Influence of Monitoring Strategy on Assessment of Ablation Success and Postablation Atrial Fibrillation Burden Assessment: Implications for Practice and Clinical Trial Design.

BACKGROUND: Various noninvasive intermittent rhythm monitoring strategies have been used to assess arrhythmia recurrences in trials evaluating pharmacological and invasive therapeutic interventions for atrial fibrillation (AF). We determined whether a frequency and duration of noninvasive rhythm monitoring could be identified that accurately detects arrhythmia recurrences and approximates the AF burden derived from continuous monitoring using an implantable cardiac monitor (ICM). METHODS: The rhythm history of 346 patients enrolled in the CIRCA-DOSE trial (Cryoballoon Versus Contact-Force Irrigated Radiofrequency Catheter Ablation) was reconstructed. Using computer simulations, we evaluated event-free survival, sensitivity, negative predictive value, and AF burden of a range of noninvasive monitoring strategies, including those used in contemporary AF ablation trials. RESULTS: A total of 126 290 monitoring days were included in the analysis. At 12 months, 164 patients experienced atrial arrhythmia recurrence as documented by the ICM (1-year event-free survival, 52.6%). Most noninvasive monitoring strategies used in AF ablation trials had poor sensitivity for detecting arrhythmia recurrence. Sensitivity increased with the intensity of monitoring, with serial (3) short-duration monitors (24-/48-hour ECG monitors) missing a substantial proportion of recurrences (sensitivity, 15.8% [95% CI, 8.9%-20.7%] and 24.5% [95% CI, 16.2%-30.6%], respectively). Serial (3) longer-term monitors (14-day ECG monitors) more closely approximated the gold standard ICM (sensitivity, 64.6% [95% CI, 53.6%-74.3%]). AF burden derived from short-duration monitors significantly overestimated the true AF burden in patients with recurrences. Increasing monitoring duration resulted in improved correlation and concordance between noninvasive estimates of the invasive AF burden (R2 = 0.85 and interclass correlation coefficient = 0.91 for serial [3] 14-day ECG monitors versus ICM). CONCLUSIONS: The observed rate of postablation atrial tachyarrhythmia recurrence is highly dependent on the arrhythmia monitoring strategy employed. Between-trial discrepancies in outcomes may reflect different monitoring protocols. On the basis of measures of agreement, serial long-term (7-14 day) intermittent monitors accumulating at least 28 days of annual monitoring provide estimates of AF burden comparable with ICM. However, ICMs outperform intermittent monitoring for arrhythmia detection, and should be considered the gold standard for clinical trials. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01913522.

Artificial intelligence as an emerging technology in the current care of neurological disorders.

BACKGROUND: Artificial intelligence (AI) has influenced all aspects of human life and neurology is no exception to this growing trend. The aim of this paper is to guide medical practitioners on the relevant aspects of artificial intelligence, i.e., machine learning, and deep learning, to review the development of technological advancement equipped with AI, and to elucidate how machine learning can revolutionize the management of neurological diseases. This review focuses on unsupervised aspects of machine learning, and how these aspects could be applied to precision neurology to improve patient outcomes. We have mentioned various forms of available AI, prior research, outcomes, benefits and limitations of AI, effective accessibility and future of AI, keeping the current burden of neurological disorders in mind. DISCUSSION: The smart device system to monitor tremors and to recognize its phenotypes for better outcomes of deep brain stimulation, applications evaluating fine motor functions, AI integrated electroencephalogram learning to diagnose epilepsy and psychological non-epileptic seizure, predict outcome of seizure surgeries, recognize patterns of autonomic instability to prevent sudden unexpected death in epilepsy (SUDEP), identify the pattern of complex algorithm in neuroimaging classifying cognitive impairment, differentiating and classifying concussion phenotypes, smartwatches monitoring atrial fibrillation to prevent strokes, and prediction of prognosis in dementia are unique examples of experimental utilizations of AI in the field of neurology. Though there are obvious limitations of AI, the general consensus among several nationwide studies is that this new technology has the ability to improve the prognosis of neurological disorders and as a result should become a staple in the medical community. CONCLUSION: AI not only helps to analyze medical data in disease prevention, diagnosis, patient monitoring, and development of new protocols, but can also assist clinicians in dealing with voluminous data in a more accurate and efficient manner.

Clinical assessment of AF pattern is poorly correlated with AF burden and post ablation outcomes: A CIRCA-DOSE sub-study.

