In traumatic mass casualty incidents (MCIs), accurate triage is essential for prioritizing care and managing resources effectively. This study assesses the accuracy of the START (Simple Triage and Rapid Treatment) method across different responder variables, including occupation, experience, gender, and unit. Additionally, it compares the accuracy rates for each triage category and the time spent. The study further evaluates the execution rate of critical interventions, such as hemorrhage control and airway opening, which are essential steps within the START method.

This study utilized AI-generated realistic images of injured patients to create a high-fidelity simulation environment. Participants included physicians, nurses, and emergency medical technicians (EMTs) with varying levels of experience (<2 years, 2-5 years, >5 years) and from different units (emergency department, non emergency, and fire stations). During the simulation, evaluators interacted face-to-face with participants, acting as standardized patients (SPs) to support the triage decision-making process. Participants assessed 30 simulated patients within a 30-minute timeframe, making triage color judgments based on START criteria. Bleeding control materials and nasopharyngeal airways were provided for simulated interventions.

On average, participants correctly assessed 28.04 cases, achieving a mean accuracy rate of 93.71%. The average time spent on triage was 845.28 seconds. Triage accuracy by color category was as follows: green (94%), yellow (96%), red (89%), and black (100%). Analysis by occupation and experience indicated that experienced participants and those in emergency-related roles performed more accurately, particularly in the red and black categories.

This study highlights variability in START triage accuracy based on responder occupation and experience. The use of AI-generated injury images facilitated realistic training, suggesting that such simulations could enhance competency in triage skills, especially in hemorrhage and airway management. Enhanced training for responders from non-emergency units or with limited experience may lead to more consistent triage accuracy and improved MCI response.

Hualien County, stretching 137.5 kilometers, is characterized by mountainous terrain that complicates external transportation. Medical resources are mainly concentrated in northern Hualien, and disaster relief efforts face huge challenges. To this end, the Hualien Health Bureau established the Hualien Disaster Medical Assistance Team (DMAT) and developed the mobile application system iDMAT. The team collaborates closely with the Fire Department and receives logistical support from the NGO Tzu Chi Foundation to ensure swift and effective rescue operations.

1. Inter-agency Collaboration: Hualien DMAT is composed of medical and administrative staff from eight hospitals and works jointly with the Fire Department. EMTs arrive at the disaster scene first, setting up casualty collection points in cold zones. Hualien DMAT’s advance team then joined them to enhance patient care. Tzu Chi Foundation maintains logistics. 2. DMAT Advance Team: This team consists of one physician, two nurses, and two administrative staff members. They can quickly reach the disaster scene and initiate preliminary rescue actions, meeting the flexible needs of multi-site disasters. 3. iDMAT Development: DMAT members use the iDMAT APP to log disaster assessments and patient information in real-time. By scanning patient wristband QR codes, teams track triage, treatment, and transfer progress. All data is uploaded to the cloud, ensuring information accuracy and continuity.

During the 2021 Taroko train accident, the 2022 Taitung earthquake, and the 2024 Hualien 0403 earthquake, the DMAT advance team swiftly conducted on-site assessments, reporting directly to the Health Bureau via iDMAT. This real-time data sharing enables disaster relief decisions to be made promptly, while hospitals receive patient updates in advance, greatly enhancing treatment efficiency.

Hualien’s integrated model of inter-agency collaboration and iDMAT application reduces response times and ensures continuous patient care, alleviating healthcare provider burdens. This model effectively improves disaster response capability and highlights the value of real-time information management in disaster relief.

Effective disaster medical response hinges on timely data management and efficient resource allocation. The Hualien Disaster Medical Assistance Team (DMAT) in Taiwan functions as a mobile emergency department during disasters, integrating resources from health bureaus, emergency centers, hospitals, and private organizations. Previous disaster responses revealed significant challenges in data capture and real-time management; reliance on frequent calls and messages led to information errors, overburdened medical staff, and diminished rescue efficiency.

