METHODS AND FINDINGS: We conducted a retrospective cohort study of trauma patients transported from the scene to hospitals by emergency medical service (EMS) from January 1, 2016, to November 30, 2018, using data from the Pan-Asia Trauma Outcomes Study (PATOS) database. Prehospital time intervals were categorized into response time (RT), scene to hospital time (SH), and total prehospital time (TPT). The outcomes were 30-day mortality and functional status at hospital discharge. Multivariable logistic regression was used to investigate the association of prehospital time and outcomes to adjust for factors including age, sex, mechanism and type of injury, Injury Severity Score (ISS), Revised Trauma Score (RTS), and prehospital interventions. Overall, 24,365 patients from 4 countries (645 patients from Japan, 16,476 patients from Korea, 5,358 patients from Malaysia, and 1,886 patients from Taiwan) were included in the analysis. Among included patients, the median age was 45 years (lower quartile [Q1]-upper quartile [Q3]: 25-62), and 15,498 (63.6%) patients were male. Median (Q1-Q3) RT, SH, and TPT were 20 (Q1-Q3: 12-39), 21 (Q1-Q3: 16-29), and 47 (Q1-Q3: 32-60) minutes, respectively. In all, 280 patients (1.1%) died within 30 days after injury. Prehospital time intervals were not associated with 30-day mortality. The adjusted odds ratios (aORs) per 10 minutes of RT, SH, and TPT were 0.99 (95% CI 0.92-1.06, p = 0.740), 1.08 (95% CI 1.00-1.17, p = 0.065), and 1.03 (95% CI 0.98-1.09, p = 0.236), respectively. However, long prehospital time was detrimental to functional survival. The aORs of RT, SH, and TPT per 10-minute delay were 1.06 (95% CI 1.04-1.08, p < 0.001), 1.05 (95% CI 1.01-1.08, p = 0.007), and 1.06 (95% CI 1.04-1.08, p < 0.001), respectively. The key limitation of our study is the missing data inherent to the retrospective design. Another major limitation is the aggregate nature of the data from different countries and unaccounted confounders such as in-hospital management.

METHODS: This retrospective study was conducted in the participating centers of the Pan-Asian Trauma Outcome Study from October 2015 to December 2020. Subjects who reported "school" as the site of injury were included. Major trauma was defined as an Injury Severity Score (ISS) value of ≥16.

RESULTS: In total, 1305 injury cases (1.0% of 127,715 events) occurred at schools. Among these, 68.2% were children. Unintentional injuries were the leading cause and intentional injuries comprised 7.5% of the cohort. Major trauma accounted for 7.1% of those with documented ISS values. Multivariable regression revealed associations between major trauma and factors, including age, intention of injury (self-harm), type of injury (traffic injuries, falls), and body part injured (head, thorax, and abdomen). Twenty-two (1.7%) died, with six deaths related to self-harm. Females represented 28.4% of injuries but accounted for 40.9% of all deaths.

CONCLUSIONS: In Asia, injuries at schools affect a significant number of children. Although the incidence of injuries was higher in males, self-inflicted injuries and mortality cases were relatively higher in females.

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.

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.

METHODS: Medical directors and emergency physicians at PATOS-participating hospitals in countries across the Asia Pacific were surveyed through a standardized questionnaire. General information, trauma care system data, and trauma emergency department (ED) outcomes at each hospital were collected by email and analyzed using descriptive statistics.

RESULTS: Survey data from 35 hospitals across 15 countries were collected from archived data between June 2014 and July 2015. Designated trauma centers were identified as the highest hospital level for trauma patients in 70% of surveyed countries. Half of the hospitals surveyed had special teams for trauma care, and almost all prepared activation protocol documents for these teams. Most hospitals offered specialized trauma education programs, and 72.7% of hospitals had a hospital-based trauma registry. The total number of trauma patients visiting the ED across 25 of the hospitals was 300,376. The overall survival-to-discharge rate was 97.2%; however, it varied greatly between 85.1% and 99.7%. The difference between survival-to-discharge rates of moderate and severe injury groups was highest in Taiwan (41.8%) and lowest in Thailand (18.6%).

METHODS: A total of 9,737 pediatric patients aged <18 years with unintentional injuries cared for at participating centers of the Pan-Asian Trauma Outcome Study (PATOS) from October 2015 to December 2020 were reviewed retrospectively. Patients were divided into two groups: those <8 and those ≥8 years of age. Variables such as patient demographics, injury epidemiology, Injury Severity Score (ISS), and prehospital care were collected. Injury severity and administered prehospital care stratified by gross national income were also analyzed.

RESULTS: Pediatric unintentional injuries accounted for 9.4% of EMS-transported trauma cases in the participating Asian centers, and the mortality rate was 0.88%. The leading cause of injury was traffic injuries in older children aged ≥8 years (56.5%), while falls at home were common among young children aged <8 years (43.9%). Compared with younger children, older children with similar ISS tended to receive more prehospital interventions. Uneven disease severity was found in that older children in lower-middle and upper-middle-income countries had higher ISS compared with those in high-income countries. The performance of prehospital interventions also differed among countries with different gross national incomes. Immobilizations were the most performed prehospital intervention followed by oxygen administration, airway management, and pain control; only one patient received prehospital thoracentesis. Procedures were performed more frequently in high-income countries than in upper-middle-income and lower-middle-income countries.

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).