title: Functions of Baire Class One over a Bishop Topology

text: If [Formula: see text] is a topology of open sets on a set X, a real-valued function on X is of Baire class one over [Formula: see text], if it is the pointwise limit of a sequence of functions in the corresponding ring of continuous functions C(X). If F is a Bishop topology of functions on X, a constructive and function-theoretic alternative to [Formula: see text] introduced by Bishop, we define a real-valued function on X to be of Baire class one over F, if it is the pointwise limit of a sequence of functions in F. We show that the set [Formula: see text] of functions of Baire class one over a given Bishop topology F on a set X is a Bishop topology on X. Consequently, notions and results from the general theory of Bishop spaces are naturally translated to the study of Baire class one-functions. We work within Bishop’s informal system of constructive mathematics [Formula: see text], that is [Formula: see text] extended with inductive definitions with rules of countably many premises.


title: A Note on Computable Embeddings for Ordinals and Their Reverses

text: We continue the study of computable embeddings for pairs of structures, i.e. for classes containing precisely two non-isomorphic structures. Surprisingly, even for some pairs of simple linear orders, computable embeddings induce a non-trivial degree structure. Our main result shows that although [Formula: see text] is computably embeddable in [Formula: see text], the class [Formula: see text] is not computably embeddable in [Formula: see text] for any natural number [Formula: see text].


title: The Computational Significance of Hausdorff’s Maximal Chain Principle

text: As a fairly frequent form of the Axiom of Choice about relatively simple structures (posets), Hausdorff’s Maximal Chain Principle appears to be little amenable to computational interpretation. This received view, however, requires revision. When attempting to convert Hausdorff’s principle into a conservation theorem, we have indeed found out that maximal chains are more reminiscent of maximal ideals than it might seem at first glance. The latter live in richer algebraic structures (rings), and thus are readier to be put under computational scrutiny. Exploiting the newly discovered analogy between maximal chains and ideals, we can carry over the concept of Jacobson radical from a ring to an arbitrary set with an irreflexive symmetric relation. This achievement enables us to present a generalisation of Hausdorff’s principle first as a semantic and then as a syntactical conservation theorem. We obtain the latter, which is nothing but the desired computational core of Hausdorff’s principle, by passing from maximal chains to paths of finite binary trees of an adequate inductively generated class. In addition to Hausdorff’s principle, applications include the Maximal Clique Principle for undirected graphs. Throughout the paper we work within constructive set theory.


title: Ackermannian Goodstein Sequences of Intermediate Growth

text: The original Goodstein process proceeds by writing natural numbers in nested exponential k-normal form, then successively raising the base to [Formula: see text] and subtracting one from the end result. Such sequences always reach zero, but this fact is unprovable in Peano arithmetic. In this paper we instead consider notations for natural numbers based on the Ackermann function. We define two new Goodstein processes, obtaining new independence results for [Formula: see text] and [Formula: see text], theories of second order arithmetic related to the existence of Turing jumps.


title: On the Perceptron’s Compression

text: We study and provide exposition to several phenomena that are related to the perceptron’s compression. One theme concerns modifications of the perceptron algorithm that yield better guarantees on the margin of the hyperplane it outputs. These modifications can be useful in training neural networks as well, and we demonstrate them with some experimental data. In a second theme, we deduce conclusions from the perceptron’s compression in various contexts.


title: ASNP: A Tame Fragment of Existential Second-Order Logic

text: Amalgamation SNP (ASNP) is a fragment of existential second-order logic that strictly contains binary connected MMSNP of Feder and Vardi and binary connected guarded monotone SNP of Bienvenu, ten Cate, Lutz, and Wolter; it is a promising candidate for an expressive subclass of NP that exhibits a complexity dichotomy. We show that ASNP has a complexity dichotomy if and only if the infinite-domain dichotomy conjecture holds for constraint satisfaction problems for first-order reducts of binary finitely bounded homogeneous structures. For such CSPs, powerful universal-algebraic hardness conditions are known that are conjectured to describe the border between NP-hard and polynomial-time tractable CSPs. The connection to CSPs also implies that every ASNP sentence can be evaluated in polynomial time on classes of finite structures of bounded treewidth. We show that the syntax of ASNP is decidable. The proof relies on the fact that for classes of finite binary structures given by finitely many forbidden substructures, the amalgamation property is decidable.


title: On Simulation in Automata Networks

text: An automata network is a finite graph where each node holds a state from some finite alphabet and is equipped with an update function that changes its state according to the configuration of neighboring states. More concisely, it is given by a finite map [Formula: see text]. In this paper we study how some (sets of) automata networks can be simulated by some other (set of) automata networks with prescribed update mode or interaction graph. Our contributions are the following. For non-Boolean alphabets and for any network size, there are intrinsically non-sequential transformations (i.e. that can not be obtained as composition of sequential updates of some network). Moreover there is no universal automaton network that can produce all non-bijective functions via compositions of asynchronous updates. On the other hand, we show that there are universal automata networks for sequential updates if one is allowed to use a larger alphabet and then use either projection onto or restriction to the original alphabet. We also characterize the set of functions that are generated by non-bijective sequential updates. Following Tchuente, we characterize the interaction graphs D whose semigroup of transformations is the full semigroup of transformations on [Formula: see text], and we show that they are the same if we force either sequential updates only, or all asynchronous updates.


title: On the Complexity of Validity Degrees in Łukasiewicz Logic

text: Łukasiewicz logic is an established formal system of many-valued logic. Decision problems in both propositional and first-order case have been classified as to their computational complexity or degrees of undecidability; for the propositional fragment, theoremhood and provability from finite theories are [Formula: see text] complete. This paper extends the range of results by looking at validity degree in propositional Łukasiewicz logic, a natural optimization problem to find the minimal value of a term under a finite theory in a fixed complete semantics interpreting the logic. A classification for this problem is provided using the oracle class [Formula: see text], where it is shown complete under metric reductions.


title: On the Interplay Between Inductive Inference of Recursive Functions, Complexity Theory and Recursive Numberings

text: The present paper surveys some results from the inductive inference of recursive functions, which are related to the characterization of inferrible function classes in terms of complexity theory, and in terms of recursive numberings. Some new results and open problems are also included.


title: Deterministic and Nondeterministic Iterated Uniform Finite-State Transducers: Computational and Descriptional Power

text: An iterated uniform finite-state transducer ([Formula: see text]) operates the same length-preserving transduction, starting with a sweep on the input string and then iteratively sweeping on the output of the previous sweep. The [Formula: see text] accepts or rejects the input string by halting in an accepting or rejecting state along its sweeps. We consider both the deterministic ([Formula: see text]) and nondeterministic ([Formula: see text]) version of this device. We show that constant sweep bounded [Formula: see text]s and [Formula: see text]s accept all and only regular languages. We study the size cost of removing nondeterminism as well as sweeps on constant sweep bounded [Formula: see text]s, and the descriptional power of constant sweep bounded [Formula: see text]s and [Formula: see text]s with respect to classical models of finite-state automata. Finally, we focus on non-constant sweep bounded devices, proving the existence of a proper infinite nonregular language hierarchy depending on the sweep complexity both in the deterministic and nondeterministic case. Also, we show that the nondeterministic devices are always more powerful than their deterministic variant if at least a logarithmic number of sweeps is given.


title: Prawf: An Interactive Proof System for Program Extraction

text: We present an interactive proof system dedicated to program extraction from proofs. In a previous paper [5] the underlying theory IFP (Intuitionistic Fixed Point Logic) was presented and its soundness proven. The present contribution describes a prototype implementation and explains its use through several case studies. The system benefits from an improvement of the theory which makes it possible to extract programs from proofs using unrestricted strictly positive inductive and coinductive definitions, thus removing the previous admissibility restrictions.


Response by Nguyen et al to Letter Regarding Article, “Mechanical Thrombectomy in the Era of the COVID-19 Pandemic: Emergency Preparedness for Neuroscience Teams: A Guidance Statement From the Society of Vascular and Interventional Neurology”


Addiction in the times of pandemic


Letter by Baracchini and Pieroni Regarding Article, “Protected Code Stroke: Hyperacute Stroke Management During the Coronavirus Disease 2019 (COVID-19) Pandemic”


Response by Khosravani et al to Letter Regarding Article, “Protected Code Stroke: Hyperacute Stroke Management During the Coronavirus Disease 2019 (COVID-19) Pandemic”


title: Decline in Stroke Presentations During COVID-19 Surge

text: We aimed to investigate the acute stroke presentations during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: The data were obtained from a health system with 19 emergency departments in northeast Ohio in the United States. Baseline period from January 1 to March 8, 2020, was compared with the COVID period from March 9, to April 2, 2020. The variables included were total daily stroke alerts across the hospital emergency departments, thrombolysis, time to presentation, stroke severity, time from door-to-imaging, time from door-to-needle in thrombolysis, and time from door-to-puncture in thrombectomy. The 2 time periods were compared using nonparametric statistics and Poisson regression. RESULTS: Nine hundred two stroke alerts during the period across the emergency departments were analyzed. Total daily stroke alerts decreased from median, 10 (interquartile range, 8–13) during baseline period to median, 8 (interquartile range, 4–10, P=0.001) during COVID period. Time to presentation, stroke severity, and time to treatment were unchanged. COVID period was associated with decrease in stroke alerts with rate ratio of 0.70 (95% CI, 0.60–0.28). Thrombolysis also decreased with rate ratio, 0.52 (95% CI, 0.28–0.97) but thrombectomy remained unchanged rate ratio, 0.93 (95% CI, 0.52–1.62) CONCLUSIONS: We observed a significant decrease in acute stroke presentations by ≈30% across emergency departments at the time of surge of COVID-19 cases. This observation could be attributed to true decline in stroke incidence or patients not seeking medical attention for emergencies during the pandemic.


