METHODS: Patients with unexplained pediatric-onset epilepsy were identified from the in-house Severance Neurodevelopmental Disorders and Epilepsy Database. All patients underwent either exome sequencing or multigene panels from January 2017 to December 2019, at Severance Children's Hospital in Korea. Clinical data were extracted from the medical records.
RESULTS: Of the 957 patients studied, 947 (99.0%) were Korean and 570 were male (59.6%). The median age at testing was 4.91 years (interquartile range, 1.53-9.39). The overall diagnostic yield was 32.4% (310/957). Clinical exome sequencing yielded a diagnostic rate of 36.9% (134/363), whereas the epilepsy panel yielded a diagnostic rate of 29.9% (170/569). Diagnostic yield differed across epilepsy syndromes. It was high in Dravet syndrome (87.2%, 41/47) and early infantile developmental epileptic encephalopathy (60.7%, 17/28), but low in West syndrome (21.8%, 34/156) and myoclonic-atonic epilepsy (4.8%, 1/21). The most frequently implicated genes were SCN1A (n = 49), STXBP1 (n = 15), SCN2A (n = 14), KCNQ2 (n = 13), CDKL5 (n = 11), CHD2 (n = 9), SLC2A1 (n = 9), PCDH19 (n = 8), MECP2 (n = 6), SCN8A (n = 6), and PRRT2 (n = 5). The recurrent genetic abnormalities included 15q11.2 deletion/duplication (n = 9), Xq28 duplication (n = 5), PRRT2 deletion (n = 4), MECP2 duplication (n = 3), SCN1A, c.2556+3A>T (n = 3), and 2q24.3 deletion (n = 3).
SIGNIFICANCE: Here we present the results of a large-scale study conducted in East Asia, where we identified several common genes and recurrent variants that varied depending on specific epilepsy syndromes. The overall genetic landscape of the Asian population aligns with findings from other populations of varying ethnicities.
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.
IMPACT: Epidemiological data and risk factors for major trauma resulting from school injuries in Asia are lacking. This study identified significant risk factors for major trauma occurring at schools, including age, intention of injury (self-harm), injury type (traffic injuries, falls), and body part injured (head, thoracic, and abdominal injuries). Although the incidence of injuries was higher in males, the incidence of self-harm injuries and mortality rates were higher in females. The results of this would make a significant contribution to the development of prevention strategies and relative policies concerning school injuries.
METHODS: This retrospective and multinational cohort study included all adult transferred injury patients from Korea, Malaysia, Vietnam, and Taiwan between 2016 and 2018. The outcome of interest was a death in the emergency department (ED) after the patients' ED visit. Using these results, we developed the interpretable field triage score with the Korea registry using an interpretable machine learning framework and validated the score externally. The performance of each country's score was assessed using the area under the receiver operating characteristic curve (AUROC). Furthermore, a website for real-world application was developed using R Shiny.
FINDINGS: The study population included 26,294, 9404, 673 and 826 transferred injury patients between 2016 and 2018 from Korea, Malaysia, Vietnam, and Taiwan, respectively. The corresponding rates of a death in the ED were 0.30%, 0.60%, 4.0%, and 4.6% respectively. Age and vital sign were found to be the significant variables for predicting mortality. External validation showed the accuracy of the model with an AUROC of 0.756-0.850.
INTERPRETATION: The Grade for Interpretable Field Triage (GIFT) score is an interpretable and practical tool to predict mortality in field triage for trauma.
FUNDING: This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant Number: HI19C1328).
METHODS: A cross-sectional descriptive survey addressing population characteristics, DS structures and levels of service, state of DACPR implementation (including protocols and quality improvement programs) among PAROS DS's.
