How Stressed are our Postgraduate Medical and Dental Postgraduate Students in Southern Asia? A Cross-Sectional Survey

INTRODUCTION: Stress has been quite commonly reported in the literature among medical and dental students due to the nature of their work. AIM: To assess the level of stress among medical and dental postgraduates in various medical and dental Colleges in Southern Asia.MATERIALS AND METHOD: The study was cross-sectional in nature and conducted among 809 medical and dental postgraduates. Stress was measured using the Cohen’s Perceived stress scale-14 (PSS-14) online through google forms (convenience sampling). Data was entered in MS Excel and descriptive statistics was applied followed by the independent samples t-test, post-hoc modified Bonferroni test and Odd’s Ratio (OR) using SPPS version 22.0.8 Statistical significance was set at 5% (p<0.05).RESULTS: There were 342 (41.3%) medical and 467 (58.7%) dental postgraduates. Most medical postgraduates (73%) reported stress as “severe”, while among dental postgraduates, most of them(32.5%) reported having “mild” stress (p=0.03). Among both medical and dental postgraduates, the third year of their postgraduation was found to be most stressful and the association was found to be significant (p=0.04*, OR:1.5). Unmarried postgraduates among both groups reported having most stress and the association was non-significant (OR: 1.1).CONCLUSION: Both medical and dental postgraduates are requested to practice stress relieving exercises and ask for help if the need arises so

Histone Deacetylase Inhibitors As Potential Therapeutic Agents For Various Disorders

Epigenetic modification acetylation or deacetylation of histone considered as an important element in various disorders. Histone acetyltransferases (HATs) and histone deacetylases (HDACs) are the enzymes which catalyse the acetylation and deacetylation of histone respectively. It helps in regulating the condensation of chromatin and transcription of genes. Lysine acetylation and deacetylation present on the nucleosomal array of histone is the key factor for gene expression and regulation in a normal working living cell. Modification in histone protein will lead to the development of cancer and can cause various neurodegenerative disorders. To safeguard the cells or histone proteins from these diseases histone deacetylase inhibitors are used. In this review, the main focus is upon the role of histone deacetylases inhibitors in various diseases

Neonatal Sepsis as a Major Cause of Morbidity in a Tertiary Center in Kathmandu

Introduction: Neonatal sepsis causes high morbidity and mortality of newborns. The study aims to study the predictors and clinical, haematological and bacteriological factors of neonatal sepsis. 
 Methods: A descriptive cross sectional study was conducted in a Neonatal Intensive Care Unit (NICU) of Paropakar Maternity and Women’s Hospital in Kathmandu between October and December 2011. Demographic, obstetrics, clinical and microbiological data were studied for 300 neonates. 
 Results: The NICU prevalence rate of sepsis was 37.12%. Early onset neonatal sepsis was common (91.39%) (P=0.000). Cesarean section (OR 1.95, 95% CI 1.15-3.31), apgar score <4 at 1 min (P=0.00) and <7 at 5 min of birth (P=0.00) predicted sepsis. Neonates with sepsis were more likely to present with hypothermia (OR 1.180, 95% CI 0.080-17.214), pustules (OR 2.188, 95% CI 0.110-43.465), dehydration (OR 3.040, 95% CI 0.170-54.361), diminished movement (OR 3.082, 95% CI 0.433-21.950) and bulging fontanels (OR 16.464, 95% CI 0.007-41495.430). Coagulase negative Staphylococcus spp. (CoNS) (21, 41.17%) was most common pathogen of neonatal sepsis. Variable antibiotic resistance patterns of isolates with emergence of meropenem resistance in Pseudomonas spp. and methicillin resistance in CoNS and S. aurues were noted. Mortality due to sepsis was highest (15, 8.06%) among total mortalities (21, 11.29%). 
 Conclusions: Delivery via cesarian section, apgar score <4 at 1 min, and <7 at 5 min predicted sepsis. Morbidity and mortality of neonatal sepsis was common in this setting and early maternal and neonatal interventions are required to address this issue. Keywords: morbidity; mortality; neonatal sepsis; predictors