docid: nilrxlru

title: Letter by Sharma and Rasmussen Regarding Article, “Mechanical Thrombectomy in the Era of the COVID-19 Pandemic: Emergency Preparedness for Neuroscience Teams: A Guidance Statement From the Society of Vascular and Interventional Neurology”


Coronatest wird nun für alle bezahlt: Asymptomatische Patienten gehen zum ÖGD


Hämorrhoidalprolaps wurde lebensbedrohlich


title: Nieuwe voorzitter Raad van Bestuur Wendy Borneman: “Ik ben een verbinder”

text: “Intensievere en betere samenwerking met andere partijen, meer focus, verbeterde implementatie en meer snelheid.” Kersverse NHG-bestuursvoorzitter Wendy Borneman hoopt dat het NHG over een jaar stappen heeft gezet als het om deze doelen gaat.


title: Die Leichenschau — ein aktueller Überblick: Rechtsmedizin

text: Bei der Leichenschau gibt es vieles zu beachten, von der richtigen Beleuchtung bis zum Umgang mit Verstorbenen, bei denen COVID-19 diagnostiziert wurde oder der Verdacht auf eine Infektion besteht. Der nachfolgende Beitrag bringt Sie auf den aktuellen Stand und gibt zahlreiche praktische Tipps.


docid: bhlusdiy

title: Global Crises and the Role of BISE


Identification of multiple large deletions in ORF7a resulting in in-frame gene fusions in clinical SARS-CoV-2 isolates


Pandemic, Civil Unrest, and a Tropical Storm – What Is Next? The Locusts??


docid: aptpuvye

title: A Study of Intersubjective Representations of Inferential Information in Health Crisis News Reporting

text: News discourse provides inferential information as well as factual information. Inference is a process of making an epistemic judgement, an act of passing from known facts or evidence to a conclusion with varying degrees of certainty. Intersubjective representations of inferential information in news discourse refer to the ways in which inferences are represented as carrying a higher degree of intersubjectivity.


Interface science in JMS


Approach to the diagnosis and classification of blood diseases


Acute and Chronic Infections of the Oral Cavity and Pharynx


Acute Pneumonia and its Complications


Blood Transfusion


Epidemiology and Infection Prevention and Control


Tropical Gastroenterological Problems


Molecular Pathology—In Situ Hybridization


Infections in Travelers and Adoptees from Abroad


Field Water Disinfection


Allografts: Graft Sterilization and Tissue Banking Safety Issues Graft Sterilization and Tissue Banking Safety Issues


Virus Infections of the Central Nervous System


Diffuse Air-Space Opacities


Nosocomial Infections in the Neonate


Respiratory Viruses


Introduction to Acute Infective Diarrhoea


Cleaning and Disinfecting Gastrointestinal Endoscopic Equipment


Pharyngitis, Stomatitis, Peritonsillar, and Retropharyngeal Abscess


Pulmonary Infections in the Normal Host


Alternative vaccine delivery methods


title: Telehealth Approaches to Care Coordination in Autism Spectrum Disorder

text: This chapter examines the current literature regarding the use of telehealth, and its potential benefits and limitations for diagnosis, treatment, and coordination of care for children diagnosed with Autism Spectrum Disorder (ASD). Barriers to access drive the need to have telehealth as a modality for delivering evidence-based diagnostic and therapeutic processes, which can be impactful in improving developmental trajectories and functional outcomes. The chapter concludes with guidance for clinicians interested in leveraging telehealth, with directions elucidated to further advance the use of telehealth to support families with ASD. More recently, in light of Coronavirus disease 2019 (COVID-19) pandemic and social distancing guidelines and restrictions, this chapter highlights changes in telehealth policy and the use of telehealth for diagnosis and treatment of ASD as well as thoughts about future directions.


title: Persistence of HIV-1 Env-Specific Plasmablast Lineages in Plasma Cells after Vaccination in Humans

text: Induction of persistent HIV-1 Envelope (Env) specific antibody (Ab) is a primary goal of HIV vaccine strategies; however, it is unclear whether HIV Env immunization in humans induces bone marrow plasma cells, the presumed source of long-lived systemic Ab. To define the features of Env-specific plasma cells after vaccination, samples were obtained from HVTN 105, a phase I trial testing the same gp120 protein immunogen, AIDSVAX B/E, used in RV144, along with a DNA immunogen in various prime and boost strategies. Boosting regimens that included AIDSVAX B/E induced robust peripheral blood plasmablast responses. The Env-specific immunoglobulin repertoire of the plasmablasts is dominated by VH1 gene usage and targeting of the V3 region. Numerous plasmablast-derived immunoglobulin lineages persisted in the bone marrow >8 months after immunization, including in the CD138(+) long-lived plasma cell compartment. These findings identify a cellular linkage for the development of sustained Env-specific Abs following vaccination in humans.


title: Predictors of deep-vein thrombosis in subarachnoid hemorrhage: a retrospective analysis

text: BACKGROUND: Subarachnoid hemorrhage is a severe subtype of hemorrhagic stroke, and deep-vein thrombosis is a frequent complication detected in these patients. In addition to other well-established risk factors, the early activation of coagulation systems present in patients with subarachnoid hemorrhage could potentially play a role in the incidence of deep-vein thrombosis. This study aims to identify possible predictors for deep-vein thrombosis related to subarachnoid hemorrhage. METHODS: We conducted a retrospective cohort study on patients with a diagnosis of subarachnoid hemorrhage who presented to our institution between 1 January 2014 and 1 August 2018. We reviewed electronic medical records and analyzed several parameters such as Fisher scale, World Federation of Neurosurgical Surgeons scale, aneurysm site, surgical or endovascular treatment, decompressive craniectomy, vasospasm, infection (meningitis and pneumonia), presence of motor deficit, length of stay in the ICU, length of hospital stay, number of days under ventilator support, d-dimer at hospitalization, and the time to thromboprophylaxis (days). RESULTS: The univariate analysis showed that intraparenchymal cerebral hemorrhage, d-dimer at hospitalization, the time to thromboprophylaxis, motor deficit, and aneurysm located at the internal carotid artery were statistically significant factors. Intraparenchymal cerebral hemorrhage (OR 2,78 95%CI 1.07–7.12), motor deficit (OR 3.46; 95%CI 1.37–9.31), and d-dimer at hospitalization (OR 1.002 95% CI 1.001–1.003) were demonstrated as independent risk factors for deep-vein thrombosis. Length of hospital stay was also found to be significantly longer in patients who developed deep-vein thrombosis (p value 0.018). CONCLUSION: Elevated d-dimer level at the time of hospitalization, motor deficit, and the presence of an intraparenchymal hemorrhage are independent risk factors for deep-vein thrombosis. Patients with DVT also had a significantly longer hospital stay. Even though further studies are needed, patients with elevated d-dimer at hospitalization and intraparenchymal cerebral hemorrhage may benefit from a more aggressive screening strategy for deep-vein thrombosis.


title: A 23-year-old man with left lung atelectasis treated with a targeted segmental recruitment maneuver: a case report

text: BACKGROUND: Lung atelectasis are nonventilated parts of lung tissue and occur as a result of the collapse of the pulmonary parenchyma (alveoli). Various therapeutic procedures for inflating the collapsed pulmonary parenchyma, such as bronchial aspiration and/or standard recruitment maneuvers, are not always successful. CASE PRESENTATION: We report a case of a 23-year-old Croatian man with a parapharyngeal abscess on the left side of the neck with spreading of infection in the mediastinum and left side of the thorax and consequent major atelectasis of the left lung. The patient was mechanically ventilated. We decided to apply a new method in which a pulmonary artery catheter was placed (guided by bronchoscope) on the entrance to the lower left bronchus. The pulmonary artery catheter balloon was inflated to achieve bronchial closure. Using another respirator, we ventilated the affected lobe separately with continuously high pressure of 30 cmH(2)O. After 30 minutes, we removed the pulmonary artery catheter from the lower left bronchus and placed it in the upper left bronchus and repeated the procedure. Our method allowed a significantly longer duration (30 minutes) of continuously high pressure of 30 cmH(2)O separately to only one of the total of five lobes of the lungs while the other four lobes were simultaneously ventilated continuously with protective ventilation mode. CONCLUSION: Use of a pulmonary artery catheter and two respirators in our patient’s case proved to be a successful method for recruiting the atelectatic lung while maintaining protective ventilation of the lung segments without atelectasis.


title: Technology, power, and uncontrolled great power strategic competition between China and the United States

text: Great power competition has returned to the global centre stage. However, the new round competition is developing with unprecedented uncertainties. The fierce competition between China and the U.S. has already expanded from trade to high-tech protection, regional strategies, and two development models supported by different values. The fact of more intertwined geopolitics and technology reflects the underlying intensified competition between China and the U.S. and exacerbates the direct competition between the two powers for control over the rules, norms, and institutions that will govern international relations in the decades to come. This paper discusses whether the competition will slip into a vicious conflict between the two sides or even possibly two blocs that hold differentiated ideologies, political values, and remarkably different economic models.


