METHODS: We conducted a multinational retrospective cohort study involving adult trauma patients admitted to emergency departments in the included countries from 2016 to 2020. Prehospital and hospital data were reviewed from the Pan-Asia Trauma Outcomes Study database. Patients aged ≥18 years transported by emergency medical services were included. Patients lacking data regarding age, sex, physiological criteria, or injury severity scores were excluded. We examined the performance of sFTS in all age groups and fine-tuned physiological criteria to improve sFTS performance in identifying high-risk trauma patients in different age groups.
RESULTS: The sensitivity and specificity of the physiological and anatomical criteria for identifying major trauma (injury severity score ≥ 16) were 80.6% and 58.8%, respectively. The modified sFTS showed increased sensitivity and decreased specificity, with more pronounced changes in the young age group. Adding the shock index further increased sensitivity in both age groups.
CONCLUSIONS: sFTS using only physiological and anatomical criteria is suboptimal for Asian adult patients with trauma of all age groups. Adjusting the physiological criteria and adding a shock index as a triage tool can improve the sensitivity of severely injured patients, particularly in young age groups. A swift field triage process can maintain acceptable sensitivity and specificity in severely injured patients.
OBJECTIVE: To compare the ability of the prehospital GCS and GCS-M to predict 30-day mortality and severe disability in trauma patients.
DESIGN: We used the Pan-Asia Trauma Outcomes Study registry to enroll all trauma patients >18 years of age who presented to hospitals via emergency medical services from 1 January 2016 to November 30, 2018.
SETTINGS AND PARTICIPANTS: A total of 16,218 patients were included in the analysis of 30-day mortality and 11 653 patients in the analysis of functional outcomes.
OUTCOME MEASURES AND ANALYSIS: The primary outcome was 30-day mortality after injury, and the secondary outcome was severe disability at discharge defined as a Modified Rankin Scale (MRS) score ≥4. Areas under the receiver operating characteristic curve (AUROCs) were compared between GCS and GCS-M for these outcomes. Patients with and without traumatic brain injury (TBI) were analyzed separately. The predictive discrimination ability of logistic regression models for outcomes (30-day mortality and MRS) between GCS and GCS-M is illustrated using AUROCs.
MAIN RESULTS: The primary outcome for 30-day mortality was 1.04% and the AUROCs and 95% confidence intervals for prediction were GCS: 0.917 (0.887-0.946) vs. GCS-M:0.907 (0.875-0.938), P = 0.155. The secondary outcome for poor functional outcome (MRS ≥ 4) was 12.4% and the AUROCs and 95% confidence intervals for prediction were GCS: 0.617 (0.597-0.637) vs. GCS-M: 0.613 (0.593-0.633), P = 0.616. The subgroup analyses of patients with and without TBI demonstrated consistent discrimination ability between the GCS and GCS-M. The AUROC values of the GCS vs. GCS-M models for 30-day mortality and poor functional outcome were 0.92 (0.821-1.0) vs. 0.92 (0.824-1.0) ( P = 0.64) and 0.75 (0.72-0.78) vs. 0.74 (0.717-0.758) ( P = 0.21), respectively.
CONCLUSION: In the prehospital setting, on-scene GCS-M was comparable to GCS in predicting 30-day mortality and poor functional outcomes among patients with trauma, whether or not there was a TBI.