Routine Measurement of Serum Amylase in Acute Abdomen

Introduction: Acute abdominal pain is a common condition presenting to both the emergency department and surgical admission unit. Increase in serum amylase levels are found in much gastrointestinal pathology. Serum amylase level is consistently high in acute pancreatitis though high values are not pathognomonic of pancreatitis .The aim of this study to assess the level of serum amylase in various diseases presenting with acute abdominal pain and to evaluate the role of routine measurement of serum amylase in the screening of patient with acute abdominal pain for the diagnosis of acute pancreatitis in a prospective series. Methods: A prospective observational study was performed from 15th May 2014 – 15th Nov 2014 (6 months) at Department of Surgery of Kathmandu medical College Teaching Hospital; Kathmandu. All consecutive patients presented at emergency department and required admissions in surgical ward were included. A multivariate analysis was performed to assess the level of serum amylase in various diseases presenting with acute abdominal pain including acute pancreatitis. Results: Overall, 318 patients were included during a period of 6 months among them 48 patients were excluded. 34 cases (12.6 %) were diagnosed of acute pancreatitis. three cases (1.1%) of non pancreatic pathology with raised serum amylase level (> 1000 U\L). Conclusions: Routine assessment of serum amylase is helpful in excluding differential diagnosis of patient presenting with acute abdomen and this study identified serum amylase as a good screening tool if done in cases with clinical suspicion.  Keywords: acute abdominal pain; acute pancreatitis; serum amylase

Predicting Falls in Long-term Care Facilities: Machine Learning Study

BackgroundShort-term fall prediction models that use electronic health records (EHRs) may enable the implementation of dynamic care practices that specifically address changes in individualized fall risk within senior care facilities. ObjectiveThe aim of this study is to implement machine learning (ML) algorithms that use EHR data to predict a 3-month fall risk in residents from a variety of senior care facilities providing different levels of care. MethodsThis retrospective study obtained EHR data (2007-2021) from Juniper Communities’ proprietary database of 2785 individuals primarily residing in skilled nursing facilities, independent living facilities, and assisted living facilities across the United States. We assessed the performance of 3 ML-based fall prediction models and the Juniper Communities’ fall risk assessment. Additional analyses were conducted to examine how changes in the input features, training data sets, and prediction windows affected the performance of these models. ResultsThe Extreme Gradient Boosting model exhibited the highest performance, with an area under the receiver operating characteristic curve of 0.846 (95% CI 0.794-0.894), specificity of 0.848, diagnostic odds ratio of 13.40, and sensitivity of 0.706, while achieving the best trade-off in balancing true positive and negative rates. The number of active medications was the most significant feature associated with fall risk, followed by a resident’s number of active diseases and several variables associated with vital signs, including diastolic blood pressure and changes in weight and respiratory rates. The combination of vital signs with traditional risk factors as input features achieved higher prediction accuracy than using either group of features alone. ConclusionsThis study shows that the Extreme Gradient Boosting technique can use a large number of features from EHR data to make short-term fall predictions with a better performance than that of conventional fall risk assessments and other ML models. The integration of routinely collected EHR data, particularly vital signs, into fall prediction models may generate more accurate fall risk surveillance than models without vital signs. Our data support the use of ML models for dynamic, cost-effective, and automated fall predictions in different types of senior care facilities

Dengue virus infection during window period of consecutive outbreaks in Nepal and assessment of clinical parameters

Abstract Nepal is an endemic country for dengue infection with rolling of every 3 year’s clear cyclic outbreaks with exponential growth since 2019 outbreak and the virus gearing towards the non-foci temperate hill regions. However, the information regarding circulating serotype and genotype is not frequent. This research discusses on the clinical features, diagnosis, epidemiology, circulating serotype and genotype among 61 dengue suspected cases from different hospitals of Nepal during the window period 2017–2018 between the two outbreaks of 2016 and 2019. E-gene sequences from PCR positive samples were subjected to phylogenetic analysis under time to most recent common ancestor tree using Markov Chain Monte Carlo (MCMC) and BEAST v2.5.1. Both evolution and genotypes were determined based on the phylogenetic tree. Serotyping by Real-time PCR and Nested PCR showed the co-circulation of all the 3 serotypes of dengue in the year 2017 and only DENV-2 in 2018. Genotype V for DENV-1 and Cosmopolitan Genotype IVa for DENV-2 were detected. The detected Genotype V of DENV-1 in Terai was found close to Indian genotype while Cosmopolitan IVa of DENV-2 found spreading to geographically safe hilly region (now gripped to 9 districts) was close to South-East Asia. The genetic drift of DENV-2 is probably due to climate change and rapid viral evolution which could be a representative model for high altitude shift of the infection. Further, the increased primary infection indicates dengue venturing to new populations. Platelets count together with Aspartate transaminase and Aalanine transaminase could serve as important clinical markers to support clinical diagnosis. The study will support future dengue virology and epidemiology in Nepal