docid: rdmljitu

title: Engineering antibody therapies for protective immunity


Pediatría de atención primaria centrada en el paciente. ¿Se necesita un cambio de paradigma?


docid: rajiskvc

title: World Brain Day 2020: Move together to end Parkinson's disease


If not now, then when? The importance of intervening early to provide family-based environments for all children


Institutionalisation and deinstitutionalisation of children 2: policy and practice recommendations for global, national, and local actors


title: Desirability Optimization Models to Create the Global Healthcare Competitiveness Index

text: The aim of this research is to enhance desirability optimization models to create a global healthcare competitiveness index (GHCI) covering 53 countries with gross domestic product per capita (GDP PC) of over $10,000. The GHCI is defined as an index that reveals the progress and quality of the healthcare systems in countries providing their patients with easier access opportunities to healthcare services within the scope of this work. Methods of statistical analysis have been adopted together with optimization models and techniques in this research. The optimum and feasible values of the factors considered influential on objective functions have been determined as the basis of healthcare expenditure (HE) and GHCI in those relevant countries. Those released optimum outcomes are displayed between 0.64 and 0.66 in terms of desirability value. The GHCI values of those aforementioned countries range from 0 to 6. The computed average of the GHCI values of those countries is estimated as 2.4758. Finally, GHCI values of 53 countries have been calculated to set the current basis of desirability optimization models. These findings will be deemed as the basic essence of those prospective theories to be established for the future researches to constitute a new index to measure the competitiveness of healthcare systems in various countries all over the world.


Editor’s Perspective – July 2020


title: Predictors of respiratory complications in patients with C5–T5 spinal cord injuries

text: STUDY DESIGN: Retrospective chart audit. OBJECTIVES: Describing the respiratory complications and their predictive factors in patients with acute traumatic spinal cord injuries at C5–T5 level during the initial hospitalization. SETTING: Hospital Vall d’Hebron, Barcelona. METHODS: Data from patients admitted in a reference unit with acute traumatic injuries involving levels C5–T5. Respiratory complications were defined as: acute respiratory failure, respiratory infection, atelectasis, non-hemothorax pleural effusion, pulmonary embolism or haemoptysis. Candidate predictors of these complications were demographic data, comorbidity, smoking, history of respiratory disease, the spinal cord injury characteristics (level and ASIA Impairment Scale) and thoracic trauma. A logistic regression model was created to determine associations between potential predictors and respiratory complications. RESULTS: We studied 174 patients with an age of 47.9 (19.7) years, mostly men (87%), with low comorbidity. Coexistent thoracic trauma was found in 24 (19%) patients with cervical and 35 (75%) with thoracic injuries (p < 0.001). Respiratory complications were frequent (53%) and were associated to longer hospital stay: 83.1 (61.3) and 45.3 (28.1) days in patients with and without respiratory complications (p < 0.001). The strongest predictors of respiratory complications were: previous respiratory disease (OR 5.4, 95% CI: 1.5–19.2), complete motor function impairment (AIS A–B) (OR 4.7, 95% CI: 2.4–9.5) and concurrent chest trauma (OR 3.73, 95% CI: 1.8–7.9). CONCLUSIONS: Respiratory complications are common in traumatic spinal cord injuries between C5–T5. We identified previous respiratory disease, complete motor function impairment and the coexistence of thoracic trauma as predictors of respiratory complications. Identification of patients at risk might help clinicians to implement preventive strategies.


title: Facial fractures and associated injuries in high- versus low-energy trauma: all are not created equal

text: INTRODUCTION: Facial fractures (FFs) occur after high- and low-energy trauma; differences in associated injuries and outcomes have not been well articulated. OBJECTIVE: To compare the epidemiology, management, and outcomes of patients suffering FFs from high-energy and low-energy mechanisms. METHODS: We conducted a 6-year retrospective local trauma registry analysis of adults aged 18–55 years old that suffered a FF treated at the Santa Barbara Cottage Hospital. Fracture patterns, concomitant injuries, procedures, and outcomes were compared between patients that suffered a high-energy mechanism (HEM: motor vehicle crash, bicycle crash, auto versus pedestrian, falls from height > 20 feet) and those that suffered a low-energy mechanism (LEM: assault, ground-level falls) of injury. RESULTS: FFs occurred in 123 patients, 25 from an HEM and 98 from an LEM. Rates of Le Fort (HEM 12% vs. LEM 3%, P = 0.10), mandible (HEM 20% vs. LEM 38%, P = 0.11), midface (HEM 84% vs. LEM 67%, P = 0.14), and upper face (HEM 24% vs. LEM 13%, P = 0.217) fractures did not significantly differ between the HEM and LEM groups, nor did facial operative rates (HEM 28% vs. LEM 40%, P = 0.36). FFs after an HEM event were associated with increased Injury Severity Scores (HEM 16.8 vs. LEM 7.5, P <0.001), ICU admittance (HEM 60% vs. LEM 13.3%, P <0.001), intracranial hemorrhage (ICH) (HEM 52% vs. LEM 15%, P <0.001), cervical spine fractures (HEM 12% vs. LEM 0%, P = 0.008), truncal/lower extremity injuries (HEM 60% vs. LEM 6%, P <0.001), neurosurgical procedures for the management of ICH (HEM 54% vs. LEM 36%, P = 0.003), and decreased Glasgow Coma Score on arrival (HEM 11.7 vs. LEM 14.2, P <0.001). CONCLUSION: FFs after HEM events were associated with severe and multifocal injuries. FFs after LEM events were associated with ICH, concussions, and cervical spine fractures. Mechanism-based screening strategies will allow for the appropriate detection and management of injuries that occur concomitant to FFs. TYPE OF STUDY: Retrospective cohort study. LEVEL OF EVIDENCE: Level III.


title: Second-Order Optimality Conditions in Locally Lipschitz Inequality-Constrained Multiobjective Optimization

text: The main goal of this paper is to give some primal and dual Karush–Kuhn–Tucker second-order necessary conditions for the existence of a strict local Pareto minimum of order two for an inequality-constrained multiobjective optimization problem. Dual Karush–Kuhn–Tucker second-order sufficient conditions are provided too. We suppose that the objective function and the active inequality constraints are only locally Lipschitz in the primal necessary conditions and only strictly differentiable in sense of Clarke at the extremum point in the dual conditions. Examples illustrate the applicability of the obtained results.


title: Conclusions: Still Risking Implementation Gaps

text: Continuity and differentiation elements in the administrative reform cycles are considered from the perspective of implementation, and its gaps. The reformist seasons of the last 25 years mostly shared the same principles, goals and weaknesses in their implementation phases. The vicious cycle of administrative reforms has not been defused: the widespread disagreement in the policy community against further waves of comprehensive reform is an indicator of a persistent low degree of practical implementation, and rather of the prevalence of contradictory effects with respect to reforming principles and goals, like the performance evaluation introduced by statute in 2009. Creeping resistance within administrations is a constant presence, apparently unaffected by several waves of normative innovation. Notwithstanding the recent call for “concreteness” of the Five-Star Movement and League “government of change”, we find that the lack of empirical, in-depth organizational analysis gives the real measure of current complexity to be dealt with.


24th Annual Scientific Meeting of the International Society of Cardiovascular Pharmacotherapy


title: A strong dollar: help or harm?

text: Strong policies that deliver stronger fundamentals and a stronger currency are very much in the national interest. There can be some short-term advantages to currency depreciation, but the United States is better served by making clear that we intend to pursue strong policies, and in turn that generates a well-functioning international order. There has been a lot of progress with internationalization of the Renminbi, but there are some pretty serious obstacles to its becoming a major reserve currency. Clearly the Chinese Renminbi is playing more of a role in international finance. However, there are foundations for being a major international currency, and right now China does not seem to be moving too quickly to build those. These include capital controls, heavy management of the exchange rate, and financial repression. The phase one managed trade deal with China has targets that are likely unachievable, and continuing protectionist US policies would more likely put upward pressure on the dollar. It would be nice for the US dollar to remain strong because we have really good policy and fundamentals. It seems more likely we're going to remain strong because looking at Europe, Japan, and China, nobody is an impressive competitor.


title: The great delusion of engagement: how China should compete with America

text: Faced with a fundamental shift in America’s China policy, Beijing should have a clear-eyed analysis of its choices and strategies. It is no longer feasible for China to hide its capabilities and bide its time. Instead, competition must be met with competition. Thus, China should rethink how to improve its competitive strength vis-à-vis the United States. Strength stems from not only economic and military power, but also international legitimacy. To bolster its international legitimacy, China should improve relations with its neighbors, enable the international community to have a larger share of its prosperity, articulate broadly appealing political values, and make its national identity more inclusive. These four steps are not confrontational, but they will make China a more formidable competitor vis-à-vis the United States.


