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Underdiagnosis and underreporting of scrub typhus has increasingly affected public health in Bhutan since its initial detection in 2008. Identifying scrub typhus risk factors would support early diagnosis and treatment for this nonspecific febrile disease, reducing the incidence of potentially fatal complications. We conducted a hospital-based, case‒control study during October‒December 2015 in 11 scrub typhus‒prone districts. We identified harvesting cardamom as the major risk factor (odds ratio 1,519; p

Objective: To evaluate the outcomes of therapeutic penetrating keratoplasty (TPK) performed for severe fungal keratitis. Materials and Methods: Medical records of all patients who underwent TPK in Siriraj Medical Center between April 2010 and July 2020 were culled, and those in which fungal pathogens were definitively identified were studied. Patient records with follow up less than three months were excluded. Patient demographic data, outcome measures and complications following TPK were recorded. The primary outcome was eradication of the fungal infection. Secondary outcomes were preservation of anatomical integrity, graft survival and achievement of visual acuity (VA) greater than or equal to 3/60. Results: Sixty patients met the study criteria and were included in the analysis. The mean patient age was 56 (range: 23-79) years, and most patients were men (46, 77%). The mean follows up time was 30.87 months (range1.61-122.71). Fifteen eyes (25%) sustained corneal perforation before undergoing TPK. Graft survival was 30% at 1 year, 18% at 5 years, and 11% at 10 years. The most common organism was fusarium (23 patients, 38%). The median duration from presentation to surgery was 14 (8-21) days. Disease eradication was achieved in 44 patients (73%) and VA better than 3/60 was achieved in 14 (23%). Anatomical integrity was maintained in 46 (76%) eyes. Repeat PKP was performed in 15 patients (25%), most commonly for recurrent infection. Conclusion: TPK offers a good chance of disease eradication and maintenance of anatomical globe integrity and is a reasonable therapeutic option in patients with severe fungal infection.

Introduction: To address the suicide issue in the country, the Royal Government of Bhutan implemented a three year suicide prevention action plan from 1st July 2015 to 30th June 2018. As part of that action plan a national suicide registry was established under the Ministry of Health in January 2016 to collect comprehensive national data on suicide. The purpose of this study is to generate national information on suicide by analysing the suicide cases investigated and reported to suicide registry by the Forensic Department during the first two and half years. Methods: The study is a descriptive, retrospective and quantitative analysis of the suicide cases investigated by the Forensic Department from 1st January 2016 to 30th June 2018. The variables included the characteristics of the suicide victims. Result: Majority of the victims were young adults with no or low education and were either unemployed or employed with less income. 56.7% of the victims were women. Majority of them did not have physical illness or disability. About 45% had some form of mental health issues. Majority of them experienced some form of acute stressful event prior to committing suicide. Conclusion: Improved socioeconomic conditions through gainful employment, easily accessible mental health services and social support networks as well as population with good social and emotional skills will contribute to prevention of suicide in the country.

Abstract Background Rabies is endemic in southern Bhutan, associated with 1–2 human deaths and high post exposure prophylaxis (PEP) costs annually. Evaluation of clinicians’ management of human cases potentially exposed to rabies could contribute to improving PEP prescribing practices to both reduce unnecessary costs associated with PEP and reach the target of zero human deaths due to rabies by 2023. Methods A cross-sectional survey of 50 clinicians’ management of human cases potentially exposed to rabies was conducted in 13 health centers in high-rabies-risk areas of Bhutan during February–March 2016. Results Data were collected on clinicians’ management of 273 human cases potentially exposed to rabies. The 50 clinicians comprised health assistants or clinical officers (55%) and medical doctors (45%) with a respective median of 19, 21 and 2 years’ experience. There was poor agreement between clinicians’ rabies risk assessment compared with an independent assessment for each case based on criteria in the National Rabies Management Guidelines (NRMG). Of the 194 cases for which clinicians recorded a rabies risk category, only 53% were correctly classified when compared with the NRMG. Clinicians were more likely to underestimate the risk of exposure to rabies and appeared to prescribe PEP independently of their risk classification.. Male health assistants performed the most accurate risk assessments while female health assistants performed the least accurate. Clinicians in Basic Health Units performed less accurate risk assessments compared with those in hospitals. Conclusions This study highlights important discrepancies between clinicians’ management of human cases potentially exposed to rabies and recommendations in the NRMG. In particular, clinicians were not accurately assessing rabies risk in potentially exposed cases and were not basing their PEP treatment on the basis of their risk assessment. This has significant implications for achieving the national goal of eliminating dog-mediated human rabies by 2030 and may result in unnecessary costs associated with PEP. Recommendations to improve clinician’s management of human cases potentially exposed to rabies include: reviewing and updating the NRMG, providing clinicians with regular and appropriately targeted training about rabies risk assessment and PEP prescription, and regularly reviewing clinicians’ practices.

