, Japan. The findings are reviewed in this paper.
Results: Emergency medicine (EM) has over the years evolved into a distinct and recognized medical discipline requiring a unique set of cognitive, administrative and technical skills for managing all types of patients with acute illness or injury. EM has contributed to healthcare by providing effective, safe, efficient and cost-effective patient care. Integrated systems have developed to allow continuity of emergency care from the community into emergency departments. Structured training curriculum for undergraduates, and specialty training programs for postgraduates are in place to equip trainees with the knowledge and skills required for the unique practice of EM.
Conclusion: The practice of EM still varies among the Asian countries. However, as a region, we strive to continue in our efforts to develop the specialty and improve the delivery of EM.
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 <40 years, systolic blood pressure <100 mmHg, respiration rate >20/minute, pulse oximetry <94%, and levels of consciousness to pain or unresponsiveness. The AUROC in the derivation and validation cohorts was 0.767 and 0.782, respectively. The HL test revealed good calibration of the model (p = 0.906).
CONCLUSION: We established a prediction model using variables from the PATOS database and measured them immediately after EMS personnel arrived to predict EMS-witnessed TCA. The model allows prehospital medical personnel to focus on high-risk patients and promptly administer optimal treatment.