title: Blockchain for Internet of Medical Things: A Technical Review

text: The Internet of Medical Things (IoMT) represents a network of implantable or wearable medical devices that continuously collect medical data about the patient’s health status. These data are heavy, sensitive and require high level of security. With the emergence of blockchain technology, researchers are focusing on using blockchain strategies to bring security to healthcare applications. However, such integration is very difficult and challenging due to the different requirements in these two technologies. We present in this paper a technical review of existing solutions applying blockchain technology on IoMT. We analyze these studies, discuss the proposed architectures and how they managed the integration challenges. The open issues regarding the application of blockchain over IoMT are also specified.


title: Uncertainty in IoT for Smart Healthcare: Challenges, and Opportunities

text: According to Knight, uncertainty signifies deviations from the expected states, which prevent us from the use of any probability for the determination of a result for a given action or decision [1]. This paper describes the phenomenon of uncertainty in the face of technological megatrends and challenges associated with them. The article focuses on the analysis of the uncertainty in one of the most important technology trends – the Internet of Things (IoT) – on the example of Healthcare. The right decisions are not always equivalent to good results. Sometimes, the decision taken in accordance with general rules brings worse results than the one who breaks them. Such a situation is possible as a result of the uncertainty accompanying the predictions of the future. In this article the concept of the IoT is treated as a big, complex, dynamic system with specific characteristics, dimensions. structures and behaviors. The aim of the article is to analyze the factors that may determine the uncertainty and ambiguity of such systems in the context of the development of Healthcare, and recommendations are made for future research directions.


title: Study of Healthcare Professionals’ Interaction in the Patient Records Based on Annotations

text: The annotation practice is an almost daily activity; it is used by healthcare professionals (PHC) to analyze, collaborate, share knowledge and communicate, between them, information present in the healthcare record of patients. These annotations are created in a healthcare cycle that consists of: diagnosis, treatment, advice, follow-up and observation. Due to an exponential increase in the number of medical annotation systems that are used by different categories of health professionals, we are faced with a problem of lack of organization of medical annotation systems developed on the basis of formal criteria. As a result, we have a fragmented image of these annotations tools which make the mission of choice of an annotation system by a PHC, in a well-defined context (biology, radiology…) and according to their needs to the functionalities offered by these tools, are difficult. In this article we present a classification of thirty annotation tools developed by industry and academia based on 5 generic criteria. We conclude this survey paper with model proposition.


title: Machine Learning Classification Models with SPD/ED Dataset: Comparative Study of Abstract Versus Full Article Approach

text: In response to the researchers need in the bio-medical domain, we opted for automating the bibliographic research stage. In this context, several classification models of supervised machine learning are used. Namely the SVM, Random Forest, Decision Tree, KNN, and Gradient Boosting. In this paper, we conduct a comparative study between experimental results of full article classification and abstract classification approaches. Furthermore, we evaluate our results by using evaluation metrics such as accuracy, precision, recall and F1-score. We observe that the abstract approach outperforms the full article approach in terms of learning time and efficiency.


title: Mobile Assistive Application for Blind People in Indoor Navigation

text: Navigation is an important human task that needs the human sense of vision. In this context, recent technologies developments provide technical assistance to support the visually impaired in their daily tasks and improve their quality of life. In this paper, we present a mobile assistive application called “GuiderMoi” that retrieves information about directions using color targets and identifies the next orientation for the visually impaired. In order to avoid the failure in detection and the inaccurate tracking caused by the mobile camera, the proposed method based on the CamShift algorithm aims to introduce better location and identification of color targets. Tests were conduct in natural indoor scene. The results depending on the distance and the angle of view, defined the accurate values to have a highest rate of target recognition. This work has perspectives for this such as implicating the augmented reality and the intelligent navigation based on machine learning and real-time processing.


title: Trust Execution Environment and Multi-party Computation for Blockchain e-Health Systems

text: Blockchain is a rich and attractive domain for researchers since it is independent of “third party” such as Bank or government. This “open” phenomenon does not respect all the security criteria such as private data protection and confidentiality; hence, we cannot trust this approach despite its contributions. Blockchain technology has gained considerable progress in recent years in fields such as e-health. The medical data contains personal and sensitive information that must be preserved. The current Blockchain systems suffer from serious practical limitations, e.g. poor performance, high-energy consumption and lack of confidentiality. On the other hand, Trust Execution Environment TEE is imperfect; it is based on the centralization of data. To avoid data centralization and its limitations, an approach based on collecting the necessary data from distributed database is presented in this paper. Our goals are to protect the user’s privacy and to execute it in TEE combined with Multi-party computation MPC. We proof by security analysis that our new solution meets the fundamental criteria of security such as confidentiality and privacy.


title: The PULSE Project: A Case of Use of Big Data Uses Toward a Cohomprensive Health Vision of City Well Being

text: Despite the silent effects sometimes hidden to the major audience, air pollution is becoming one of the most impactful threat to global health. Cities are the places where deaths due to air pollution are concentrated most. In order to correctly address intervention and prevention thus is essential to assest the risk and the impacts of air pollution spatially and temporally inside the urban spaces. PULSE aims to design and build a large-scale data management system enabling real time analytics of health, behaviour and environmental data on air quality. The objective is to reduce the environmental and behavioral risk of chronic disease incidence to allow timely and evidence-driven management of epidemiological episodes linked in particular to two pathologies; asthma and type 2 diabetes in adult populations. developing a policy-making across the domains of health, environment, transport, planning in the PULSE test bed cities.


title: Evaluation of Stationary Wavelet Transforms in Reconstruction of Pure High Frequency Oscillations (HFOs)

text: High frequency oscillations (HFO) from, MEG (magnetoencephalography) and intracerebral EEG are considered as effective tools to identify cognitive status and several cortical disorders especially in epilepsy diagnosis. The aim of our study is to evaluate stationary wavelet transform (SWT) technique performance in efficient reconstruction of pure epileptic high frequency oscillations, reputed as biomarkers of epileptogenic zones: generators of inter ictal epileptic discharges, and offhand seizures. We applied SWT on simulated and real database to detect non-contaminated HFO by spiky element. For simulated data, we computed the GOF of reconstruction that reaches for all studied constraint (relative amplitude, frequency, SNR and overlap) a promising results. For real data we used time frequency domain to evaluate SWT robustness of HFO reconstruction. We proved that SWT is an efficient filtering technique for separation HFO from spiky events. Our results would have an important impact on the definition of epileptogenic zones.


title: Study of Middleware for Internet of Healthcare Things and Their Applications

text: The rapid proliferation and miniaturization of the wireless and embedded devices has led to the invasion of the Internet of Things in many domains and has reached the healthcare sector to form what is called the Internet of Healthcare Things (IoHT) . The growing number of the applications in the Internet of Healthcare Things as well as the overwhelming number of heterogeneous medical devices that should interact in this network has put the researchers and developers in front of lot of challenges: How to facilitate the implementation of the various healthcare applications? And how to ease the integration of new devices and make their interoperation a transparent task for the developers? To fulfill these requirements, lot of middleware have been proposed. In this paper we provide a complete study on the existing middleware for IoHT and specify their applications, we propose a taxonomy for them and we present their main advantages and drawbacks.


title: Application of Blockchain Technology in Healthcare: A Comprehensive Study

text: Blockchain technology has been emerged in the last decade and has gained a lot of interests from several sectors such as finance, government, energy, health, etc. This paper gives a broad ranging survey of the application of blockchain in healthcare domain. In fact, the ongoing research in this area is evolving rapidly. Therefore, we have identified several use cases in the state of art applying the blockchain technology, for instance for sharing electronic medical records, for remote patient monitoring, for drug supply chain, etc. We have focused also on identifying limitations of studied approaches and finally we have discussed some open research issues and the areas of future research.


docid: fdeltwej

title: A Fuzzy-Ontology Based Diabetes Monitoring System Using Internet of Things

text: The majority of the Internet-of-things (IoT)-based health monitoring systems adopt ontologies to represent and interoperate the huge quantity of data collected. Classical ontologies cannot appropriately treat imprecise and ambiguous knowledge. The integration of Fuzzy logic theory with ontology can effectively resolve knowledge problems with uncertainty. It considerably raises the accuracy and the precision of healthcare decisions. This paper presents a fuzzy-ontology based system using the internet of things and aims to ensure continues monitoring of diabetic patients. It mainly describes the ontology-based model and the semantic fuzzy decision-making mechanism. The system is evaluated using semantic querying. The results indicate its feasibility for effective remote continuous monitoring for diabetes.


title: Using Learning Techniques to Observe Elderly’s Behavior Changes over Time in Smart Home

text: Smart environments and technology used for elder care, increases independent living time and cuts long-term care costs. A key requirement for these systems consists in detecting and informing about abnormal behavior in users’routines. In this paper, our objective is to automatically observe the elderly behavior over time and detect anomalies that may occur on the long term. Therefore, we propose a learning method to formalize a normal behavior pattern for each elderly people related to his Activities of Daily Living (ADL). We also adopt a temporal similarity score between activities that allows to detect behavior changes over time. In change behavior period we focus on each activity to detect anomalies. A use case with real datasets are promising.


