Frailty and Other Factors Associated With Early Outcomes in Middle-to Older Age Trauma Patients: A Prospective Cohort Study.

OBJECTIVES: To prospectively investigate associations of frailty and other predictor variables with functional recovery and health outcomes in middle-aged and older patients with trauma. DESIGN: Single-center prospective cohort study. SETTING: Emergency department of Wan Fang Hospital in Taiwan. PARTICIPANTS: Trauma patients aged 45 and older. MEASUREMENTS: Frailty was assessed with the Clinical Frailty Scale (CFS). Injury mechanisms, pre-existing diseases, and fracture locations were recorded at baseline. The primary outcome was functional recovery assessed using the Barthel Index (BI). Secondary outcomes were new care needs, unscheduled return visits, and falls 3 months postinjury. RESULTS: A total of 588 participants were included in the final analysis. For every one-point increase in the CFS, the multivariable-adjusted odds ratio (OR, 95% confidence interval [CI]) of failure to retain the preinjury BI was 1.34 (1.16-1.55); associations were consistent across levels of age and injury severities. Significant joint associations of frailty and age with poor functional recovery were observed. CFS was also associated with new care needs (OR for every one-point increase, 1.36, 95% CI, 1.17-1.58), unscheduled return visits (OR 1.26, 95% CI, 1.04-1.51), and falls (OR 1.23, 95% CI, 1.01-1.51). Other variables associated with failure to retain preinjury BI included road traffic accident and presence of hip fracture. CONCLUSION: Frailty was significantly associated with poor functional and health outcomes regardless of injury severity in middle-aged and older patients with trauma. Injury mechanisms and fracture locations were also significant predictors of functional recovery postinjury.

Effect of motorcycle helmet types on head injuries: evidence from eight level-I trauma centres in Taiwan.

BACKGROUND: Motorcycle full-coverage helmet use may reduce fatalities and head injuries. METHODS: This retrospective cohort study extracted injury data from eight level-I trauma centres in Taiwan and performed a questionnaire survey to investigate injuries sustained by motorcyclists for the period between January 2015 and June 2017. RESULTS: As many as 725 patients participated in the questionnaire survey and reported their helmet types or phone use during crashes. The results of multivariate logistic models demonstrated that nonstandard helmet (half or open-face helmet) use was associated with an increased risk of head injuries and more severe injuries (injury severity score ≥ 8). Drunk riding and phone use appeared to be two important risk factors for head injuries and increased injury severity. Anaemia was also found to be a determinant of head injuries." CONCLUSIONS: Compared to full-coverage helmets, nonstandard provide less protection against head injuries and increased injury severity among motorcyclists.

Improving the timeliness and accuracy of injury severity data in road traffic accidents in an emerging economy setting.

Road traffic injuries (RTIs) are among the leading causes of injury and fatality worldwide. RTI casualties are continually increasing in Taiwan; however, because of a lack of an advanced method for classifying RTI severity data, as well as the fragmentation of data sources, road traffic safety and health agencies encounter difficulties in analyzing RTIs and their burden on the healthcare system and national resources. These difficulties lead to blind spots during policy-making for RTI prevention and control. After compiling classifications applied in various countries, we summarized data sources for RTI severity in Taiwan, through which we identified data fragmentation. Accordingly, we proposed a practical classification for RTI severity, as well as a feasible model for collecting and integrating these data nationwide. This model can provide timely relevant data recorded by medical professionals and is valuable to healthcare providers. The proposed model's pros and cons are also compared to those of other current models.

National trends in therapeutic approaches and outcomes for pediatric appendicitis: a Taiwanese nationwide cohort study.

