Whether rapid transportation can benefit patients with trauma remains controversial. We determined the association between prehospital time and outcome to explore the concept of the “golden hour” for injured patients. 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. Longer prehospital time was not associated with an increased risk of 30-day mortality, but it may be associated with increased risk of poor functional outcomes in injured patients. This finding supports the concept of the “golden hour” for trauma patients during prehospital care in the countries studied.

OBJECTIVES: Following current cardiopulmonary resuscitation (CPR) guidelines, which recommend chest compressions at “the center of the chest,” ~50% of patients experiencing out-of-hospital cardiac arrest (OHCA) undergo aortic valve (AV) compression, obstructing blood flow. We used resuscitative transesophageal echocardiography (TEE) to elucidate the impact of uncompressed vs. compressed AV on outcomes of adult patients experiencing OHCA. DESIGN: Prospective observational cohort study. SETTING: Single center. PATIENTS: This study included adult OHCA patients undergoing resuscitative TEE in the emergency department. Patients were categorized into AV uncompressed or AV compressed groups based on TEE findings. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary outcome was sustained return of spontaneous circulation (ROSC). The secondary outcomes included end-tidal co ₂ (Etco ₂) during CPR, any ROSC, survival to ICU and hospital discharge, post-resuscitation withdrawal, and favorable neurologic outcomes at discharge. Additional analyses on intra-arrest arterial blood pressure (ABP) were also conducted. The sample size was pre-estimated at 37 patients/group. From October 2020 to January 2023, 76 patients were enrolled, 39 and 37 in the AV uncompressed and AV compressed groups, respectively. Intergroup baseline characteristics were similar. Compared with the AV compressed group, the AV uncompressed group had a higher probability of sustained ROSC (53.8% vs. 24.3%; adjusted odds ratio [aOR], 4.72; p = 0.010), any ROSC (56.4% vs. 32.4%; aOR, 3.30; p = 0.033), and survival to ICU (33.3% vs. 8.1%; aOR, 6.74; p = 0.010), and recorded higher initial diastolic ABP (33.4 vs. 11.5 mm Hg; p = 0.002) and a larger proportion achieving diastolic ABP greater than 20 mm Hg during CPR (93.8% vs. 33.3%; p < 0.001). The Etco ₂, post-resuscitation withdrawal, and survival to discharge revealed no significant intergroup differences. No patients were discharged with favorable neurologic outcomes. Uncompressed AV seemed critical for sustained ROSC across all subgroups. CONCLUSIONS: Absence of AV compression during OHCA resuscitation is associated with an increased chance of ROSC and survival to ICU. However, its effect on long-term outcomes remains unclear.

Background: The shock index (SI) predicts short-term mortality in trauma patients. Other shock indices have been developed to improve discriminant accuracy. The authors examined the discriminant ability of the SI, modified SI (MSI), and reverse SI multiplied by the Glasgow Coma Scale (rSIG) on short-term mortality and functional outcomes. Methods: The authors evaluated a cohort of adult trauma patients transported to emergency departments. The first vital signs were used to calculate the SI, MSI, and rSIG. The areas under the receiver operating characteristic curves and test results were used to compare the discriminant performance of the indices on short-term mortality and poor functional outcomes. A subgroup analysis of geriatric patients with traumatic brain injury, penetrating injury, and nonpenetrating injury was performed. Results: A total of 105 641 patients (49±20 years, 62% male) met the inclusion criteria. The rSIG had the highest areas under the receiver operating characteristic curve for short-term mortality (0.800, CI: 0.791–0.809) and poor functional outcome (0.596, CI: 0.590–0.602). The cutoff for rSIG was 18 for short-term mortality and poor functional outcomes with sensitivities of 0.668 and 0.371 and specificities of 0.805 and 0.813, respectively. The positive predictive values were 9.57% and 22.31%, and the negative predictive values were 98.74% and 89.97%. rSIG also had better discriminant ability in geriatrics, traumatic brain injury, and nonpenetrating injury. Conclusion: The rSIG with a cutoff of 18 was accurate for short-term mortality in Asian adult trauma patients. Moreover, rSIG discriminates poor functional outcomes better than the commonly used SI and MSI.