To address these issues, Hualien DMAT developed the iDMAT system, a digital platform designed to simplify medical record keeping and data management during disaster response. The user operates the application downloaded on the mobile phone. Feedback and operational data from users have been collected during exercises since 2023 and during the Hualien earthquake on April 3, 2024.

Implementation of the iDMAT system significantly improved operational efficiency. The team members reduced the average medical record completion time from 5.89 minutes (paper-based) to 2.68 minutes, achieving a 45% reduction. Approximately 78.57% of records were completed within 2–3 minutes. Data integration time decreased dramatically from 35.91 minutes to 6.80 minutes, with 70% of cases integrated within 3 minutes—a fivefold increase in efficiency.

By providing accurate and timely data to government agencies, the iDMAT system enhanced on-site medical care and resource allocation, facilitating rapid decision-making and resource deployment. These improvements led to better patient outcomes and reduced mortality during disasters. The system is scalable to other out-of-hospital care scenarios, such as major accidents and large-scale events. Future developments include integrating international standards like FHIR to promote cross-border collaboration and establishing a seamless care continuum among hospitals, fire departments, and ambulances.

The impact of inter-hospital transfer before endovascular thrombectomy (EVT) on short-term outcomes has been reported, but its effect on long-term outcomes remains unclear. We examined long-term clinical outcomes after EVT, stratified by whether patients underwent inter-hospital transfer.

We conducted a population-based cohort study using linked administrative data from Ontario, Canada (2017–2023). We included all community-dwelling residents hospitalized with acute ischemic stroke who received EVT. Inter-hospital transfer was defined as any transfer from a non-comprehensive stroke center (CSC) to a CSC before EVT. The primary outcome was all-cause mortality at maximum follow-up, assessed using propensity score-weighted hazard ratios.

Of 68523 ischemic stroke patients, 5394 (7.9%) underwent EVT, with 42.9% transferred before EVT. Direct-to-CSC patients were older, had higher rates of atrial fibrillation and dyslipidemia and were more likely to reside in urban areas. Propensity score-weighted analysis comparing transferred versus direct-to-CSC patients showed no difference in all-cause mortality, but the hazard ratio varied over time, violating the proportional hazards assumption. Transfer was associated with higher early mortality than direct-to-CSC, which declined over time, with mortality lower after 6.3 months, remaining below 1 over prolonged follow-up out to 34.6 months. Transferred patients were more likely to be admitted to long-term care (aHR 1.17, 95% CI: 1.03–1.33), but there was no significant difference in recurrent stroke.

Nearly half of EVT patients underwent inter-hospital transfer, which showed a time-varying association with all-cause mortality, with early risk that attenuated after 6.3 months and reversed over time.

This study aimed to develop a disaster triage training program designed to enhance knowledge, skills, and resilience for disasters among nurses.

A randomized controlled trial was conducted at two government hospitals in Indonesia. One hundred and eight nurses were randomly assigned in equal numbers to the experimental and control groups. The experimental group received a 4-hour triage training focused on mass casualty incidents. Disaster triage knowledge, skills, and resilience were assessed at three time points: before, immediately after, and 1 month following the intervention. Generalized Estimating Equations were used to evaluate the effectiveness of the training program.

The results of this study revealed that nurses in the experimental group showed significantly greater improvements in disaster triage knowledge, skills, and resilience compared to those in the control group at 2 post-test time points. In addition, feedback from trained nurses emphasized its relevance to local disaster scenarios, such as earthquakes and floods, and highlighted the value of hands-on practice and easily accessible learning materials.

The study demonstrates that disaster triage training can effectively enhance nurses’ preparedness for disasters. It is recommended that health care institutions integrate disaster-related content into regular on-the-job training programs for nurses and assess its effectiveness.

Patients with stroke or transient ischemic attack (TIA) are at high early risk of mortality and morbidity. Current risk prediction tools focus on patients after hospital discharge but not on those surviving to outpatient follow-up. We examined whether demographic and medical history data could predict 1-year stroke recurrence and mortality, among those discharged alive and event-free for 90 days after stroke and 1 day after TIA.