PURPOSE: To define the pattern of therapeutic approaches for pediatric appendicitis and compare their benefits in Taiwan, we analyzed a research-oriented dataset released by the Bureau of National Health Insurance in Taiwan through the Collaboration Center for Health Information Application (CCHIA) to document the impact of the rise of laparoscopic treatment on outcomes. METHODS: We identified 22,161 patients under 18 years who had been hospitalized with a diagnosis of acute appendicitis between 2007 and 2012 in the CCHIA. Statistical comparisons between the Laparoscopic appendectomy (LA) and open appendectomy (OA, control) groups were computed using a Chi squared test. The odds ratios (ORs) and 95% confidence intervals (CIs) of risk factors for intra-abdominal abscess (IAA) and postoperative bowel obstruction (PBO) were derived from multivariate logistic regression models. RESULTS: In each respective year, the incidence of LA increased from 29.17% in 2007 to 57.4% in 2012, while that of OA decreased from 70.83% in 2007 to 42.60% in 2012; incidences of non-perforated appendicitis and perforated appendicitis with LA or OA seemed similar. The length of hospitalization between an LA and OA for non-perforated appendicitis was the same, but that with an LA was shorter for perforated appendicitis. The adjusted ORs for IAA and PBO for those patients with perforated and non-perforated appendicitis were 6.30 (95% CI = 5.09-7.78; p < 0.001) and 6.49 (95% CI = 4.45-9.48; p < 0.001); while for those cases undergoing an LA and OA, they were 0.50 (95 % CI = 0.40-0.62; p < 0.001) and 2.07 (95% CI = 1.45-2.95; p < 0.001), respectively. The ORs of IAA and PBO for those patients ≤6 and 7-12 years of age were 1.67 (95% CI = 1.23-2.25; p = 0.001) and 1.20 (95% CI = 0.97-1.49; p = 0.095), and 1.88 (95% CI = 1.08-3.24; p = 0.025) and 1.47 (95% CI = 1.01-2.14; p = 0.043), respectively, compared to those aged 13-18 years. CONCLUSIONS: Our study demonstrated that young age and perforated appendicitis can affect postoperative IAA and PBO. LA appeared beneficial in reducing the length of hospitalization and postoperative IAA, but had an increasing risk of PBO. Although laparoscopic approach for pediatric appendectomy is increasing in our country, the different hospital levels and pediatric surgeon's laparoscopic experience must be evaluated in further study.

Risk of Traumatic Intracranial Hemorrhage After Stroke: A Nationwide Population-Based Cohort Study in Taiwan.

BACKGROUND: Stroke and traumatic intracranial hemorrhage (tICH) are major causes of disability worldwide, with stroke exerting significant negative effects on the brain, potentially elevating tICH risk. In this study, we investigated tICH risk in stroke survivors. METHODS AND RESULTS: Using relevant data (2017-2019) from Taiwan's National Health Insurance Research Database, we conducted a population-based retrospective cohort study. Patients were categorized into stroke and nonstroke groups, and tICH risk was compared using a Cox proportional-hazards model. Among 164 628 patients with stroke, 1004 experienced tICH. Patients with stroke had a higher tICH risk than nonstroke counterparts (adjusted hazard ratio [HR], 3.49 [95% CI, 3.17-3.84]). Subgroup analysis by stroke type revealed higher tICH risk in hemorrhagic stroke survivors compared with ischemic stroke survivors (HR, 5.64 [95% CI, 4.97-6.39] versus 2.87 [95% CI, 2.58-3.18], respectively). Older patients (≥45 years) with stroke had a higher tICH risk compared with their younger counterparts (<45 years), in contrast to younger patients without stroke (HR, 7.89 [95% CI, 6.41-9.70] versus 4.44 [95% CI, 2.99-6.59], respectively). Dementia and Parkinson disease emerged as significant tICH risk factors (HR, 1.69 [95% CI, 1.44-2.00] versus 2.17 [95% CI, 1.71-2.75], respectively). In the stroke group, the highest tICH incidence density occurred 3 months after stroke, particularly in patients aged >65 years. CONCLUSIONS: Stroke survivors, particularly those with hemorrhagic stroke and those aged ≥45 years, face elevated tICH risk. Interventions targeting the high-risk period are vital, with fall injuries potentially contributing to tICH incidence.

Prediction of posttraumatic functional recovery in middle-aged and older patients through dynamic ensemble selection modeling.