title: Modeling and Specification of Bootstrapping and Registration Design Patterns for IoT Applications

text: The architectures of software systems are becoming more complex, large, and dynamic. The design of these architectures allows architects to master building complex software systems. But, their informal description, may give rise to ambiguity, their understanding becomes more and more difficult and leads to the incorrect implementation of these software systems. There are many solutions allowing software architecture design. In this paper, we use software design patterns as a solution. This is due to their reusable software elements. Our principal objective is to propose other alternatives to the informal visual description of software architectures. In past work, we have studied Service Oriented Architectures. We used SOA design patterns with standard formal notations. This work is a continuation to the past one. We apply our approach on design patterns for the Internet of Things. We introduce a refinement-based approach for modeling IoT design patterns. It takes advantage of graphical modeling and formal method. It is organized around two main axes. The first axis is to provide modeling solutions in conformance with the UML standard language. The second axis covers the general specification of design pattern models with the Event-B method. As a result, we propose a design support tool for IoT architectures based on IoT design patterns. It allows modeling of correct-by-design software systems.


title: Respiratory Activity Classification Based on Ballistocardiogram Analysis

text: Ballistocardiogram signals describe the mechanical activity of the heart. It can be measured by an intelligent mattress in a totally unobtrusive way during periods of rest in bed or sitting on a chair. The BCG signals are highly vulnerable to artefacts such as noise and movement making useful information like respiratory activities difficult to extract. The purpose of this study is to investigate a classification method to distinguish between seven types of respiratory activities such as normal breathing, cough and hold breath. We propose a feature selection method based on a spectral analysis namely spectral flatness measure (SFM) and spectral centroid (SC). The classification is carried out using the nearest neighbor classifier. The proposed method is able to discriminate between the seven classes with the accuracy of 94% which shows its usefulness in context of Telemedicine.


title: Baseline Modelling and Composite Representation of Unobtrusively (IoT) Sensed Behaviour Changes Related to Urban Physical Well-Being

text: We present the grounding approach, deployment and preliminary validation of the elementary devised model of physical well-being in urban environments, summarizing the heterogeneous personal Big Data (on physical activity/exercise, walking, cardio-respiratory fitness, quality of sleep and related lifestyle and health habits and status, continuously collected for over a year mainly through wearable IoT devices and survey instruments in 7 global testbed cities) into 5 composite domain indicators/indexes convenient for interpretation and use in predictive public health and preventive interventions. The approach is based on systematized comprehensive domain knowledge implemented through range/threshold-based rules from institutional and study recommendations, combined with statistical methods, and will serve as a representative and performance benchmark for evolution and evaluation of more complex and advanced well-being models for the aimed predictive analytics (incorporating machine learning methods) in subsequent development underway.


title: Human Activities Recognition in Android Smartphone Using WSVM-HMM Classifier

text: Being able to recognize human activities is essential for several applications such as health monitoring, fall detection, context-aware mobile applications. In this work, we perform the recognition of the human activity based on the combined Weighted SVM and HMM by taking advantage of the relative strengths of these two classification paradigms. One significant advantage in WSVMs is that, they deal the problem of imbalanced data but his drawback is that, they are inherently static classifiers - they do not implicitly model temporal evolution of data. HMMs have the advantage of being able to handle dynamic data with certain assumptions about stationary and independence. The experiment results on real datasets show that the proposed method possess the better robustness and distinction.


title: ForeSight - An AI-driven Smart Living Platform, Approach to Add Access Control to openHAB

text: We created an approach for a smart living platform called ForeSight which consists of different modules: a service engineering module, a Web of Things (WoT)-based Internet of Things (IoT) module and an artificial intelligence (AI) component. This paper describes how openHAB, a smart home middleware, is extended to fulfill platform requirements related to a successful interaction with the IoT module of ForeSight, more precisely, to add identity and access management (IAM) to openHAB and comply with European privacy laws.


title: A Hybrid Approach for Heart Disease Diagnosis and Prediction Using Machine Learning Techniques

text: Heart disease is considered as one of the major causes of death throughout the world. It cannot be easily predicted by the medical practitioners as it is a difficult task which demands expertise and higher knowledge for prediction. Currently, the recent development in medical supportive technologies based on data mining, machine learning plays an important role in predicting cardiovascular diseases. In this paper, we propose a new hybrid approach to predict cardiovascular disease using different machine learning techniques such as Logistic Regression (LR), Adaptive Boosting (AdaBoostM1), Multi-Objective Evolutionary Fuzzy Classifier (MOEFC), Fuzzy Unordered Rule Induction (FURIA), Genetic Fuzzy System-LogitBoost (GFS-LB) and Fuzzy Hybrid Genetic Based Machine Learning (FH-GBML). For this purpose, the accuracy and results of each classifier have been compared, with the best classifier chosen for a more accurate cardiovascular prediction. With this objective, we use two free software (Weka and Keel).


title: Deep Learning-Based Approach for Atrial Fibrillation Detection

text: Atrial Fibrillation (AF) is a health-threatening condition, which is a violation of the heart rhythm that can lead to heart-related complications. Remarkable interest has been given to ECG signals analysis for AF detection in an early stage. In this context, we propose an artificial neural network ANN application to classify ECG signals into three classes, the first presents Normal Sinus Rhythm NSR, the second depicts abnormal signal with Atrial Fibrillation (AF) and the third shows noisy ECG signals. Accordingly, we achieve 93.1% accuracy classification results, 95.1% of sensitivity, 90.5% of specificity and 98%. Furthermore, we yield a value of zero error and a low value of cross entropy, which prove the robustness of the proposed ANN model architecture. Thus, we outperform the state of the art by achieving high accuracy classification without pre-processing step and without high level of feature extraction, and then we enable clinicians to determine automatically the class of each patient ECG signal.


title: Remote Health Monitoring Systems Based on Bluetooth Low Energy (BLE) Communication Systems

text: Nowadays, remote healthcare monitoring systems (RHMS) are attracting patients, doctors and caregivers. RHMS reduces the number of unessential hospitalizations by providing the required healthcare services for patients at home. Furthermore, continuous health monitoring using RHMS is a hopeful solution for elderly people suffering from chronic diseases. RHMS is in general three tiers architecture where the first tier uses intelligent wearable sensors to gather physiological signs. The majority of wearable sensors constructors commercialized sensing devices with Bluetooth Low Energy (BLE) communication interfaces, which lead to the development of diverse RHMS deploying BLE communication interfaces for physiological patient data gathering. In this paper, we introduce the basic concepts related to RHMS design and development. Besides that, we focus our investigation on the BLE communication protocol used in the healthcare context and its configuration to sense several physiological data. Also, we highlight the different steps enabling reading sensed data on mobile application.


title: A Convolutional Neural Network for Lentigo Diagnosis

text: Using Reflectance Confocal Microscopy (RCM) for lentigo diagnosis is today considered essential. Indeed, RCM allows fast data acquisition with a high spatial resolution of the skin. In this paper, we use a deep convolutional neural network (CNN) to perform RCM image classification in order to detect lentigo. The proposed method relies on an InceptionV3 architecture combined with data augmentation and transfer learning. The method is validated on RCM data and shows very efficient detection performance with more than 98% of accuracy.


title: Machine Learning Based Rank Attack Detection for Smart Hospital Infrastructure

text: In recent years, many technologies were racing to deliver the best service for human being. Emerging Internet of Things (IoT) technologies made birth to the notion of smart infrastructures such as smart grid, smart factories or smart hospitals. These infrastructures rely on interconnected smart devices collecting real-time data in order to improve existing procedures and systems capabilities. A critical issue in smart infrastructures is the information protection which may be more valuable than physical assets. Therefore, it is extremely important to detect and deter any attacks or breath to the network system for information theft. One of these attacks is the rank attack that is carried out by an intruder node in order to attract legitimate traffic to it, then steal personal data of different persons (both patients and staffs in hospitals). In this paper, we propose an anomaly based rank attack detection system against an IoT network using Support Vector Machines. As a use case, we are interested in the healthcare sector and in particular in smart hospitals which are multifaceted with many challenges such as service resilience, assets interoperability and sensitive information protection. The proposed intrusion detection system (IDS) is implemented and evaluated using Conticki Cooja simulator. Results show a high detection accuracy and low false positive rates.


docid: xiggsrjy

title: A Novel On-Wrist Fall Detection System Using Supervised Dictionary Learning Technique

text: Wrist-based fall detection system provides a very comfortable and multi-modal healthcare solution, especially for elderly risking falls. However, the wrist location presents a very challenging and unstable spot to distinguish falls among other daily activities. In this paper, we propose a Supervised Dictionary Learning approach for wrist-based fall detection. Three Dictionary learning algorithms for classification are invoked in this study, namely SRC, FDDL, and LRSDL. To extract the best descriptive representation of the signal data we followed different preprocessing scenarios based on accelerometer, gyroscope, and magnetometer. A considerable overall performance was obtained by the SRC algorithms reaching respectively 99.8%, 100%, and 96.6% of accuracy, sensitivity, and specificity using raw data provided by a triaxial accelerometer, accordingly overthrowing previously proposed methods for wrist placement.


title: Context-Aware Healthcare Adaptation Model for COPD Diseases

text: Nowadays, ubiquitous computing and mobile applications are controlling all our life’s aspects, from social media and entertainment to the very basic needs like commerce, learning, government, and health. These systems have the ability to self-adapt to meet changes in their execution environment and the user’s context. In the healthcare domain, information systems have proven their efficiency, not only by organizing and managing patients’ data and information but also by helping doctors and medical experts in diagnosing disease and taking precluding procedure to avoid serious conditions. In chronic diseases, telemonitoring systems provide a way to monitor the patient’s state and biomarkers within their usual life’s routine. In this article, we are combining the healthcare telemonitoring systems with the context awareness and self-adaptation paradigm to provide a self-adaptive framework architecture for COPD patients.