Cardiovascular disease is a leading cause of death in the Kingdom of Bhutan, and early detection of hypertension is critical for preventing cardiovascular disease. However, health-seeking behavior, including blood pressure measurement, is infrequently investigated in Bhutan. Therefore, this study investigated factors related to blood pressure measurement in Bhutan. We performed a secondary data analysis of a target population of 1,962 individuals using data from the "2014 Bhutan STEPS survey data"as a cross-sectional study. Approximately 26% of those with hypertension who were detected during the STEPS survey had never had their blood pressure measured. Previous blood pressure measurement was significantly associated with age and working status in men (self-employed [odds ratio (OR): 0.219, 95% CI: 0.133-0.361], non-working [OR: 0.114, 95% CI: 0.050-0.263], employee [OR: 1.000]). Previous blood pressure measurement was significantly associated with higher income in women (Quartile-2 [OR: 1.984, 95% CI: 1.209-3.255], Quartile-1 [OR: 2.161, 95% CI: 1.415-3.299], Quartile-4 [OR: 1.000]). A family history of hypertension (OR: 2.019, 95% CI: 1.549-2.243) increased the likelihood of having experienced a blood pressure measurement in both men and women. Multivariate logistic regression showed that people with unhealthy lifestyles (high salt intake [adjusted odds ratio (AOR): 0.247, 95% confidence interval (CI): 0.068-0.893], tobacco use [AOR: 0.538, 95% CI: 0.380-0.761]) had a decreased likelihood of previous blood pressure measurement. To promote the early detection of hypertension in Bhutan, we suggest that more attention be paid to low-income women, non-working, self-employed, and low-income men, and a reduction of barriers to blood pressure measurement. Before the STEPS survey, a substantial number of hypertensive people had never had their blood pressure measured or were unconcerned about their health. As a result, we propose that early blood pressure monitoring and treatment for people with hypertension or at higher risk of hypertension be given increased emphasis.

Cardiovascular disease is the leading cause of death in the Kingdom of Bhutan. Thus, the early detection and prevention of hypertension is critical for reducing cardiovascular disease. However, the influence of sociocultural factors on vulnerability to hypertension needs further investigation. This study performed secondary data analysis on 1,909 individuals in a cross-sectional study (the National survey for noncommunicable disease risk factors and mental health using World Health Organization (WHO) STEPS approach in Bhutan- 2014). Multivariate logistic regression demonstrated a significant association between gender with marital status and hypertension. Women had a higher odds ratio than men (Ref) when married (AOR: 1.27, 95% confidence intervals (CI): 1.23-1.31), and when separated, divorced, or widowed (AOR: 1.18, 95% CI: 1.12-1.26). People who speak the Tshanglakha language scored the highest odds (AOR: 1.24, 95% CI: 1.20-1.27), followed by Lhotshamkha (AOR: 1.09, 95% CI: 1.06-1.12) and Dzongkha (Ref) after adjusting for various social and biomedical factors. Additionally, tobacco use displayed decreased odds for hypertension. To promote the early detection and prevention of hypertension, these cultural factors should be considered even within small geographic areas, such as Bhutan. It is necessary to strengthen hypertension preventive strategies for people who speak Tshanglakha and Lhotshamkha. Furthermore, careful consideration should be given to preventing hypertension among adults aged 40 years or more, women who are married, separated, divorced, or widowed, and men who never married in Bhutan.