Introduction: Age-specific risk factors may delay posttraumatic functional recovery; complex interactions exist between these factors. In this study, we investigated the prediction ability of machine learning models for posttraumatic (6 months) functional recovery in middle-aged and older patients on the basis of their preexisting health conditions. Methods: Data obtained from injured patients aged ≥45 years were divided into training-validation (n = 368) and test (n = 159) data sets. The input features were the sociodemographic characteristics and baseline health conditions of the patients. The output feature was functional status 6 months after injury; this was assessed using the Barthel Index (BI). On the basis of their BI scores, the patients were categorized into functionally independent (BI >60) and functionally dependent (BI ≤60) groups. The permutation feature importance method was used for feature selection. Six algorithms were validated through cross-validation with hyperparameter optimization. The algorithms exhibiting satisfactory performance were subjected to bagging to construct stacking, voting, and dynamic ensemble selection models. The best model was evaluated on the test data set. Partial dependence (PD) and individual conditional expectation (ICE) plots were created. Results: In total, nineteen of twenty-seven features were selected. Logistic regression, linear discrimination analysis, and Gaussian Naive Bayes algorithms exhibited satisfactory performances and were, therefore, used to construct ensemble models. The k-Nearest Oracle Elimination model outperformed the other models when evaluated on the training-validation data set (sensitivity: 0.732, 95% CI: 0.702-0.761; specificity: 0.813, 95% CI: 0.805-0.822); it exhibited compatible performance on the test data set (sensitivity: 0.779, 95% CI: 0.559-0.950; specificity: 0.859, 95% CI: 0.799-0.912). The PD and ICE plots showed consistent patterns with practical tendencies. Conclusion: Preexisting health conditions can predict long-term functional outcomes in injured middle-aged and older patients, thus predicting prognosis and facilitating clinical decision-making.

Association between short-term air pollution exposure and traumatic intracranial hemorrhage: pilot evidence from Taiwan.

Introduction: The detrimental effects of air pollution on the brain are well established. However, few studies have examined the effect of air pollution on traumatic brain injury (TBI). This pilot study evaluated the association between short-term air pollution exposure and traumatic intracranial hemorrhage (TIH). Methods: Hospital data of patients with TBI following road traffic accidents were retrospectively collected from the electronic medical records at five trauma centers in Taiwan between 1 January and 31 December 2017. TIH was employed as an outcome measure. All road accident locations were geocoded, and air quality data were collected from the nearest monitoring stations. Air pollutants were entered into five multivariable models. A sensitivity analysis was performed on patients who are vulnerable to suffering TBI after road accidents, including motorcyclists, bicyclists, and pedestrians. Results: Among 730 patients with TBI, 327 had TIH. The ages of ≥65 [odds ratio (OR), 3.24; 95% confidence interval (CI), 1.85-5.70], 45-64 (OR, 2.61; 95% CI, 1.64-4.15), and 25-44 (OR, 1.79; 95% CI, 1.13-2.84) years were identified as significant risk factors in the multivariable analysis. In the best-fit multivariable model, exposure to higher concentrations of particulate matter ≤ 2.5 µm in aerodynamic diameter (PM2.5) was associated with an elevated TIH risk (OR, 1.50; 95% CI, 1.17-1.94). The concentration of nitrogen oxides (NOX) did not increase the risk of TIH (OR, 0.45; 95% CI, 0.32-0.61). After categorizing the air pollution concentration according to quartile, the trend tests in the multivariate model showed that the concentrations of PM2.5 and NOX were significant (p = 0.017 and p < 0.001, respectively). There was a negative borderline significant association between temperature and TIH risk (OR, 0.75; 95% CI, 0.56-1.00, p = 0.05). Notably, the single-vehicle crash was a significant risk factor (OR, 2.11; 95% CI, 1.30-3.42) for TIH. Discussion: High PM2.5 concentrations and low temperatures are risk factors for TIH in patients with TBI. High NOX concentrations are associated with a lower TIH risk.

Unveiling the future of COVID-19 patient care: groundbreaking prediction models for severe outcomes or mortality in hospitalized cases.