title: Automatic Daily Activity Schedule Planning for Simulating Smart House with Elderly People Living Alone

text: A simulation tool that supports developers to build scenarios automatically in multiple simulation platforms is proposed. As an essential part of this simulator, this study proposed an activity schedule generator to mimic the daily life of elderly people living alone. This generator outperforms existing methods of activity schedule planning in three aspects: 1) it is adaptive to the layout of a simulated smart house; 2) there is no unspecified time in the timeline of generated schedules; and 3) it generates stable, but not tedious schedules for a number of days. A real-time location data generator is proposed to convert generated schedules to simulated real-time location data of the resident, and a proposed interface converts these simulated location data to simulated records of virtual passive infrared (PIR) sensors, which can be used to optimize placement of PIR sensors in a smart house.


title: Secure E-Health Platform

text: Currently, the Internet has become a service hosting infrastructure through its interconnection of a very large number of heterogeneous objects, thus offering users several types of services implemented by different sectors. Although these services make people’s lives easier and provide them with a means of communication between their real and virtual worlds, they risk being a path of intrusion into their private lives, or in some cases an easy target for malicious individuals aiming to endanger human life. To avoid this, we have designed a secure e-health platform based on IoT that serves to monitor patients’ medical profiles remotely by collecting their medical records while ensuring their confidentiality and integrity.


docid: dffnvxnf

title: Alzheimer’s Disease Early Detection Using a Low Cost Three-Dimensional Densenet-121 Architecture

text: The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good results: a deep neural network showing metrics of 87% accuracy, 87% sensitivity (micro-average), 88% specificity (micro-average), and 92% AUROC (micro-average) for the task of classifying five different classes (disease stages). The use of tools available for free means that this work can be replicated in developing countries.


title: Older People’s Needs and Opportunities for Assistive Technologies

text: Older adults experience a disconnect between their needs and adoption of technologies that have potential to assist and to support more independent living. This paper reviewed research that links people’s needs with opportunities for assistive technologies. It searched 13 databases identifying 923 papers with 34 papers finally included for detailed analysis. The research papers identified needs in the fields of health, leisure, living, safety, communication, family relationship and social involvement. Amongst these, support for activities of daily living category was of most interest. In specific sub-categories, the next most reported need was assistive technology to support walking and mobility followed by smart cooking/kitchen technology and assistive technology for social contacts with family member/other people. The research aimed to inform a program of research into improving the adoption of technologies where they can ameliorate identified needs of older people.


title: Improving Access and Mental Health for Youth Through Virtual Models of Care

text: The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial.


title: Personalized and Contextualized Persuasion System for Older Adults’ Physical Activity Promoting

text: Aging often involves a significant change in roles and social positions. The greatest health risk for seniors is the adoption of a sedentary lifestyle that causes isolation, depression, and many diseases. However, convincing an older adult to regularly do physical activities is not generally a simple mission. This paper proposes a personalized and contextualized persuasion system to promote physical activities for older adults. In fact, our approach considers the personal and health profile of the older adult. It also considers different context parameters (context-awareness). This intelligence is guaranteed thanks to the use of the semantic modeling and reasoning, which from different types of information would be able to decide the best moment to trigger notifications from our persuasive system to the participating older adults.


title: Multirate ECG Processing and k-Nearest Neighbor Classifier Based Efficient Arrhythmia Diagnosis

text: The goal of this work is to make a contribution to the development of computationally efficient multirate Electrocardiogram (ECG) automated detectors of arrhythmia. It utilizes an intelligent combination of multirate denoising plus wavelet decomposition for an effective realization of the ECG wireless implants. The decomposed signal subband features are mined and in next step these are utilized by the mature k-Nearest Neighbor (KNN) classifier for arrhythmia diagnosis. The multirate nature substantially reduces the processing activity of the system and thus allows a dramatic decrease in energy consumption compared to traditional counterparts. The performance of the system is estimated also in terms of the classification performance. Obtained results reveal an overall 22.5-fold compression gain and 4-folds processing outperformance over the traditional equals while securing 93.2% highest classification accuracy and specificity of 0.956. Findings confirm that the proposed solution could potentially be embedded in contemporary automatic and mobile cardiac diseases diagnosis systems.


title: An Embedded ANN Raspberry PI for Inertial Sensor Based Human Activity Recognition

text: Human Activity Recognition (HAR) is one of the critical subjects of research in health and human machine interaction fields in recent years. Algorithms such as Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), Decision Tree (DT) and many other algorithms were previously implemented to serve this common goal but most of the traditional Machine learning proposed solutions were not satisfying in term of accuracy and real time testing process. For that, a human activities analysis and recognition system with an embedded trained ANN model on Raspberry PI for an online testing process is proposed in this work. This paper includes a comparative study between the Artificial Neural Network (ANN) and the Recurrent Neural Network (RNN), using signals produced by the accelerometer and gyroscope, embedded within the BlueNRG-Tile sensor. After evaluate algorithms performance in terms of accuracy and precision which reached an accuracy of 82% for ANN and 99% for RNN, obtained ANN model was implemented in a Raspberry PI for real-time predictions. Results show that the system provides a real-time human activity recognition with an accuracy of 86%.


title: Unsupervised Method Based on Superpixel Segmentation for Corpus Callosum Parcellation in MRI Scans

text: In this paper, we introduce an unsupervised method for the parcellation of the Corpus Callosum (CC) from MRI images. Since there are no visible landmarks within the structure that explicit its parcels, non-geometric CC parcellation is a challenging task especially that almost of proposed methods are geometric or data-based. In fact, in order to subdivide the CC from brain sagittal MRI scans, we adopt the probabilistic neural network as a clustering technique. Then, we use a cluster validity measure based on the maximum entropy (Vmep) to obtain the optimal number of classes. After that, we obtain the isolated CC that we parcel automatically using SLIC (Simple Linear Iterative Clustering) as superpixel segmentation technique. The obtained results on two challenging public datasets prove the performance of the proposed method against geometric methods from the state of the art. Indeed, as best as we know, it is the first work that investigates the validation of a CC parcellation method on ground-truth datasets using many objective metrics.


title: Comparative Study of Relevant Methods for MRI/X Brain Image Registration

text: Several methods of brain image registration have been proposed in order to overcome the requirement of clinicians. In this paper, we assess the performance of a hybrid method for brain image registration against the most used standard registration tools. Most traditional registration tools use different methods for mono- and multi-modal registration, whereas the hybrid registration method is providing both mono and multi-modal brain registration of PET, MRI and CT images. To determine the appropriate registration method, we used two challenging brain image datasets as well as two evaluation metrics. Results show that the hybrid method outperforms all other standard registration tools and has achieved promising accuracy for MRI/X brain image registration.


title: EEG-Based Hypo-vigilance Detection Using Convolutional Neural Network

text: Hypo-vigilance detection is becoming an important active research areas in the biomedical signal processing field. For this purpose, electroencephalogram (EEG) is one of the most common modalities in drowsiness and awakeness detection. In this context, we propose a new EEG classification method for detecting fatigue state. Our method makes use of a and awakeness detection. In this context, we propose a new EEG classification method for detecting fatigue state. Our method makes use of a Convolutional Neural Network (CNN) architecture. We define an experimental protocol using the Emotiv EPOC+ headset. After that, we evaluate our proposed method on a recorded and annotated dataset. The reported results demonstrate high detection accuracy (93%) and indicate that the proposed method is an efficient alternative for hypo-vigilance detection as compared with other methods.


title: Self-adaptative Early Warning Scoring System for Smart Hospital

text: With the advent of the Internet of Things (IoT), various interconnected objects can be used to improve the collection and the process of vital signs with partially or fully automatized methods in smart hospital environment. The vital signs data are used to evaluate patient health status using heuristic approaches, such as the early warning scoring (EWS) approach. Several applications have been proposed based on the early warning scores approach to improve the recognition of patients at risk of deterioration. However, there is a lack of efficient tools that enable a personalized monitoring depending on the patient situations. This paper explores the publish-subscribe pattern to provide a self-adaptative early warning score system in smart hospital context. We propose an adaptative configuration of the vital sings monitoring process depending on the patient health status variation and the medical staff decisions.


docid: ultdtcuh

title: Combined Machine Learning and Semantic Modelling for Situation Awareness and Healthcare Decision Support

text: The average of global life expectancy at birth was 72 years in 2016 [1], however, the global healthy life expectancy at birth was only 63.3 years in the same year, 2016 [2]. Living a long life is not any more as challenging as assuring active and associated life [25]. We propose in this paper an IoT based holistic remote health monitoring system for chronically ill and elderly patients. It supports smart clinical decision help and prediction. The patient heterogeneous vital signs and contexts gathered from wore and surrounding sensors are semantically simplified and modeled via a validated ontology composed by FOAF (Friend of a Friend), SSN (Semantic Sensors Network)/SOSA (Sensor, Observation, Sample and Actuator) and ICNP (International Classification Nursing Practices) ontologies. The reasoner engine is based on a scalable set of inference rules cohesively integrated with a ML (Machine Learning) algorithm to ensure predictive analytic and preventive personalized health services. Experimental results prove the efficiency of the proposed system.