Background and Objectives: Systemic analgesics, including opioids, are commonly used for acute pain control in traumatic hip fracture patients in the emergency department (ED). However, their use is associated with high rates of adverse reactions in the geriatric population. As such, the aim of this study was to investigate the impact of lidocaine-based single-shot ultrasound-guided femoral nerve block (USFNB) on the standard care for acute pain management in geriatric patients with traumatic hip fracture in the ED. Methods: This retrospective, single-center, observational study included adult patients aged ≥60 years presenting with acute traumatic hip fracture in the ED between 1 January 2017 and 31 December 2020. The primary outcome measure was the difference in the amount of opioid use, in terms of morphine milligram equivalents (MME), between lidocaine-based single-shot USFNB and standard care groups. The obtained data were evaluated through a time-to-event analysis (time to meaningful pain relief), a time course analysis, and a multivariable analysis. Results: Overall, 607 adult patients (USFNB group, 66; standard care group, 541) were included in the study. The patients in the USFNB group required 80% less MME than those in the standard care group (0.52 ± 1.47 vs. 2.57 ± 2.53, p < 0.001). The multivariable Cox proportional hazards regression models showed that patients who received USFNB achieved meaningful pain relief 2.37-fold faster (hazard ratio (HR) = 2.37, 95% confidence intervals (CI) = 1.73–3.24, p < 0.001). Conclusions: In geriatric patients with hip fractures, a lidocaine-based single-shot USFNB can significantly reduce opioid consumption and provide more rapid and effective pain reduction.

Prehospital spinal immobilization is a widely used procedure in the emergency medical service (EMS) system worldwide, while the incidence of patients with spinal injury (SI) is relatively low, and unnecessary prehospital spinal immobilization is associated with patient complications. This study aimed to determine the association between prehospital spine immobilization and favorable functional outcomes at hospital discharge among trauma patients with SI. We conducted a retrospective cohort study using the Pan-Asia Trauma Outcomes Study (PATOS) registry data from January 1, 2016, to November 30, 2018. A total of 759 patients with SI were enrolled from 43,752 trauma patients in the PATOS registry during the study period. The subjects had a median age of 58 years (Q1–Q3, 41–72), and 438 (57.7%) patients had prehospital spine immobilization. Overall, prehospital spinal immobilization was not associated with favorable functional outcomes at discharge in multivariable logistic regression (aOR 1.06; 95% CI 0.62–1.81, p = 0.826). However, in the subgroup of cervical SI, prehospital spinal immobilization was associated with favorable functional outcomes at discharge (aOR 3.14; 95% CI 1.04–9.50; p = 0.043). Therefore, we suggest that paramedics should be more careful when determining the presence of a cervical SI and should apply full spine immobilization if possible.

Background: Early recognition of severely injured patients in prehospital settings is of paramount importance for timely treatment and transportation of patients to further treatment facilities. The dispatching accuracy has seldom been addressed in previous studies. Objective: In this study, we aimed to build a machine learning–based model through text mining of emergency calls for the automated identification of severely injured patients after a road accident. Methods: Audio recordings of road accidents in Taipei City, Taiwan, in 2018 were obtained and randomly sampled. Data on call transfers or non-Mandarin speeches were excluded. To predict cases of severe trauma identified on-site by emergency medical technicians, all included cases were evaluated by both humans (6 dispatchers) and a machine learning model, that is, a prehospital-activated major trauma (PAMT) model. The PAMT model was developed using term frequency–inverse document frequency, rule-based classification, and a Bernoulli naïve Bayes classifier. Repeated random subsampling cross-validation was applied to evaluate the robustness of the model. The prediction performance of dispatchers and the PAMT model, in severe cases, was compared. Performance was indicated by sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Results: Although the mean sensitivity and negative predictive value obtained by the PAMT model were higher than those of dispatchers, they obtained higher mean specificity, positive predictive value, and accuracy. The mean accuracy of the PAMT model, from certainty level 0 (lowest certainty) to level 6 (highest certainty), was higher except for levels 5 and 6. The overall performances of the dispatchers and the PAMT model were similar; however, the PAMT model had higher accuracy in cases where the dispatchers were less certain of their judgments. Conclusions: A machine learning–based model, called the PAMT model, was developed to predict severe road accident trauma. The results of our study suggest that the accuracy of the PAMT model is not superior to that of the participating dispatchers; however, it may assist dispatchers when they lack confidence while making a judgment.