PurposeBhutan, known as a country of happiness, has experienced rapid social changes and the increasing burden of non-communicable diseases (NCDs) that can impact health and happiness. To inform future NCD prevention programs in Bhutan, this study explores knowledge, perception, and the practices of Bhutanese related to NCDs in the context of the philosophy of happiness.MethodologyResearch was conducted in rural and urban communities of Bhutan in 2017 among 79 inhabitants of both genders, aged ≥18. Participants were recruited through purposive sampling with the data collected by in-depth interviews, participatory observation, and anthropometric measurements. Data were analyzed by thematic analysis.Results/discussionAcross participants, health was considered as an important element of "happiness". However, lifestyle-related NCD risk factors prevailed due to the lack of effective education programs on NCDs and thus the lack of practical knowledge for NCD prevention across society. We further found that the value of happiness "finding happiness in any situation is virtue" was universal as well as other traditional values and customs, shaping people's health behaviors. From these observations, it is recommended that more practical NCD education/prevention programs should be urgently introduced in Bhutan that involve multiple generations, religion authorities, educational settings, and medical services.OriginalityThis is the first comprehensive qualitative study on the NCD-related lifestyle risks among Bhutanese concerning the concept of happiness.

Background: People with epilepsy (PWE) in low- and middle-income countries may not access the health resources that are considered optimal for epilepsy diagnosis. The diagnostic yield of magnetic resonance imaging (MRI) has not been well studied in these settings. Objectives: To report the diagnostic yield of brain MRI and identify clinical associations of abnormal MRI findings among PWE in a neurocysticercosis-endemic, resource-limited setting and to identify the proportion and putative structural brain causes of drug-resistant epilepsy. Methods: PWE were prospectively enrolled at the Jigme Dorji Wangchuck National Referral Hospital in Bhutan (2014-2015). Each participant completed clinical questionnaires and a 1.5-Tesla brain MRI. Each MRI was reviewed by at least 1 radiologist and neurologist in Bhutan and the United States. A working definition of drug-resistant epilepsy for resource-limited settings was given as (a) seizures for >1 year, (b) at least 1 seizure in the prior year, and (c) presently taking 2 or more antiepileptic drugs (AEDs). Logistic regression models were constructed to test the cross-sectional association of an abnormal brain MRI with clinical variables. Findings: A total of 217 participants (125 [57%] female; 54 [25%] < 18 years old; 199 [92%] taking AEDs; 154 [71%] with a seizure in the prior year) were enrolled. There was a high prevalence of abnormal brain MRIs (176/217, 81%). Mesial temporal sclerosis was the most common finding (n = 115, 53%, including 24 children), exceeding the number of PWE with neurocysticercosis (n = 26, 12%, including 1 child) and congenital/perinatal abnormalities (n = 29, 14%, including 14 children). The number of AEDs (odds ratio = .59, 'P' = .03) and duration of epilepsy (odds ratio = 1.11, 'P' = .02) were significantly associated with an abnormal MRI. Seizure in the prior month was associated with the presence of mesial temporal sclerosis (odds ratio = .47, 'P' = .01). A total of 25 (12%) participants met our definition of drug-resistant epilepsy, with mesial temporal sclerosis (n = 10), congenital malformations (n = 5), and neurocysticercosis (n = 4) being the more common findings. Conclusions: The prevalence of abnormalities on brain MRI for PWE in resource-limited settings is high as a result of a diffuse range of etiologies, most commonly mesial temporal sclerosis. Drug-resistant epilepsy accounted for 12% of the referral population in a conservative estimation.