Background: Previous studies have identified COVID-19 risk factors, such as age and chronic health conditions, linked to severe outcomes and mortality. However, accurately predicting severe illness in COVID-19 patients remains challenging, lacking precise methods. Objective: This study aimed to leverage clinical real-world data and multiple machine-learning algorithms to formulate innovative predictive models for assessing the risk of severe outcomes or mortality in hospitalized patients with COVID-19. Methods: Data were obtained from the Taipei Medical University Clinical Research Database (TMUCRD) including electronic health records from three Taiwanese hospitals in Taiwan. This study included patients admitted to the hospitals who received an initial diagnosis of COVID-19 between January 1, 2021, and May 31, 2022. The primary outcome was defined as the composite of severe infection, including ventilator use, intubation, ICU admission, and mortality. Secondary outcomes consisted of individual indicators. The dataset encompassed demographic data, health status, COVID-19 specifics, comorbidities, medications, and laboratory results. Two modes (full mode and simplified mode) are used; the former includes all features, and the latter only includes the 30 most important features selected based on the algorithm used by the best model in full mode. Seven machine learning was employed algorithms the performance of the models was evaluated using metrics such as the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, and specificity. Results: The study encompassed 22,192 eligible in-patients diagnosed with COVID-19. In the full mode, the model using the light gradient boosting machine algorithm achieved the highest AUROC value (0.939), with an accuracy of 85.5%, a sensitivity of 0.897, and a specificity of 0.853. Age, vaccination status, neutrophil count, sodium levels, and platelet count were significant features. In the simplified mode, the extreme gradient boosting algorithm yielded an AUROC of 0.935, an accuracy of 89.9%, a sensitivity of 0.843, and a specificity of 0.902. Conclusion: This study illustrates the feasibility of constructing precise predictive models for severe outcomes or mortality in COVID-19 patients by leveraging significant predictors and advanced machine learning. These findings can aid healthcare practitioners in proactively predicting and monitoring severe outcomes or mortality among hospitalized COVID-19 patients, improving treatment and resource allocation.

An old lady with anterior chest pain and unilateral facial flushing.

Harlequin syndrome is rare and typically characterized by asymmetric flushing and sweating. Although it is usually considered idiopathic, literature review shows that it may be caused by lesion over lung apex or after central venous catheterization in the internal jugular vein. We present a 74-year-old woman who had been experiencing recurrent chest pain and right shoulder pain since 2 weeks ago. The tentative diagnosis was made by the emergency physician (EP) as acute coronary syndrome. The patient was given nitroglycerin treatment. Twelve hours later, the patient developed another episode of chest pain. The electrocardiogram and cardiac enzyme study results were, however, both normal. Further evaluation showed intermittent flushing over the left side of her face, as well as right-eye ptosis. A chest computed tomography (CT) was conducted, under the suspicion of Harlequin syndrome in combination with Horner syndrome, to derive the diagnosis of a right lung apex tumor. This case showed that history taking and physical examination are very important in the emergency department. It is particularly vital to observe the microchanges in the patient's symptoms and signs. It is also imperative to reassess the patient whose symptoms fail to improve under treatment, to look for other underlying lesions.

Bruns-Cushing nystagmus due to hypertensive unilateral paramedian pontine base infarction.

Bruns-Cushing nystagmus is unusually rare and is known to be related with cerebellopontine angle tumor. A 32-year-old male patient came to our emergency department 3 times because of dizziness, right upper limb ataxia, hypertension, and Bruns-Cushing nystagmus. Magnetic resonance imaging demonstrated left paramedian pontine infarction. In conclusion, Bruns-Cushing nystagmus not only indicates a cerebellopontine angle tumor but may also be associated with pontine infarction.

A young man presenting with acute encephalopathy, hemiparesis, and headache.

BACKGROUND: Familial hemiplegic migraine (FHM) is a rare type of migraine. Correct diagnosis is challenging for emergency physicians (EPs) due to its variable clinical picture, as well as its lack of diagnostic biological markers. OBJECTIVES: To raise awareness among EPs regarding FHM's diverse clinical picture, and to highlight FHM's diagnostic criteria to facilitate an accurate and timely diagnosis of FHM in patients presenting to the emergency department (ED) with indicative symptomatology. CASE REPORT: A 24-year-old male student presented to the ED complaining of dizziness, general weakness, and blurred vision that had developed the previous night. The initial physical examination revealed drowsiness, slow speech production, and slight weakness with paresthesia in all limbs. Detailed communication with the patient's aunt revealed that he had experienced several similar attacks since the age of 12 years, and that there was also an extensive family history of the same symptoms. In addition, 2 h after arrival, the patient experienced severe throbbing headache, vomiting, severe dysphasia, and the weakness shifted to the right side. A computed tomography scan of the brain showed no anomalies. He was admitted with a tentative diagnosis of FHM. CONCLUSION: A diagnosis of FHM should be considered if the patient's clinical features include headache and weakness, with a family history of similar symptomatology. However, atypical symptoms of FHM may present as recurrent episodes of unexplained encephalopathy. Crucial elements for making an accurate and timely diagnosis of FHM include a detailed knowledge of weakness-related diseases and an ability to consider FHM in the differential diagnosis, as well as obtaining a thorough family history with repeated neurologic assessments.

