Prevalence of Mood Disorders and Associated Factors at the Time of the COVID-19 Pandemic: Potocol for a Community Survey in La Manouba Governorate, Tunisia

Aims: The present survey aims to assess the overall mood disorder prevalence and identify associated socio-demographic and clinical factors in a Tunisian community sample, with special attention to the COVID-19 pandemic. Background: Mood disorders are one of the leading causes of all non-fatal burdens of disease, with depression being at the top of the list. The COVID-19 pandemic may have increased the prevalence of mood disorders, especially in Low and Middle-income countries (LMICs) and in vulnerable populations. Objective: 1/ Assess point and lifetime prevalence of depressive and bipolar disorders as well as subthreshold bipolarity in a representative population sample of La Manouba governorate and assess treatment patterns for these disorders; 2/Study socio-demographic and clinical correlates of mood disorders 3/ Assess the association between mood disorders and quality of life 4/ Study the impact of the COVID-pandemic on the prevalence of mood disorders 5/ Assess coping mechanisms to the COVID-pandemic and whether these mechanisms moderate the appearance of mood disorders or symptoms since the beginning of the pandemic Methods: This is a household cross-sectional observational survey to be conducted in La Manouba Governorate in a sample of 4540 randomly selected individuals aged ≥ 15 years. Data collection will be carried out by trained interviewers with clinical experience, through face-to-face interviews and the use of the computer assisted personal interviewing approach (CAPI). The following assessment tools are administered: Results: Structured clinical Interview for DSM IV-TR (Mood disorder section and Screening questions on Anxiety), Mood Disorder Questionnaire (MDQ), Suicide Behaviors Questionnaire-Revised (SBQ), 12-item Short Form Survey (SF-12), the Brief-COPE, and a questionnaire about a headache. In addition, socio-demographic and clinical data will be collected. Conclusion: This will be one of the very few household surveys in a general population sample to assess mental health problems and COVID-19-related variables since the beginning of the pandemic. Through this research, we aim to obtain an epidemiological profile of mood disorders in Tunisia and an estimation of the impact of the COVID-19 pandemic on their prevalence. Results should contribute to improving mental health care in Tunisia

Acute myocardial infarction in a patient with hypofibrinogenemia: a case report

<p>Abstract</p> <p>Introduction</p> <p>Congenital fibrinogen deficiency is a rare coagulation disorder usually responsible for hemorrhagic diathesis. However, it can be associated with thrombosis and there have been limited reports of arterial thrombotic complications in these patients.</p> <p>Case presentation</p> <p>A 42-year-old Tunisian man with congenital hypofibrinogenemia and no cardiovascular risk factors presented with new onset prolonged angina pectoris. An electrocardiogram showed features of inferior acute myocardial infarction. His troponin levels had reached 17 ng/L. Laboratory findings confirmed hypofibrinogenemia and ruled out thrombophilia. Echocardiography was not useful in providing diagnostic elements but did show preserved left ventricular function. Coronary angiography was not performed and our patient did not receive any anticoagulant treatment due to the major risk of bleeding. Magnetic resonance imaging confirmed myocardial necrosis. Our patient was managed with aspirin, a beta-blocker, an angiotensin-converting enzyme inhibitor and statin medication. The treatment was well tolerated and no ischemic recurrence was detected.</p> <p>Conclusion</p> <p>Although coronary thrombosis is a rare event in patients with fibrinogen deficiency, this condition is of major interest in view of the difficulties observed in managing these patients.</p

Reducing the Risk of Cognitive Decline and Dementia: WHO Recommendations

With population ageing worldwide, dementia poses one of the greatest global challenges for health and social care in the 21st century. In 2019, around 55 million people were affected by dementia, with the majority living in low- and middle-income countries. Dementia leads to increased costs for governments, communities, families and individuals. Dementia is overwhelming for the family and caregivers of the person with dementia, who are the cornerstone of care and support systems throughout the world. To assist countries in addressing the global burden of dementia, the World Health Organisation (WHO) developed the Global Action Plan on the Public Health Response to Dementia 2017–2025. It proposes actions to be taken by governments, civil society, and other global and regional partners across seven action areas, one of which is dementia risk reduction. This paper is based on WHO Guidelines on risk reduction of cognitive decline and dementia and presents recommendations on evidence-based, multisectoral interventions for reducing dementia risks, considerations for their implementation and policy actions. These global evidence-informed recommendations were developed by WHO, following a rigorous guideline development methodology and involved a panel of academicians and clinicians with multidisciplinary expertise and representing geographical diversity. The recommendations are considered under three broad headings: lifestyle and behaviour interventions, interventions for physical health conditions and specific interventions. By supporting health and social care professionals, particularly by improving their capacity to provide gender and culturally appropriate interventions to the general population, the risk of developing dementia can be potentially reduced, or its progression delayed