Scrub typhus (ST) is a vector-borne rickettsial infection causing acute febrile illness. The re-emergence of ST in the Asia-Pacific region represents a serious public health threat. ST was first detected in Bhutan in 2008. However, the disease is likely to be under-diagnosed and under-reported, and the true impact is difficult to estimate. At the end of 2014, the SD Bioline Tsutsugamushi TestTM rapid diagnostic test (RDT) kits became available in all hospitals to assist clinicians in diagnosing ST. We conducted a retrospective descriptive study, reviewing records from all hospitals of Bhutan to identify all RDT-positive clinical cases of ST in Bhutan in 2015. The aim was to evaluate the burden of ST in Bhutan, describe the demographic, spatial and temporal patterns of disease, and identify the typical clinical presentations. The annual incidence of RDT-positive cases of ST reporting to Bhutanese hospitals in 2015 was estimated to be 62 per 100,000 population at risk. The incidence of disease was highest in the southern districts with a subtropical climate and a high level of agricultural production. The highest proportion of cases (87%) was rural residents, with farmers being the main occupational category. The disease was strongly seasonal, with 97% of cases occurring between June and November, coinciding with the monsoon and agricultural production seasons. Common ST symptoms were not specific, and an eschar was noted by clinicians in only 7.4% of cases, which is likely to contribute to an under-diagnosis of ST. ST represents an important and neglected burden, especially in rural communities in Bhutan. The outcomes of this study will inform public health measures such as timely-awareness programmes for clinicians and the public in high-risk areas, to improve the diagnosis, treatment and clinical outcomes of this disease.

Scrub typhus, or tsutsugamushi disease, is a vectorborne zoonotic disease caused by Orientia tsutsugamushi, which is endemic to the tsutsugamushi triangle, centered in Southeast and Pacific Asia (1). Trombiculid mites [...]

This study presents the structural damage classification of a large-scale bridge, considering several damage scenarios using One dimensional convolutional neural network (1D-CNN). Measurements obtained from the Z24 bridge in Switzerland during the short-term progressive damage tests are used for this study. Acceleration responses at 291 sensor locations are measured under forced and ambient excitations. This study considers only the measurements under ambient excitations, which has the advantage over forced excitation of not required to measure the excitations. Furthermore, to reduce the overall cost of monitoring the structure, this study aims to use fewer sensor measurements. Out of 291 sensors, only three measurements are used in this study. Each measurement contains 65,536 samples collected at a sampling frequency of 100 Hz. The measurements from three sensors are processed into shorter lengths of 150 data points, each with a 50% overlap. The processed data are inputted to the proposed 1D-CNN model. The proposed 1D-CNN consists of two 1D-CNN networks with different kernel sizes to perform better with different abstract features. The flattened outputs from these two networks using the same input are concatenated and fed into a fully connected dense network for damage classification. The labelled outputs are the different damage scenarios introduced in the progressive damage tests. The performance of the proposed approach is measured in terms of accuracy supported by a confusion matrix. The performance is measured for three cases. The result indicates that better performance is obtained compared to a previous study with the fused features as input to the deep learning models, although fewer sensors are used. Practical Applications: The findings from this study demonstrated that a good damage classification could be achieved using fewer sensor measurements from a large-scale bridge. The Z24 bridge benchmark data are used as an example in this study. Several damage scenarios were considered during the progressive damage test, and all tests were performed under ambient and forced excitation conditions. A multi-headed, one-dimensional convolutional neural network is proposed to classify the damages using the ambient condition data set. The performance is compared with an existing study using the same data set, but the data pre-processing techniques and model are improved. Three cases are defined by varying the size and length of the available time-series data. The proposed model has obtained better damage classification results for all the cases than an existing study. The advantage of the study is that the damage classification is performed using data obtained from a real large-scale structure under ambient conditions, eliminating the need for external force excitation. The proposed method could also be used for condition monitoring and safety evaluation of aerospace and mechanical structures. [ABSTRACT FROM AUTHOR]

Austenitic Fe–Cr–Ni stainless steel is widely used in aviation, chemistry, energy, due to its excellent properties of high-temperature performance. In this study, the splitting Hopkinson pressure bar with high-temperature system was employed to evaluate the dynamic mechanical properties of Fe–Cr–Ni stainless steel. The true stress-strain curves were obtained under varying conditions, including variable strains, strain rates and temperatures. The true stress increases and levels off as the true strain increases, while increases as the strain rate increases, but decreases sharply as the deformation temperature rises. The deformation temperature is consist of healing temperature and adiabatic temperature. The adiabatic temperature rise related to the specific heat capacity was calculated. The actual deformation temperatures were calculated under different strains by combining the true stress-strain curves. The true stress-strain curve under variable temperature was corrected to the stress-strain curve under isothermal state by using the thermal softening rate, which decoupled the strain and temperature. The Power-Law and Johnson-Cook constitutive models were fitted based on the real stress-strain isothermal curve. The fitting accuracy of Power-Law model was 1.61% for different strain rates at room temperature in average, 3.51% for fixed strain rate at different temperatures. While the fitting accuracy of Johnson-Cook model was 2.94% for different strain rates at room temperature in average, 6.18% for fixed strain rate at different temperatures.

