Background: Non-invasive mechanical ventilation (NIV) has become an alternative to an invasive artificial airway for the management of acute respiratory failure (ARF). NIV failure causes delayed intubation, which eventually has been associated with increased morbidity and mortality. This study aimed to develop the clinical scoring system of NIV failure in ARF patients. Methods: This study was a diagnostic, retrospectively cross-sectional, and exploratory model at the Emergency Medicine Department in Ramathibodi Hospital between February 2017 and December 2017. We included all of the acute respiratory failure patients aged > 18 years and received non-invasive ventilation (NIV). Clinical factors associated with NIV failure were recorded. The predictive model and prediction score for NIV failure were developed by multivariable logistic regression analysis. Result: A total of 329 acute respiratory failure patients have received NIV success (N = 237) and failure (N = 92). This study showed that NIV failure was associated with heart rate > 110 bpm, systolic BP < 110 mmHg, SpO2 < 90%, arterial pH < 7.30 and serum lactate. The clinical scores were classified into three groups: low, moderate, and high. Conclusion: We suggested that the novel clinical scoring of the NIV failure in this study may use as a good predictor for NIV failure in the emergency room.

Introduction: Emergency department (ED) revisits increase overcrowding and predicting which patients may need to revisit could increase patient safety. This study aimed to identify clinical variables that could be used to predict the probability of revisiting ED within 48 hours of discharge. Methods: A retrospective case-control study was conducted between July 2018 and January 2019 at the Emergency Medicine Department in Ramathi-bodi Hospital, Bangkok, Thailand. Patients who revisited the ED within 48 hours of discharge (case group) and patients who did not (control group) participated. The predictive factors for ED revisit were identified through multivariate logistic regression analysis. Results: The case group consisted of 372 patients, who revisited the ED within 48 hours, and the control group consisted of 1488 patients. The most common reason for revisiting the ED was recurring gastrointestinal illness, in 107 patients (28.76%). According to the multivariate data analysis, five factors influenced the probability of revisiting the ED: age of more than 60 years (p < 0.001, OR = 2.04, 95%CI: 1.51-2.77), initial Emergency Severity Index (ESI) triage level of 2 (p = 0.007, OR = 1.20, 95%CI: 0.93-1.56), ED stay duration of 4 hours or longer (p = 0.013, OR = 1.12, 95%CI: 0.87-1.44), body temperature of >= 37.5 degrees C on discharge (p = 0.034, OR = 1.34, 95%CI: 1.00-1.80), and pulse rate of less than 60 (OR = 1.55, 95%CI: 0.87-2.77) or more than 100 beats/minute (OR = 1.53, 95%CI: 1.10-2.11) (p = 0.011). Conclusion: According to the findings, the most important and independent predictive factor of ED revisit within 48 hours of discharge were, age >= 60 years, ESI triage level 2, ED length of stay >= 4 hours, temperature >= 37.5 C, and 60 > pulse rate >= 100 beats/minute.

Introduction: Prehospital trauma care includes on-scene assessments, essential treatment, and facilitating transfer to an appropriate trauma center to deliver optimal care for trauma patients. While the Simple Triage and Rapid Treatment (START), Revised Triage Sieve (rTS), and National Early Warning Score (NEWS) tools are user-friendly in a prehospital setting, there is currently no standardized on-scene triage protocol in Thailand Emergency Medical Service (EMS). Therefore, this study aims to evaluate the precision of these tools (SI, rSIG, and NEWS) in predicting the severity of trauma patients who are transferred to the emergency department (ED). Methods: This study was a retrospective cross-sectional and diagnostic research conducted on trauma patients transferred by EMS to the ED of Ramathibodi Hospital, a university-affiliated super tertiary care hospital in Bangkok, Thailand, from January 2015 to September 2022. We compared the on-scene triage tool (SI, rSIG, and NEWS) and ED triage tool (Emergency Severity Index) parameters, massive transfusion protocol (MTP), and intensive care unit (ICU) admission with the area under ROC (univariable analysis) and diagnostic odds ratio (multivariable logistic regression analysis). The optimal cut-off threshold for the best parameter was determined by selecting the value that produced the highest area under the ROC curve. Results: A total of 218 patients were traumatic patients transported by EMS to the ED, out of which 161 were classified as ESI levels 1– 2, while the remaining 57 patients were categorized as levels 3– 5 on the ESI triage scale. We found that NEWS was a more accurate triage tool to discriminate the severity of trauma patients than rSIG and SI. The area under the ROC was 0.74 (95% CI 0.70– 0.79) (OR 18.98, 95% CI 1.06– 337.25), 0.65 (95% CI 0.59– 0.70) (OR 1.74, 95% CI 0.17– 18.09) and 0.58 (95% CI 0.52– 0.65) (OR 0.28, 95% CI 0.04– 1.62), respectively (P-value < 0.001). The cut point of NEWS to discriminate ESI levels 1– 2 and levels 3– 5 was > 6 points. Conclusion: NEWS is the best on-scene triage screening tool to predict the severity at the emergency department, massive transfusion protocol (MTP), and intensive care unit (ICU) admission compared with other triage tools SI and rSIG.