Association of Air Pollution and Weather Factors with Traffic Injury Severity: A Study in Taiwan.

Exposure to air pollutants may elevate the injury severity scores (ISSs) for road traffic injuries (RTIs). This multicenter cross-sectional study aimed to investigate the associations between air pollution, weather conditions, and RTI severity. This retrospective study was performed in Taiwan in 2018. The location of each road traffic accident (RTA) was used to determine the nearest air quality monitoring and weather station, and the time of each RTA was matched to the corresponding hourly air pollutant concentration and weather factors. Five multiple logistic regression models were used to compute the risk of sustaining severe injury (ISS ≥ 9). Of the 14,973 patients with RTIs, 2853 sustained severe injury. Moderate or unhealthy air quality index, higher exposure to particulate matter ≤2.5 µm in diameter, bicyclists or pedestrians, greater road width, nighttime, and higher temperature and relative humidity were significant risk factors for severe injury. Exposure to nitrogen oxide and ozone did not increase the risk. Auto occupants and scene-to-hospital time were the protective factors. Sensitivity analyses showed consistent results between air pollutants and the risk of severe injury. Poor air quality and hot and humid weather conditions were associated with severe RTIs. Active commuters were at higher risk of sustaining severe RTI.

Determinants of coronavirus disease 2019 infection by artificial intelligence technology: A study of 28 countries.

OBJECTIVES: The coronavirus disease 2019 pandemic has affected countries around the world since 2020, and an increasing number of people are being infected. The purpose of this research was to use big data and artificial intelligence technology to find key factors associated with the coronavirus disease 2019 infection. The results can be used as a reference for disease prevention in practice. METHODS: This study obtained data from the "Imperial College London YouGov Covid-19 Behaviour Tracker Open Data Hub", covering a total of 291,780 questionnaire results from 28 countries (April 1~August 31, 2020). Data included basic characteristics, lifestyle habits, disease history, and symptoms of each subject. Four types of machine learning classification models were used, including logistic regression, random forest, support vector machine, and artificial neural network, to build prediction modules. The performance of each module is presented as the area under the receiver operating characteristics curve. Then, this study further processed important factors selected by each module to obtain an overall ranking of determinants. RESULTS: This study found that the area under the receiver operating characteristics curve of the prediction modules established by the four machine learning methods were all >0.95, and the RF had the highest performance (area under the receiver operating characteristics curve is 0.988). Top ten factors associated with the coronavirus disease 2019 infection were identified in order of importance: whether the family had been tested, having no symptoms, loss of smell, loss of taste, a history of epilepsy, acquired immune deficiency syndrome, cystic fibrosis, sleeping alone, country, and the number of times leaving home in a day. CONCLUSIONS: This study used big data from 28 countries and artificial intelligence methods to determine the predictors of the coronavirus disease 2019 infection. The findings provide important insights for the coronavirus disease 2019 infection prevention strategies.

Environmental Factors Associated with Severe Motorcycle Crash Injury in University Neighborhoods: A Multicenter Study in Taiwan.