Data were obtained from the Ontario Stroke Registry (13,848 stroke and 13,059 TIA patients) and linked to administrative databases. Two-thirds of each cohort were used for model derivation and one-third for validation. Multivariable regression models were used to predict stroke recurrence and all-cause mortality.

There were 238 (2.71%) recurrent strokes in the ischemic stroke and 298 (3.44%) in the TIA cohorts at one year. Increasing age and previous stroke/TIA were associated with an increased risk of recurrent stroke in both cohorts. A higher modified Rankin Scale and diabetes were associated with an increased risk of recurrent stroke in the stroke cohort and heart failure, smoking and discharge location in the TIA cohort. Time-dependent areas under the curve were modest, 0.59 (0.54–0.64) and 0.59 (0.55–0.64) for the stroke and TIA validation cohorts, respectively. C-statistics from derivation and validation cohorts for mortality ranged from 0.74–0.78.

The predictive accuracy of the models was quite low after accounting for several risk factors. Additional risk factors associated with stroke recurrence for people seen in outpatient stroke clinics, and innovative approaches to individualized secondary prevention are needed.

Transoral robotic surgery has gained much recognition in the surgical management of obstructive sleep apnoea, allowing for improved surgical access and precise dissection around the narrow surgical field. However, it is associated with a steeper learning curve and may give rise to significant morbidity especially amongst less experienced surgeons.

Through a comprehensive literature search, this review summarises patient selection for transoral robotic surgery as well as peri-operative considerations and management.

Apart from technical mastery, successful transoral robotic surgery require for the surgeon to be proficient with navigating the entire care continuum beginning with patient selection to management of post-operative complications.

Transoral robotic surgery remains a promising tool for surgical treatment of patients with obstructive sleep apnoea. This review provides an overview of the surgical application of transoral robotic surgery in obstructive sleep apnoea, together with practical guidance for the sleep surgeon.

CD33 has been implicated in the pathogenesis of Alzheimer’s disease primarily through its role in inhibiting the clearance of beta-amyloid (Aβ). However, genetic studies yield mixed results and it is unclear whether the impact of CD33 is specific to Alzheimer’s disease or related to broader neurodegenerative processes. Interestingly, CD33 has also been shown to interact with the hepatitis B (HBV) and C viruses (HCV).

This study aims to investigate the effects of CD33 single-nucleotide polymorphisms (SNPs) on cognitive functions across diverse populations, including healthy controls, individuals with chronic HBV or HCV and those diagnosed with Parkinson’s disease.

We genotyped CD33 SNPs in 563 participants using the Affymetrix platform. Participants’ cognitive functions were cross-sectionally assessed using a neuropsychological test battery spanning six domains.

Our analysis revealed that CD33 SNP variations had no significant cognitive impact on healthy individuals or Parkinson’s disease patients. However, chronic HBV and HCV patients exhibited significant cognitive differences, particularly in memory, related to CD33 SNP genotypes. Moderation analysis indicated a heightened influence of CD33 SNPs on cognitive functions in chronic HBV and HCV individuals. Our data also suggest that inflammation severity may modulate the cognitive effects in hepatitis patients with specific CD33 SNPs.

This study highlights the importance of CD33 SNPs in cognitive outcomes, emphasising their role in the context of chronic viral hepatitis. It contributes to understanding the cognitive profiles influenced by CD33 SNPs and posits CD33’s potential contribution to neurodegenerative disease progression, potentially intensified by HBV/HCV-induced inflammation.

The cumulative effects of long-term exposure to pandemic-related stressors and the severity of social restrictions may have been important determinants of mental distress in the time of COVID-19.

This study aimed to investigate mental health among a cohort of Chinese university students over a 28-month period, focusing on the effects of lockdown type.