BACKGROUND: Contemporary guidelines recommend that atrial fibrillation (AF) be classified into paroxysmal and persistent AF based on clinical assessment, with these categorizations forming the basis of therapeutic recommendations. While pragmatic, clinical assessment may introduce misclassification errors, which may impact treatment decisions. We sought to determine the relationship between AF classification, baseline AF burden, and post-ablation arrhythmia outcomes. DESIGN: The current study is a sub-analysis of a prospective, parallel-group, multicenter, single-blinded randomized clinical trial. All 346 patients enrolled in CIRCA-DOSE received an implantable cardiac monitor a median of 72 days prior to ablation. AF was classified as low burden paroxysmal, high burden paroxysmal, or persistent based on clinical assessment prior to device implantation. Prior to ablation patients were re-classified using the same definitions based on device monitoring data. Correlation between classifications, AF burden, and post-ablation arrhythmia outcomes were assessed. RESULTS: There was poor agreement between clinical and device-based AF classification (Cohen's kappa: 0.192). AF classification derived from pre-ablation continuous monitoring reflected baseline and post-ablation AF burden with greater accuracy and with less overlap between the AF classes (P < 0.01 for all categorical comparisons). Patients objectively classified as "Low Burden" paroxysmal by continuous monitoring data had significantly greater freedom from recurrent AF/AT/AFL compared to those classified as "High Burden" paroxysmal (hazard ratio [HR] 0.57 for AF/AT/AFL recurrence) or persistent AF (HR 0.19 for AF/AT/AFL recurrence). CONCLUSIONS: Classification of AF pattern based on pre-ablation continuous cardiac rhythm monitoring better predicted AF burden and freedom from recurrent AF post ablation. Despite the use of standardized definitions, classification of AF based on clinical assessment did not predict baseline AF burden, post ablation AF burden, or freedom from recurrent AF post ablation. TRIAL REGISTRATION: ClinicalTrials.govNCT01913522.

Genre et attitudes de stigmatisation à l'égard des Personnes vivant avec le VIH (PVVIH) au Bénin

Contexte : Les attitudes de rejet des PVVIH constituent un frein à l'accès universel et à leurs droits essentiels. Cet article vise à apporter un éclairage sur les disparités de genre en matière de stigmatisation des PVVIH.Méthodologie : Analyse secondaire des données de l'EDSB 2011-2012. Un indicateur de niveau de stigmatisation a été créé pour faire des analyses multi-variées de régression logistique sur un échantillon de 4813 hommes et 14849 femmes.Résultats : Pour les deux sexes, avoir un niveau élevé d'instruction, être exposé fréquemment aux médias, être chrétien et appartenir au groupe ethnique Adja déterminent l'attitude bienveillante envers les PVVIH. Il en est de même pour les femmes qui sont en union conjugale, celles qui vivent en milieu rural, celles vivant dans des ménages riches ou celles n'ayant aucune activité économique.Conclusion: Développer des stratégies de protection des PVVIH en s'appuyant sur les attitudes bienveillantes observées

La fasciite nécrosante des membres dans un service de chirurgie plastique en milieu tropical

Introduction: La fasciite nécrosante est une urgence chirurgicale et médicale. Cette étude avait pour objectif de décrire le profil épidémiologique, clinique, et thérapeutique des patients ayant une fasciite nécrosante dans un service de chirurgie plastique en milieu tropical. Méthodes : il s'agissait d'une étude rétrospective descriptive de dossiers des patients traités pour une fasciite nécrosante entre janvier 2015 et décembre 2017. Les paramètres d'étude concernaient l'épidémiologie, les signes, le traitement et l'évolution. Les lésions cutanées ont été classées selon les critères de Wong. Le score LRINEC a été établi. Résultats : Sur la période d'étude, 947 patients ont été reçus. Dix-huit avaient une fasciite nécrosante soit 1.9% des patients. Cette étude a concerné 11patients. Il y avait neuf femmes et deux hommes. L'âge moyen était de 47 ans. Tous les patients avaient un faible revenu économique. Une porte d'entrée était notée (n=8). Les pathologies médicales commorbides associées étaient le diabète (n=5), l'infection au VIH (n=2) . La prise d'anti-inflammatoires non stéroïdiens a été noté (n=5). L'usage de cataplasmes était enregistré (n= 8). La notion de prise d'alcool a été notée (n=2). Le délai moyen de consultation était de 29 jours. Les lésions siégeaient au membre inférieur ( n=9) et au membre supérieur (n=2). Le diagnostic était clinique. Les lésions étaient du stade 3. Le score LRINEC a été établi chez huit patients. Il était inférieur à 6 (n=4), égal à 6 (n=2), supérieur ou égal à 8(n=2). Le traitement médical comportait la ceftriaxone associée au métronidazole. Une excision des tissus nécrosés a été faite dans les 24 heures suivant l'admission. Une greffe de peau mince a été réalisée dans un délai moyen de 28,7 jours. Un décès a été enregistré (patiente atteint du VIH avec score LRINEC=13). Au recul moyen de 14 mois il n'y avait pas de récidive. Conclusion : La fasciite nécrosante est rare. Les lésions ont intéressé en général des patients de sexe féminin avec un âge moyen de 47ans. Ils avaient des pathologies médicales commorbides associées à des degrés variables. Le traitement traditionnel à type de cataplasme est un facteur favorisant. La consultation est tardive. Les lésions concernaient les membres inferieurs dans la majorité des cas. Elles étaient de stade 3. Une excision des tissus nécrosés et une greffe de peau mince après la formation d'une granulation ont été faites. Le traitement médical comportait la ceftriaxone associée au métronidazole. Un décès a été noté. Au recul moyen de 14 mois il n'y avait pas de récidives