University neighborhoods in Taiwan have high-volume traffic, which may increase motorcyclists' risk of injury. However, few studies have analyzed the environmental factors affecting motorcycle crash injury severity in university neighborhoods. In this multicenter cross-sectional study, we explored the factors that increase the severity of such injuries, especially among young adults. We retrospectively connected hospital data to the Police Traffic Accident Dataset. Areas within 500 m of a university were considered university neighborhoods. We analyzed 4751 patients, including 513 with severe injury (injury severity score ≥ 8). Multivariate analysis revealed that female sex, age ≥ 45 years, drunk driving, early morning driving, flashing signals, and single-motorcycle crashes were risk factors for severe injury. Among patients aged 18-24 years, female sex, late-night and afternoon driving, and flashing signals were risk factors. Adverse weather did not increase the risk. Time to hospital was a protective factor, reflecting the effectiveness of urban emergency medical services. Lifestyle habits among young adults, such as drunk driving incidents and afternoon and late-night driving, were also explored. We discovered that understanding chaotic traffic in the early morning, flashing signals at the intersections, and roadside obstacles is key for mitigating injury severity from motorcycle crashes in university neighborhoods.

Effects of the COVID-19 Pandemic on Treatment Efficiency for Traumatic Brain Injury in the Emergency Department: A Multicenter Study in Taiwan.

The coronavirus disease 2019 (COVID-19) pandemic has impacted emergency department (ED) practice, including the treatment of traumatic brain injury (TBI), which is commonly encountered in the ED. Our study aimed to evaluate TBI treatment efficiency in the ED during the COVID-19 pandemic. A retrospective observational study was conducted using the electronic medical records from three hospitals in metropolitan Taipei, Taiwan. The time from ED arrival to brain computed tomography (CT) and the time from ED arrival to surgical management were used as measures of treatment efficiency. TBI treatment efficiencies in the ED coinciding with a small-scale local COVID-19 outbreak in 2020 (P1) and large-scale community spread in 2021 (P2) were compared against the pre-pandemic efficiency recorded in 2019. The interval between ED arrival and brain CT was significantly shortened during P1 and P2 compared with the pre-pandemic interval, and no significant delay between ED arrival and surgical management was found, indicating increased treatment efficiency for TBI in the ED during the COVID-19 pandemic. Minimizing viral spread in the community and the hospital is vital to maintaining ED treatment efficiency and capacity. The ED should retain sufficient capacity to treat older patients with serious TBI during the COVID-19 pandemic.

A pilot study of citizens' opinions on the Incident Command System in Taiwan.

Local residents may have different views on disaster-response modes depending on their cultural and socioeconomic background. The purpose of this study was to examine Taiwan residents' opinions on the Incident Command System (ICS). We performed a structured survey through face-to-face interviews in mudslide-affected communities. Quantitative analysis showed that the residents exhibited a clear preference for the ICS core-principle attributes of 'integrated communications', 'transfer of command' and 'modular organisation'. By contrast, the residents tended towards a non-ICS approach for 'incident action plan' and 'manageable span of control'. Qualitative analysis revealed an uncertain attitude towards 'transfer of command' and 'incident action plan'. Community acceptance is important in the promotion of the ICS. A better understanding of residents' preferences should be acquired through a broader community survey, allowing us to understand perspectives on the ICS among different societies and facilitate implementation of the ICS at the basic community level.

Heme oxygenase-1 mediates the inhibitory actions of brazilin in RAW264.7 macrophages stimulated with lipopolysaccharide.

Brazilin, the main constituent of Caesalpinia sappan L., is a natural red pigment that has been reported to possess anti-inflammatory properties. This study aimed to identify a novel anti-inflammatory mechanism of brazilin. We found that brazilin did not cause cytotoxicity below 300 microM, and activated heme oxygenase-1 (HO-1) protein synthesis in a concentration-dependent manner at 10-300 microM in RAW264.7 macrophages without affecting mRNA transcription of HO-1. Additionally, brazilin increased bilirubin production and HO-1 activity in RAW264.7 macrophages. In lipopolysaccharide (LPS)-stimulated macrophages, brazilin suppressed the release of nitric oxide (NO), prostaglandin E(2) (PGE(2)), interleukin (IL)-1beta and tumor necrosis factor-alpha (TNF-alpha), and reduced the expression of inducible nitric oxide synthase (iNOS). A specific inhibitor of HO-1, Zn(II) protoporphyrin IX, blocked the suppression of NO production, cytokines release and iNOS expression by brazilin. These results suggest that brazilin possesses anti-inflammatory actions in macrophages and works through a novel mechanism involving the action of HO-1.