Application of Graphene within Optoelectronic Devices and Transistors

Scientists are always yearning for new and exciting ways to unlock graphene's true potential. However, recent reports suggest this two-dimensional material may harbor some unique properties, making it a viable candidate for use in optoelectronic and semiconducting devices. Whereas on one hand, graphene is highly transparent due to its atomic thickness, the material does exhibit a strong interaction with photons. This has clear advantages over existing materials used in photonic devices such as Indium-based compounds. Moreover, the material can be used to 'trap' light and alter the incident wavelength, forming the basis of the plasmonic devices. We also highlight upon graphene's nonlinear optical response to an applied electric field, and the phenomenon of saturable absorption. Within the context of logical devices, graphene has no discernible band-gap. Therefore, generating one will be of utmost importance. Amongst many others, some existing methods to open this band-gap include chemical doping, deformation of the honeycomb structure, or the use of carbon nanotubes (CNTs). We shall also discuss various designs of transistors, including those which incorporate CNTs, and others which exploit the idea of quantum tunneling. A key advantage of the CNT transistor is that ballistic transport occurs throughout the CNT channel, with short channel effects being minimized. We shall also discuss recent developments of the graphene tunneling transistor, with emphasis being placed upon its operational mechanism. Finally, we provide perspective for incorporating graphene within high frequency devices, which do not require a pre-defined band-gap.Comment: Due to be published in "Current Topics in Applied Spectroscopy and the Science of Nanomaterials" - Springer (Fall 2014). (17 pages, 19 figures

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

Background and Objectives: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. Methods: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. Results: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. Conclusions: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS

Comparative effectiveness of autologous hematopoietic stem cell transplant vs fingolimod, natalizumab, and ocrelizumab in highly active relapsing-remitting multiple sclerosis

Importance: Autologous hematopoietic stem cell transplant (AHSCT) is available for treatment of highly active multiple sclerosis (MS). Objective: To compare the effectiveness of AHSCT vs fingolimod, natalizumab, and ocrelizumab in relapsing-remitting MS by emulating pairwise trials. Design, Setting, and Participants: This comparative treatment effectiveness study included 6 specialist MS centers with AHSCT programs and international MSBase registry between 2006 and 2021. The study included patients with relapsing-remitting MS treated with AHSCT, fingolimod, natalizumab, or ocrelizumab with 2 or more years study follow-up including 2 or more disability assessments. Patients were matched on a propensity score derived from clinical and demographic characteristics. Exposure: AHSCT vs fingolimod, natalizumab, or ocrelizumab. Main outcomes: Pairwise-censored groups were compared on annualized relapse rates (ARR) and freedom from relapses and 6-month confirmed Expanded Disability Status Scale (EDSS) score worsening and improvement. Results: Of 4915 individuals, 167 were treated with AHSCT; 2558, fingolimod; 1490, natalizumab; and 700, ocrelizumab. The prematch AHSCT cohort was younger and with greater disability than the fingolimod, natalizumab, and ocrelizumab cohorts; the matched groups were closely aligned. The proportion of women ranged from 65% to 70%, and the mean (SD) age ranged from 35.3 (9.4) to 37.1 (10.6) years. The mean (SD) disease duration ranged from 7.9 (5.6) to 8.7 (5.4) years, EDSS score ranged from 3.5 (1.6) to 3.9 (1.9), and frequency of relapses ranged from 0.77 (0.94) to 0.86 (0.89) in the preceding year. Compared with the fingolimod group (769 [30.0%]), AHSCT (144 [86.2%]) was associated with fewer relapses (ARR: mean [SD], 0.09 [0.30] vs 0.20 [0.44]), similar risk of disability worsening (hazard ratio [HR], 1.70; 95% CI, 0.91-3.17), and higher chance of disability improvement (HR, 2.70; 95% CI, 1.71-4.26) over 5 years. Compared with natalizumab (730 [49.0%]), AHSCT (146 [87.4%]) was associated with marginally lower ARR (mean [SD], 0.08 [0.31] vs 0.10 [0.34]), similar risk of disability worsening (HR, 1.06; 95% CI, 0.54-2.09), and higher chance of disability improvement (HR, 2.68; 95% CI, 1.72-4.18) over 5 years. AHSCT (110 [65.9%]) and ocrelizumab (343 [49.0%]) were associated with similar ARR (mean [SD], 0.09 [0.34] vs 0.06 [0.32]), disability worsening (HR, 1.77; 95% CI, 0.61-5.08), and disability improvement (HR, 1.37; 95% CI, 0.66-2.82) over 3 years. AHSCT-related mortality occurred in 1 of 159 patients (0.6%). Conclusion: In this study, the association of AHSCT with preventing relapses and facilitating recovery from disability was considerably superior to fingolimod and marginally superior to natalizumab. This study did not find evidence for difference in the effectiveness of AHSCT and ocrelizumab over a shorter available follow-up time