A novel adaptive deep learning model of Covid-19 with focus on mortality reduction strategies.

We employ deep learning to propose an Artificial Neural Network (ANN) based and data stream guided real-time incremental learning algorithm for parameter estimation of a non-intrusive, intelligent, adaptive and online analytical model of Covid-19 disease. Modeling and simulation of such problems pose an additional challenge of continuously evolving training data in which the model parameters change over time depending upon external factors. Our main contribution is that in a scenario of continuously evolving training data, unlike typical deep learning techniques, this non-intrusive algorithm eliminates the need to retrain or rebuild the model from scratch every time a new training data set is received. After validating the model, we use it to study the impact of different strategies for epidemic control. Finally, we propose and simulate a strategy of controlled natural immunization through risk-based population compartmentalization (PC) wherein the population is divided in Low Risk (LR) and High Risk (HR) compartments based on risk factors (like comorbidities and age) and subjected to different disease transmission dynamics by isolating the HR compartment while allowing the LR compartment to develop natural immunity. Upon release from the preventive isolation, the HR compartment finds itself surrounded by enough number of immunized individuals to prevent the spread of infection and thus most of the deaths occurring in this group are avoided.

Risk assessment of COVID-19 pandemic using deep learning model for J&K in India: a district level analysis.

The coronavirus disease 2019 (COVID-19) is an ongoing pandemic with high morbidity and mortality rates. Current epidemiological studies urge the need of implementing sophisticated methods to appraise the evolution of COVID-19. In this study, we analysed the data for 228 days (1 May to 15 December 2020) of daily incidence of COVID-19 cases for a district level analysis in the region of Jammu and Kashmir in the northern Himalayan belt of India. We used a deep learning-based incremental learning technique to model the current trend of COVID-19 transmission and to predict the future trends with 60-day forecasting. The results not only indicate high rates of morbidity and mortality but also forecast high rise in the incidence of COVID-19 in different districts of the study region. We used geographic information system (GIS) for storing, analysing, and presenting the spread of COVID-19 which provides key insights in understanding, planning, and implementing mitigating measures to tackle the current spread of the pandemic and its possible future scenarios. The existing disparity in health care facilities at district level is shown in relation to the spread of disease. The study results also highlight the need to upgrade health care infrastructure in the study region to control the current and future pandemics. These results could be useful for administration and scientific community to develop efficient short-term and long-term strategies against such diseases.

Usual opioid dosing does not adversely affect the course of healthcare-associated Clostridioides difficile infection.

Aim: We sought to determine if opioid exposure may have a detrimental effect on the course of Clostridioides difficile infection (CDI). Materials & methods: We compared opioid exposure in patients with well-defined severe CDI and non-severe CDI. Results: Following exclusions, 403 records were reviewed. Of this group, 128/403 (31.7%) were determined to have severe CDI by strict criteria, and 275/403 (68.3%) were found to have non-severe CDI. Full multivariate regression and reduced model of potential predictors for severe CDI showed no association with opioids prescribed. Conclusion: Opioid exposure (predominantly in modest range) does not appear to be a risk factor for severe healthcare-associated CDI.

Different Munc18 proteins mediate baseline and stimulated airway mucin secretion.

Airway mucin secretion is necessary for ciliary clearance of inhaled particles and pathogens but can be detrimental in pathologies such as asthma and cystic fibrosis. Exocytosis in mammals requires a Munc18 scaffolding protein, and airway secretory cells express all 3 Munc18 isoforms. Using conditional airway epithelial cell-deletant mice, we found that Munc18a has the major role in baseline mucin secretion, Munc18b has the major role in stimulated mucin secretion, and Munc18c does not function in mucin secretion. In an allergic asthma model, Munc18b deletion reduced airway mucus occlusion and airflow resistance. In a cystic fibrosis model, Munc18b deletion reduced airway mucus occlusion and emphysema. Munc18b deficiency in the airway epithelium did not result in any abnormalities of lung structure, particle clearance, inflammation, or bacterial infection. Our results show that regulated secretion in a polarized epithelial cell may involve more than one exocytic machine at the apical plasma membrane and that the protective roles of mucin secretion can be preserved while therapeutically targeting its pathologic roles.

Frequency of Primary Headache Syndromes in Patients with a Major Depressive Disorder.

Purpose The primary objective of this study was to assess the overall frequency of primary headaches in subjects with a moderate to severe major depressive disorder. A further objective was to determine the frequency of primary headache sub-types in this population. Materials and methods This descriptive, cross-sectional study was conducted at the outpatients' clinic of the department of psychiatry, Pakistan Railways Teaching Hospital, an affiliate of Islamic International Medical College, Rawalpindi. The duration of the study was from December 2016 to May 2017. One hundred and ten consecutive patients with a major depressive disorder (MDD) were assessed for a primary headache, according to the diagnostic criteria of International Classification of Headache Disorders second edition (ICHD-2). MDD patients with moderate to severe depression according to the diagnostic and statistical manual of mental disorders (DSM-5) were enrolled in the study. A semi-structured proforma was designed to gather information on sociodemographic variables. The data was analyzed by utilizing Statistical Package for Social Sciences, version 22 (IBM Corp., Armonk, NY, US). Results Of the 110 MDD patients enrolled, a primary headache was present in 45 (40.90%) cases. Additionally, five of these patients had a migraine with aura (11.11%), 12 had a migraine without aura (26.66%), and 28 had a tension-type headache (62.22%). In the females, migraines with or without aura was frequent (35.29%), while a tension-type headache was more common in males (72.72%). Conclusion More than one-third of the sample had a primary headache syndrome, which shows a high comorbidity between a migraine and its variants and MDD. There is a need to undertake further studies with larger samples to elucidate this relationship.

Importance of Mean Red Cell Distribution Width in Hypertensive Patients.

PURPOSE: Red cell distribution width (RDW), expressed in femtoliters (fl), is a measure of the variation in the size of circulating erythrocytes and is often expressed as a direct measurement of the width of the distribution. We aim to observe the mean value of red cell distribution width (RDW) in hypertensive patients. Increased RDW can be used as a tool for early diagnosis, as an inflammatory marker, and a mortality indicator in hypertensive patients due to its close relation to inflammation. MATERIALS AND METHODOLOGY: Hypertensive patients who had the condition for more than one year duration, diagnosed according to the Joint National Committee (JNC 7) criteria were subjected to complete blood count and RDW measurement. One hundred patients, aged between 12 years and 65 years were enrolled from the outpatient department of medicine at the Military Hospital Rawalpindi. RESULTS: The mean age (± SD) of the patients was 51.48 ± 10.08 years. Out of 100 patients 69% were males whereas 31% were females. The overall frequency of hypertension more than five years was 55% subjects whereas 45% individuals had duration of hypertension less than five years. Mean RDW in females was found to be 49.35±8.42 fl while mean RDW in males was 44.78±7.11 fl. An independent sample t-test was applied to assess if there was any significant difference between age and gender. No significant difference between age and gender was found (p<0.05). The Mann-Whitney test was used to assess any association of RDW with gender. RDW values in females was found to be statistically significantly higher than in males (U=603, p=0.01). Linear regression showed that mean RDW value increased with increasing age (P <0.001). CONCLUSIONS: A significant number of patients with hypertension have increased levels of RDW. Therefore, it is recommended that serum RDW should be checked regularly in patients with hypertension.