Usage of EpiFinder clinical decision support in the assessment of epilepsy.

BACKGROUND: The diagnosis of epilepsy is at times elusive for both neurologists and nonneurologists, resulting in delays in diagnosis and therapy. The development of screening methods has been identified as a priority in response to this diagnostic and therapeutic gap. EpiFinder is a novel clinical decision support tool designed to enhance the process of information gathering and integration of patient/proxy respondent data. It is designed specifically to take key terms from a patient's history and incorporate them into a heuristic algorithm that dynamically produces differential diagnoses of epilepsy syndromes. OBJECTIVE: The objective of this study was to test the usability and diagnostic accuracy of the clinical decision support application EpiFinder in an adult population. METHODS: Fifty-seven patients were prospectively identified upon admission to the Epilepsy Monitoring Unit (EMU) for episode classification from January through June of 2017. Based on semiologic input, the application generates a list of epilepsy syndromes. The EpiFinder-generated diagnosis for each subject was compared to the final diagnosis obtained via continuous video electroencephalogram (cVEEG) monitoring. RESULTS: Fifty-three patients had habitual events recorded during their EMU stay. A diagnosis of epilepsy was confirmed (with cVEEG monitoring) in 26 patients while 27 patients were found to have a diagnosis other than epilepsy. The algorithm appropriately predicted differentiation between the presence of an epilepsy syndrome and an alternative diagnosis with 86.8% (46/53 participants) accuracy. EpiFinder correctly identified the presence of epilepsy with a sensitivity of 86.4% (95% confidence interval [CI]: 65.0-97.1) and specificity of 85.1% (95% CI: 70.2-96.4). CONCLUSION: The initial testing of the EpiFinder algorithm suggests possible utility in differentiating between an epilepsy syndrome and an alternative diagnosis in adult patients.

Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population.

When attempting to identify a specific epilepsy syndrome, physicians are often unable to make or agree upon a diagnosis. This is further complicated by the fact that the current classification and diagnosis of epilepsy requires specialized training and the use of resources not typically available to the average clinician, such as training to recognize specific seizure types and electroencephalography (EEG). Even when training and resources are available, expert epileptologists often find it challenging to identify seizure types and to distinguish between specific epilepsy syndromes. Information relevant to the diagnosis is present in narrative form in the medical record across several visits for an individual patient. Our ultimate goal is to create a system that will assist physicians in the diagnosis of epilepsy. This paper explores, as a baseline, text classification methods that attempt to correlate the narrative text features to the diagnosis of West syndrome (Infantile Spasms), using data from Phoenix Children's Hospital (PCH). We tested these methods against a dataset containing known (coded) diagnosis of West Syndrome, and found the best performing method to have a precision / recall / f-measure of 76.8 / 66.7 / 71.4 when evaluated with 10-fold cross validation.

Automatic gene prioritization in support of the inflammatory contribution to Alzheimer's disease.

This research seeks to extend the process of novel therapeutic gene target discovery for the treatment of Alzheimer's disease (AD). Gene-gene and gene-pathway annotation tools as well as human analysis are used to explore likely connections between potential gene targets and biochemical mechanisms of AD and associated genes. Rule-based annotation systems, such as GeneRanker, can be applied to the continuously growing volume of literature to extract relevant gene lists. The subsequent challenge is to abstract biological significance from associated genes to aid in discovery of novel therapeutic gene targets. Automatic annotation of genes deemed significant by data-driven assays and knowledge-driven analysis is limited. Therefore, human analysis is still crucial to exploring novel gene targets and new disease models. This research illustrates a method of analysis of an extracted gene list which lead to the discovery of KNG1 as a possible therapeutic target, suggests a connection between inflammation and AD pathogenesis.