Abstract Background This study leverages a two-sample Mendelian Randomization (MR) approach to explore the causal relationships between 1,400 metabolites and pulmonary fibrosis, using genetic variation as instrumental variables. By adhering to stringent criteria for instrumental variable selection, the research aims to uncover metabolic pathways that may influence the risk and progression of pulmonary fibrosis, providing insights into potential therapeutic targets. Methods Utilizing data from the OpenGWAS project, which includes a significant European cohort, and metabolite GWAS data from the Canadian Longitudinal Aging Study (CLSA), the study employs advanced statistical methods. These include inverse variance weighting (IVW), weighted median estimations, and comprehensive sensitivity analyses conducted using the R software environment to ensure the robustness of the causal inferences. Results The study identified 62 metabolites with significant causal relationships with pulmonary fibrosis, highlighting both risk-enhancing and protective metabolic factors. This extensive list of metabolites presents a broad spectrum of potential therapeutic targets and biomarkers for early detection, underscoring the metabolic complexity underlying pulmonary fibrosis. Conclusions The findings from this MR study significantly advance our understanding of the metabolic underpinnings of pulmonary fibrosis, suggesting that alterations in specific metabolites could influence the risk and progression of the disease. These insights pave the way for the development of novel diagnostic and therapeutic strategies, emphasizing the potential of metabolic modulation in managing pulmonary fibrosis.

High Co–Ni secondary hardening steels are valuable in the field of aviation materials. With the increasing demand of lightweight, further enhancing its strength has received widespread attention. In this study, instead of using only M2C carbides as the reinforcements in the traditional high Co–Ni secondary hardening steels, nano-size NiAl phases were introduced to provide additional strength. To obtain the collaborative precipitation of these two reinforcements, systematically thermodynamic calculation, including the driving force, coarsening rate, etc., was made to quantitatively tailor the composition and the two-step aging parameters. The calculation results showed that adding 1 % Al into the standard composition of M54 is a plan with high potential and a second aging process at 450 °C should be added to promote NiAl precipitation. Based on the experimental validation, the target microstructure formed as the design. With the dual-phase strengthening of NiAl particles and M2C carbides, the yield and tensile strength are greater than 2.3 and 2.7 GPa, respectively, which increases the strength of M54 steel by >30 %, retaining sufficient elongation and relatively low cost. This new designed alloy increased the strength–ductility balance of high Co–Ni secondary hardening steels and aviation maraging steels from ∼12.5 to 13.5 GPa%.

Abstract Enhancing the interpretability of machine learning methods for predicting material properties is a key, yet complex topic in materials science. This study proposes an interpretable convolutional neural network (CNN) to establish the relationship between the microstructural evolution and mechanical properties of non‐uniform and nonlinear multisystem dual‐phase steel materials and achieve an inverse analysis of the elastic‐plastic mechanism. This study demonstrates that the developed CNN model achieves an accuracy of 94% in predicting the stress‐strain curves of dual‐phase steel microstructures with different compositions and processes, with the mean absolute error not exceeding 50 MPa, representing merely 5.26% of the average tensile strength of dual‐phase steels in the dataset. The reverse visualization results of the CNN model indicate that, during tensile deformation, the grain boundaries maintain deformation coordination within the grains by impeding dislocation slip. This results in a significant stress concentration at the grain boundaries, with stresses at the boundaries being higher than those borne by the martensitic phase and minimal stresses in the ferrite phase. Moreover, compared with traditional crystal plasticity models, the CNN model exhibits a substantial improvement in computational efficiency. This method provides a generic plan for improving the interpretability of machine learning methods for predicting material properties and can be easily applied to other alloy systems.