Determination of contact force by compression testing of cylindrical specimens.

This paper presents a method for determining values of dynamic parameters of the Hunt and Crossley model in order to estimate the amount of force generated at the point of contact (contact force) in an impact. A two-degree-of-freedom lumped-mass-system based on a non-linear visco-elastic model as proposed by Hunt and Crossley has been widely used to accurately model contact force. The primary difficulty associated with the Hunt and Crossley contact force model is the need to determine the unknown dynamic parameters of the model, which can be obtained by calibrating the model against results from high-speed impact experiments. Spherical impactors have to be placed in the gas-gun barrel for accelerating onto the target specimen. An innovative and inexpensive method proposed in this paper describes the use of compression testing on a test rig employing cylindrical specimens of colliding bodies to obtain the dynamic parameters thereby waiving away the need of costly and time-consuming impact experiments.

Rider factors associated with severe injury after a light motorcycle crash: A multicentre study in an emerging economy setting.

OBJECTIVE: In Taiwan, light motorcycles (LMCs) with cylinder capacities between 50 and 250 cc are widely used for daily commute. These vehicles are operated in a mixed traffic environment and prohibited on highways. In light of increasing motorcycle casualties, we conducted a multicentre study to analyse rider factors affecting injury severity. METHODS: Riders hospitalised upon LMC crashes were contacted. Information on demographics, comorbidities, and riding behaviours was collected through questionnaires and linked to hospital data. The injury severity score (ISS) and length of hospitalisation (LOH) were used as injury severity measures. RESULTS: In total, 725 patients (mean age: 37.7 years; 64% men) completed their questionnaires. Multivariate analysis results showed that age ≥ 65 years, half-face helmets, protective clothing, collisions with a bus/truck or car, and fatigue riding were risk factors for having an ISS of ≥9. Age ≥ 65 years; motorcycle crashes ≥2 times in the previous year; anaemia; rural crashes; half-face helmets; protective boots; collisions with a bus/truck, car, or a stationary object; alcohol/stimulating refreshment consumption; and fatigue riding were risk factors for increased LOH. A protective factor was individuals working in commerce. Collisions with opening car doors caused low risks of having an ISS of ≥9 and a short LOH. CONCLUSION: Certain factors were significantly associated with riders' injury severity and related medical resource consumption. Because of differences in the power output, use, and riding environment, risk factors for severe injuries in LMC crashes are dissimilar from those for heavy motorcycles (cylinder capacities > 250 cc) in developed countries and deserve more attention for injury prevention. Further in-depth evaluation of significant factors based on this study's results can yield valuable information to reduce severe injuries after LMC crashes in countries and areas with a high dependency on motorcycles, even considering the popularity of electric motorcycles.

Suppression of lipopolysaccharide-induced of inducible nitric oxide synthase and cyclooxygenase-2 by Sanguis Draconis, a dragon's blood resin, in RAW 264.7 cells.

Sanguis Draconis (SD) is a kind of dragon's blood resin that is obtained from Daemomorops draco (Palmae). It is used in traditional medicine and has shown anti-inflammatory activity in some diseases. In this study, we examined the effects of Sanguis Dranonis ethanol extract (SDEE) on LPS-induced inflammation using RAW 264.7 cells. Our data indicated that SDEE inhibits LPS-stimulated NO, PGE2, IL-1 beta and TNF-alpha release, and iNOS and COX-2 expression. Furthermore, SDEE suppressed the LPS-induced p65 expression of NF-kappa B, which was associated with the inhibition of I kappa B-alpha degradation. We also found that the expression of HO-1 was significantly increased in RAW 264.7 cells by SDEE. These results suggest among possibilities of anti-inflammation that SDEE inhibits the production of NO and PGE2 by the down-regulation of iNOS and COX-2 gene expression via the suppression of NF-kappaB (p65) activation. SDEE can induce HO-1 over-expression in macrophage cells, which indicates that it may possess antioxidant properties. This result means that SEDD its anti-inflammatory effects in macrophages may be through a novel mechanism that involves the action of HO-1. Thus, SD could provide a potential therapeutic approach for inflammation-associated disorders.