RESULTS: 9 DS's responded, representing a total of 23 dispatch centres from 9 countries that serve over 80 million people. Most PAROS DS's operate a tiered dispatch response, have implemented medical oversight, and tend to be staffed by dispatchers with a predominantly medical background. Almost all PAROS DS's have begun tracking key EMS indicators. 77.8% (n = 7) of PAROS DS's have introduced DACPR. Of the DS's that have rolled out DACPR, 71.4% (n = 5) provided instructions in over one language. All DS's that implemented DACPR and provided feedback to dispatchers offered feedback on missed OHCA recognition. The majority of DS's (83.3%; n = 5) that offered DACPR and provided feedback to dispatchers also implemented corrective feedback, while 66.7% (n = 4) offered positive feedback. Compression-only CPR was the standard instruction for PAROS DS's. OHCA recognition sensitivity varied widely in PAROS DS's, ranging from 32.6% (95% CI: 29.9-35.5%) to 79.2% (95% CI: 72.9-84.4%). Median time to first compression ranged from 120 s to 220 s.
CONCLUSIONS: We found notable variations in characteristics and state of DACPR implementation between PAROS DS's. These findings will lay the groundwork for future DS and DACPR studies in the PAROS network.
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.
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).
CONCLUSION: We established a prediction model using variables from the PATOS database and measured them immediately after EMS personnel arrived to predict EMS-witnessed TCA. The model allows prehospital medical personnel to focus on high-risk patients and promptly administer optimal treatment.
METHODS: The World Health Organization (WHO) aims to extend UHC to a further 1 billion people by 2023, yet evidence supporting improved emergency care coverage is lacking. In this article, we explore four phases of a research prioritisation setting (RPS) exercise conducted by researchers and stakeholders from South Africa, Egypt, Nepal, Jamaica, Tanzania, Trinidad and Tobago, Tunisia, Colombia, Ethiopia, Iran, Jordan, Malaysia, South Korea and Phillipines, USA and UK as a key step in gathering evidence required by policy makers and practitioners for the strengthening of emergency care systems in limited-resource settings.
RESULTS: The RPS proposed seven priority research questions addressing: identification of context-relevant emergency care indicators, barriers to effective emergency care; accuracy and impact of triage tools; potential quality improvement via registries; characteristics of people seeking emergency care; best practices for staff training and retention; and cost effectiveness of critical care - all within LMICs.
CONCLUSIONS: Convened by WHO and facilitated by the University of Sheffield, the Global Emergency Care Research Network project (GEM-CARN) brought together a coalition of 16 countries to identify research priorities for strengthening emergency care in LMICs. Our article further assesses the quality of the RPS exercise and reviews the current evidence supporting the identified priorities.
METHODS: We identified suicide data from official public-sector sources for countries/areas-within-countries, searching websites and academic literature and contacting data custodians and authors as necessary. We sent our first data request on 22nd June 2021 and stopped collecting data on 31st October 2021. We used interrupted time series (ITS) analyses to model the association between the pandemic's emergence and total suicides and suicides by sex-, age- and sex-by-age in each country/area-within-country. We compared the observed and expected numbers of suicides in the pandemic's first nine and first 10-15 months and used meta-regression to explore sources of variation.
FINDINGS: We sourced data from 33 countries (24 high-income, six upper-middle-income, three lower-middle-income; 25 with whole-country data, 12 with data for area(s)-within-the-country, four with both). There was no evidence of greater-than-expected numbers of suicides in the majority of countries/areas-within-countries in any analysis; more commonly, there was evidence of lower-than-expected numbers. Certain sex, age and sex-by-age groups stood out as potentially concerning, but these were not consistent across countries/areas-within-countries. In the meta-regression, different patterns were not explained by countries' COVID-19 mortality rate, stringency of public health response, economic support level, or presence of a national suicide prevention strategy. Nor were they explained by countries' income level, although the meta-regression only included data from high-income and upper-middle-income countries, and there were suggestions from the ITS analyses that lower-middle-income countries fared less well.
INTERPRETATION: Although there are some countries/areas-within-countries where overall suicide numbers and numbers for certain sex- and age-based groups are greater-than-expected, these countries/areas-within-countries are in the minority. Any upward movement in suicide numbers in any place or group is concerning, and we need to remain alert to and respond to changes as the pandemic and its mental health and economic consequences continue.
FUNDING: None.