title: Towards a Formal Context-Aware Workflow Model for Ambient Environment

text: Ambient systems owns some particular characteristics that makes their context awareness a sincere problem; they are composed of heterogeneous distributed devices, some of these devices may appear and disappear during operations. In addition, users interacting in these systems are themselves dynamic. Therefore, context-aware workflow management allows workflows to adapt dynamically according to the environment changes. Context information are complex and diverse which makes the modeling the key issue. This paper presents an approach to model context-aware workflows. First, we describe the workflow using Ag-LOTOS. Then, based on this description, we build the contextual planning system CPSw that allows the presentation of the context at each activity state.


title: Hybrid and Secure E-Health Data Sharing Architecture in Multi-Clouds Environment

text: Healthcare is among the sectors showing efforts in adopting cloud computing to its services considering the provided cost reduction and healthcare process efficiency. However, outsourcing patient’s sensitive data increases the concerns regarding security, privacy, and integrity of healthcare data. Therefore, there is a need for building a trust relationship between patients and e-health systems. In this paper, we propose a privacy-preserving framework, called Hybrid and Secure Data Sharing Architecture (HSDSA), to secure data storage in e-health systems. Our approach improves security in healthcare by maintaining the privacy and confidentiality of sensitive data and preventing threats. In fact, in the upload phase, Multi-cloud environment is used to store Rivest–Shamir–Adleman (RSA) encrypted medical records. We adopt a Shamir’s secret sharing approach for the distribution of shares to different independent cloud providers. In the retrieval phase, the reconstruction operation is based on the (t, n) strategy. To check the requester identity and to prove the hash possession, we used a zero-knowledge cryptography algorithm, namely the Schnorr algorithm. The patient has a total control over the generation and management of the decryption keys using Diffie-Hellman algorithm without relying on a trusted authority.


title: Ensuring the Correctness and Well Modeling of Intelligent Healthcare Management Systems

text: Recent research focus more and more on IoT systems and their applications in order to make people life easier and controllable. The main aim is to expand IoT applications and services into various domains while ensuring communication and automated exchange between them. Recent research handles many issues related to IoT especially implementation, modeling, and deployment. However, many challenges need more deep and thorough analysis especially in terms of flexible modeling, extensible implementation, with respect to the privacy issue. This work focuses principally on modeling IoT systems dedicated to smart healthcare case. We attempt to address the emergency service by initiating a modeling mechanism for Healthcare Management System (HMS) by using UML diagrams, and propose an appropriate access control in order to reinforce it. Then, we ensure the correctness of the developed HMS by relying on the verification and validation based on a formal analysis that showed significant results by using Alloy tool.


Special issue: 2018 Quebec elections


title: Aviation diplomacy: a conceptual framework for analyzing the relationship between aviation and international relations

text: The article aimed to conceptualize the term aviation diplomacy and to map the most typical forms of use of civil aviation for diplomatic reasons. The research included a review of approaches to aviation diplomacy and similar terms available in the scientific literature. The considerations presented in the article allowed for a proposition of tripartite framework for aviation diplomacy, with specific aspects referring either to the location of the diplomatic engagement or the actors engaged. The framework includes aviation as a foreign policy tool, aviation as a means of promoting the state’s international image, and aviation subjects as diplomatic actors.


Preventive Oral Health Services


title: Retrospective, multicenter study on the impact of baricitinib in COVID-19 moderate pneumonia

text: • Baricitinib, an anti-JAK1/JAK2, reduces cytokine release and SARS-Co-V2 entry; • In a retrospective multicenter study baricitinib reduces COVID-19 mortality rate; • Baricitinib reduces Intensive Care Unit admissions of COVID-19 pneumonia; • Baricitinb reduces SARS-CoV-2 viral burden detected by nasopharyngeal swab; • Baricitinib used for 2 weeks was not associated with serious adverse events.


Effects of neighborhood upgrading programs on domestic violence in Bolivia


A View from Arizona


Contrôles anti-dopage : trop, pas assez, autrement ?


Modern Approaches for Evaluation and Treatment of Gastrointestinal Motility Disorders


Opioid and Antibiotic Prescribing


docid: plzxntsy

title: Mitteilungen der Deutschen Gesellschaft für Neurologie


title: Uses of a Pandemic: Forging the Identities of Influenza and Virus Research in Interwar Britain

text: This paper counters the tendency to retrospectively viralise the 1918–19 pandemic and to gloss the important historiographical point that, in Britain, such knowledge was in-the-making between 1918 and 1933. It traces the genesis of influenza's virus identity to British efforts in 1918–19 to specify the cause of the pandemic and it examines how, in the 1920s, the British Medical Research Council used the connection between a virus and the pandemic to justify the development of virus research and to make influenza a core problem around which it was organised. It shows that the organisation of medical virus research was inextricably linked to the pandemic before the actual discovery of flu virus in 1933. Recognising that the relationship between the virus and the disease itself has a history demands we rethink the pandemic's medical scientific legacy and the crucial role of virus research in shaping its history.


title: Adaptive Targeted Infectious Disease Testing

text: We show how to efficiently use costly testing resources in an epidemic, when testing outcomes can be used to make quarantine decisions. If the costs of false quarantine and false release exceed the cost of testing, the optimal myopic testing policy targets individuals with an intermediate likelihood of being infected. A high cost of false release means that testing is optimal for individuals with a low probability of infection, and a high cost of false quarantine means that testing is optimal for individuals with a high probability of infection. If individuals arrive over time, the policy-maker faces a dynamic trade-off: using tests for individuals for whom testing yields the maximum immediate benefit vs spreading out testing capacity across the population to learn prevalence rates thereby benefiting later individuals. We describe a simple policy that is nearly optimal from a dynamic perspective. We briefly discuss practical aspects of implementing our proposed policy, including imperfect testing technology, appropriate choice of prior, and non-stationarity of the prevalence rate.


title: The Influenza Epidemic of 1918 and the Adivasis of Western India

text: The influenza epidemic of 1918 was the single worst outbreak of this disease known in history. This article examines an area of western India that was affected very badly—that of a tract inhabited by impoverished indigenous peoples, who are known in India as adivasis. The reasons for this are discussed. Some oral accounts help to bring out the enduring memory of that terrible time. The general health of the adivasis and the existing medical facilities in this area are examined. Attempts to check and treat the disease by the colonial government and its doctors, as well as missionary doctors and other non-governmental agencies, are considered to see why they had so little overall impact. Some comparisons are made with the fate of indigenous people in other parts of the world during the epidemic, in particular with the Inuits of Alaska.


title: Sensitivity Assessment of Rapid Influenza Diagnostic Tests for the Detection of the 2009 Pandemic Influenza A (H1N1) Virus in Clinical Specimens

text: BACKGROUND: Influenza antigen detection test kits can provide results in 30 minutes and are used frequently for the detection of seasonal influenza infections. It is very important to determine the efficacy of these tests in the diagnosis of the 2009 pandemic influenza A (H1N1) virus due to the global spread of this new influenza virus. METHODS: We evaluated 4 rapid influenza diagnostic tests (Binax Now Influenza A&B, BD Directigen EZ Flu A+B, Fujirebio Espline Influenza A&B-N, and BioTracer Influenza A&B Test) for their ability to detect the 2009 pandemic influenza A (H1N1) virus and compared these results with the diagnostic sensitivity obtained following real-time polymerase chain reaction (PCR) analysis of the same samples. RESULTS: Reverse transcriptase polymerase chain reaction (RT-PCR) analysis of 252 specimens identified 176 influenza A (H1N1) positive samples. Of these, between 29 and 62 also tested positive using the 4 rapid tests examined, demonstrating the sensitivity of the respective tests was 16.5%–35.2% with specificities of 100%. However, the 4 rapid tests were 77.3%–100% sensitive when samples contained high influenza A (H1N1) virus titers, suggesting the sensitivity of these detection kits was dependent on viral loads. Finally, the sensitivity of the 4 detection kits tested was higher when samples from children were examined compared with samples from adults. CONCLUSIONS: Data presented in this report indicated the sensitivity of the respective influenza antigen detection test kits examined was low compared to the sensitivity observed following RT-PCR. Nonetheless, they are useful tools during early outbreak investigations of influenza-like illnesses, particularly in the screening of critically ill patients and pediatric patients. However, negative results could be confirmed using other tests (eg, RT-PCR if necessary).


title: Understanding Autonomy: An Urgent Intervention

text: In this paper, I argue that the principle of respect for autonomy can serve as the basis for laws that significantly limit conduct, including orders mandating isolation and quarantine. This thesis is fundamentally at odds with an overwhelming consensus in contemporary bioethics that the principle of respect for autonomy, while important in everyday clinical encounters, must be “curtailed,” “constrained,” or “overridden” by other principles in times of crisis. I contend that bioethicists have embraced an indefensibly “thin” notion of autonomy that uproots the concept from its foundations in Kantian ethics. According to this thin conception, respect for autonomy, if unconditioned by competing principles (beneficence, justice, non-maleficence) would give competent adults the right to do anything they desired to do so long as they satisfied certain baseline psychological conditions. I argue that the dominant “principlist” model of bioethical reasoning depends on this thin view of autonomy and show how it deprives us of powerful analytical tools that would help us to think seriously about the foundations of human rights, justice, and law. Then, I offer a brief sketch of a “thick,” historically-grounded notion of autonomy and show what we could gain by taking it seriously.


title: COVID-19 and Reproductive Justice in Great Britain and the United States: Ensuring Access to Abortion Care during a Global Pandemic

text: In this paper we consider the impact that the COVID-19 pandemic is having on access to abortion care in Great Britain (England, Wales, and Scotland) and the United States. The pandemic has exacerbated problems in access to abortion services because social distancing or lockdown measures, increasing caring responsibilities, and the need to self-isolate are making clinics much more difficult to access; and this is when clinics are able to stay open which many are not. In response we argue there is a need to facilitate telemedical early medical abortion in order to ensure access to essential healthcare for people in need of terminations. There are substantial legal barriers to the establishment of telemedical abortion services in parts of Great Britain and parts of the United States. We argue that during a pandemic any restriction on telemedicine for basic healthcare is an unjustifiable human rights violation and, in the United States, is unconstitutional.