Depression, anxiety, stress and fear of COVID-19 infection were measured ten times among 188 Chinese students (females 77.7%, meanage = 19.8, s.d.age = 0.97), every 3 months: from prior to the emergence of COVID-19 in November 2019 (T1) to March 2022 (T10).

Initially depression, anxiety and stress dipped from T1 to T2, followed by a sudden increase at T3 and a slow upward rise over the remainder of the study period (T3 to T10). When locked down at university, participants showed greater mental distress compared with both home lockdown (d = 0.35–0.48) and a no-lockdown comparison period (d = 0.28–0.40). Conversely, home lockdown was associated with less anxiety and stress (d = 0.19 and 0.21, respectively), but not with depression (d = 0.13) compared with a no-lockdown period.

This study highlights the cumulative effects of exposure to COVID-19 stressors over time. It also suggests that the way in which a lockdown is carried out can impact the well-being of those involved. Some forms of lockdown appear to pose a greater threat to mental health than others.

Stroke clinical registries are critical for systems planning, quality improvement, advocacy and informing policy. We describe the methodology and evolution of the Registry of the Canadian Stroke Network/Ontario Stroke Registry in Canada.

At the launch of the registry in 2001, trained coordinators prospectively identified patients with acute stroke or transient ischemic attack (TIA) at comprehensive stroke centers across Canada and obtained consent for registry participation and follow-up interviews. From 2003 onward, patients were identified from administrative databases, and consent was waived for data collection on a sample of eligible patients across all hospitals in Ontario and in one site in Nova Scotia. In the most recent data collection cycle, consecutive eligible patients were included across Ontario, but patients with TIA and those seen in the emergency department without admission were excluded.

Between 2001 and 2013, the registry included 110,088 patients. Only 1,237 patients had follow-up interviews, but administrative data linkages allowed for indefinite follow-up of deaths and other measures of health services utilization. After a hiatus, the registry resumed data collection in 2019, with 13,828 charts abstracted to date with a focus on intracranial vascular imaging, identification of intracranial occlusions and treatment with thrombectomy.

The Registry of the Canadian Stroke Network/Ontario Stroke Registry is a large population-based clinical database that has evolved throughout the last two decades to meet contemporary stroke needs. Registry data have been used to monitor stroke quality of care and conduct outcomes research to inform policy.

Acute stroke treatments are highly time-sensitive, with geographical disparities affecting access to care. This study examined the impact of driving distance to the nearest comprehensive stroke center (CSC) and rurality on the use of thrombectomy or thrombolysis in Ontario, Canada.

This retrospective cohort study used administrative data to identify adults hospitalized with acute ischemic stroke between 2017 and 2022. Driving time from patients’ residences to the nearest CSC was calculated using the Ontario Road Network File and postal codes. Rurality was categorized using postal codes. Multivariable logistic regression, adjusted for baseline differences, estimated the association between driving distance and treatment with thrombectomy (primary outcome) or thrombolysis (secondary outcome). Driving time was modeled as a continuous variable using restricted cubic splines.

Data from 57,678 patients (median age 74 years, IQR 64–83) were analyzed. Increased driving time was negatively associated with thrombectomy in a nonlinear fashion. Patients living 120 minutes from a CSC were 20% less likely to receive thrombectomy (adjusted odds ratio [aOR] 0.80, 95% CI 0.62–1.04), and those 240 minutes away were 60% less likely (aOR 0.41, 95% CI 0.28–0.60). Driving time did not affect thrombolysis rates, even at 240 minutes (aOR 1.0, 95% CI 0.70–1.42). Thrombectomy use was similar in medium urban areas (aOR 0.80, 95% CI 0.56–1.16) and small towns (aOR 0.78, 95% CI 0.57–1.06) compared to large urban areas.

Thrombolysis access is equitable across Ontario, but thrombectomy access decreases with increased driving distance to CSCs. A multifaceted approach, combining healthcare policy innovation and infrastructure development, is necessary for equitable thrombectomy delivery.