Traumatic brain injury (TBI) is a major public health issue worldwide. A portable near-infrared spectroscopy (NIRS) is a non-invasive device to detect intracranial hematoma. The advantages of the NIRS include real time results and non-radiation exposure. However, sensitivity and specificity of the NIRS for intracranial hematoma are varied. This study aimed to evaluate the diagnostic properties of the NIRS in TBI patients to detect intracranial hematoma. This study was a diagnostic and prospective study conducted at the Emergency Department. The inclusion criteria were adult patients (age of 18 years or over) with moderate to high risk of all degrees of traumatic brain injury within 24 h after the injury. The primary endpoint of the study was a description of diagnostic properties of the NIRS compared with the CT brain. There were 47 patients enrolled in the study. Most of patients had Glasgow Coma Scale of 15 (44 patients; 93.62 %). Of those, 11 patients (23.40 %) had intracranial hematoma: subdural hematoma (n = 9), epidural hematoma (n = 1), intracerebral hematoma (n = 1), and subarachnoid hemorrhage (n = 3). One patient had subdural hematoma, epidural hematoma, intracerebral hematoma and subarachnoid hemorrhage. There were 31 patients had abnormal findings by the NIRS but only 11 patients had bleeding detected by the CT brain. There were 16 patients had negative results on both the NIRS and the CT brain. The sensitivity and specificity of the NIRS compared with the CT brain was 100 % and 44.4 %, respectively. The area under the ROC curve of the NIRS was 0.722. The median time to complete the NIRS examination was 3 min. In conclusion, the NIRS has high sensitivity and negative predictive value for intracranial hematoma detection in mild TBI patients with extra-axial hematomas.

Introduction: Disaster triage is a crucial competency for paramedics. Traditional training methods, such as lectures and tabletop exercises (TTx), may not provide immersive and high-pressure experience necessary for optimal skill development. Virtual reality (VR) is innovative, allowing trainees to engage in realistic triage simulations in a controlled, interactive environment. Objective: The study aimed to compare the effectiveness of VR-based triage training and traditional methods by assessing knowledge, learner motivation, and practical skills through pre-and post-tests, the ARCS model, and live simulations. Methods: This method-oriented, randomized study was conducted over a 2-week intervention among 83 paramedic students and compared traditional lecture-based (n = 41) with VR-based (n = 42) training for MCI triage education among paramedic students at the Faculty of Medicine, Ramathibodi Hospital, Mahidol University. Both groups attended lectures. Knowledge was assessed through validated pre- and post-tests in four domains: memory, comprehension, application and analysis. Learner motivation was evaluated using the ARCS model (Attention, Relevance, Confidence, Satisfaction), and practical skills were measured during live simulations, assessing time use and a validated accuracy score that included triage steps, proper sequencing, and the correctness of triage judgment. Results: Both groups demonstrated significant improvements in post-test knowledge scores. The VR group scored higher across all ARCS model dimensions: attention (4.78 vs. 4.17, p < 0.001), relevance (4.79 vs. 4.37, p < 0.001), confidence (4.74 vs. 4.24, p < 0.001), and satisfaction (4.71 vs. 4.34, p < 0.001). In the practical triage assessment, the VR group achieved higher accuracy in SORT triage (14.39 vs. 12.09, p = 0.001) than the traditional group. Conclusion: Both training methods effectively improved disaster triage knowledge and skills. However, the VR-based method significantly enhanced learner motivation and SORT triage accuracy, suggesting that VR may be a valuable alternative to traditional TTx in disaster triage training. Clinical trial number: TCTR20241105003. Registration Site: Thai Clinical Trials Registry. URL: https://www.thaiclinicaltrials.org/show/TCTR20241105003.