American Pandemic: The Lost Worlds of the 1918 Influenza Epidemic


Editorial: COVID-19 and I•CON; Guest Editorial: Courts’ relations; Once upon a time in Catalonia ...; In this issue


Endocytic uptake of SARS-CoV-2: the critical roles of pH, Ca(2+) and NAADP


title: Case report of anterior ST-elevation myocardial infarction in a patient with coronavirus disease-2019

text: BACKGROUND: Coronavirus disease-2019 (COVID-19) is an infectious disease appeared in China in December 2019 and, since then, has spread worldwide at a rapid pace. CASE SUMMARY: A patient with COVID-19 was hospitalized in our institution for a diabetic foot ulcer and presented afterwards a pulmonary oedema and concomitant anterior ST-segment elevation myocardial infarction. We report here on the initial presentation, coronary care and intervention, and clinical course of this patient. DISCUSSION: Emergent percutaneous coronary intervention is feasible and safe in COVID-19 patients but requires a multidisciplinary effort involving caregivers from infectious disease, intensive care, and cardiology teams.


docid: mfszypvg

title: Sustainability of ASEAN integration, competition policy, and the challenges of COVID-19


Arztgruppenübergreifende bei spezifischen Voraussetzungen berechnungsfähige Gebührenordnungspositionen


title: The Effects of Early Mobilization on Patients Requiring Extended Mechanical Ventilation Across Multiple ICUs

text: OBJECTIVES: 1) To successfully implement early mobilization of individuals with prolonged mechanical ventilation in multiple ICUs at a tertiary care hospital and 2) to reduce length of stay and improve quality of care to individuals in the ICUs. DESIGN: Comparative effectiveness cohort study based on a quality improvement project. SETTING: Five ICUs at a tertiary care hospital. PATIENTS: A total of 541 mechanically ventilated patients over a 2-year period (2014–2015): 280 and 261, respectively. Age ranged from 19 to 94 years (mean, 63.84; sd, 14.96). INTERVENTIONS: A hospital-based initiative spurred development of a multidisciplinary team, tasked with establishing early mobilization in ICUs. MEASUREMENTS AND MAIN RESULTS: Early mobilization in the ICUs was evaluated by the number of physical therapy consults, length of stay, individual treatment sessions utilizing functional outcomes, and follow-up visits. Implementation of an early mobilization protocol across all ICUs led to a significant increase in the number of physical therapy consults, a significant decrease in ICU and overall lengths of stay, significantly shorter days to implement physical therapy, and a significantly higher physical therapy follow-up rate. CONCLUSIONS: Mobilizing individuals in an intensive care setting decreases length of stay and hospital costs. With an interdisciplinary team to plan, implement, and evaluate stages of the program, a successful early mobilization program can be implemented across all ICUs simultaneously and affect change in patients who will require prolonged mechanical ventilation.


title: Improving the Intensive Care Patient Experience With Virtual Reality—A Feasibility Study

text: OBJECTIVES: Patients’ stays in the ICU are often characterized by prolonged immobility, sedation, disrupted sleep, and extended periods of pain, which put ICU patients at greater risk for ICU-acquired weakness and delirium-related mortality. The aim of this study was to evaluate the feasibility and efficacy of using meditative virtual reality to improve the hospital experience of ICU patients. DESIGN: Final report of prospective observational trial. SETTING: Surgical and trauma ICUs of the University of Florida Health, an academic hospital. PATIENTS: Fifty-nine nonintubated adult ICU patients without delirium at recruitment. INTERVENTIONS: Patients were exposed to sessions of commercially available meditative virtual reality applications focused on calmness and relaxation, performed once daily for up to 7 days. MEASUREMENTS AND MAIN RESULTS: Outcome measures included pain level, pain medication administration, anxiety, depression, sleep quality, heart rate, respiratory rate, blood pressure, delirium status, and patient ratings of the virtual reality system. Comparisons were made using paired t tests and mixed models. The virtual reality meditative intervention improved patients’ ICU experience with reduced levels of anxiety and depression; however, there was no evidence that virtual reality had significant effects on physiologic measures, pain, or sleep. CONCLUSIONS: The use of meditative virtual reality technology in the ICU was easily implemented and well-received by patients.


title: Consequences and Solutions for the Impact of Communication Impairment on Noninvasive Ventilation Therapy for Acute Respiratory Failure: A Focused Review

text: OBJECTIVES: With over 2 million cases of acute respiratory failure in the United States per year, noninvasive ventilation has become a leading treatment modality, often supplanting invasive mechanical ventilation as the initial treatment of choice. Most acute respiratory failure patients use a full face (oronasal) mask with noninvasive ventilation, which is known to impair communication, but its popularity and benefit has led many providers to accept the communication impairment. Medical staff periodically remove masks to communicate with patients, but patients are often limited to short utterances and risk lung derecruitment upon removal of positive pressure. These problems can lead to noninvasive ventilation failure, which is often linked to worse outcomes than first initiating invasive mechanical ventilation and can lead to increased hospitalization costs. DATA SOURCES: We searched MEDLINE and Google Scholar for “speech,” “communication,” “impairment,” “failure,” “complications,” “NIPPV,” “NIV,” and “noninvasive ventilation.” STUDY SELECTION: We included articles with patients in acute respiratory failure. We excluded articles for patients using noninvasive ventilation therapy for obstructive sleep apnea. DATA SYNTHESIS: Communication impairment has been associated with increasing noninvasive ventilation anxiety (odds ratio, 1.25). Of patients using noninvasive ventilation, 48% require early discontinuation, 22% refuse noninvasive ventilation, and 9% are ultimately intubated. Improvements to communication have been shown to reduce fear and anxiety in invasive mechanical ventilation patients. Analogous communication problems exist with effective solutions in other fields, such as fighter pilot masks, that can be easily implemented to enhance noninvasive ventilation patient care, increase adherence to noninvasive ventilation treatment, and improve patient outcomes. CONCLUSIONS: Communication impairment is an underappreciated cause of noninvasive ventilation complications and failure and requires further characterization. Analogous solutions—such as throat microphones and mask-based microphones—that can be easily implemented show potential as cost-effective methods to reduce noninvasive ventilation failure.


title: Walking While Dialyzing: A Retrospective Observation of Early Mobility and Ambulation for Patients on Continuous Renal Replacement Therapy

text: OBJECTIVES: To describe the practice of physical therapy for patients requiring continuous renal replacement therapy and assess data related to the safety and feasibility of physical therapy interventions. DESIGN: A retrospective observational cohort study. PATIENTS: Surgical and cardiovascular patients receiving continuous renal replacement therapy during a 2-year period from December 2016 to November 2018. SETTING: Two ICUs at a single academic medical center. INTERVENTION: Physical mobility and ambulation while on continuous renal replacement therapy. MEASUREMENTS AND MAIN RESULTS: Therapy data including ICU Mobility Scale score, number of physical therapy sessions with and without ambulation and gait distance, along with safety data including filter life, safety events, and mortality were analyzed. The cohort of patients receiving continuous renal replacement therapy during the 2-year period was 206. Of these, 172 (83.49%) received simultaneous physical therapy. The median ICU Mobility Scale was 5 (interquartile range, 4–7) over a total of 1,517 physical therapy sessions. Ambulation with concomitant continuous renal replacement therapy connected was achieved in 78 patients (37.86%). There were 377 ambulation sessions (24.85% of all sessions) with a mean of 4.83 (sds 4.94) ambulation sessions per ambulatory patient. Patients walked an average of 888.53 feet (sd 1,365.50) while on continuous renal replacement therapy and a daily average of 150.61 feet (sd 133.50). In-hospital mortality was lowest for patients who ambulated (17.95%) and highest for patients who received no therapy (73.53%). Continuous renal replacement therapy filter life was longest for patients who ambulated (2,047.20 min [sd 1,086.50 min]), and shortest in patients who received no therapy (1,682.20 min [sd 1,343.80 min]). One safety event was reported during this time (0.0007% of all physical therapy sessions). CONCLUSIONS: Ambulation while on continuous renal replacement therapy was not associated with an increased risk of safety events and was feasible with the use of nonfemoral catheters and dialysis equipment with internal batteries.


title: International Survey of Thrombolytic Use for Treatment of Cardiac Arrest Due to Massive Pulmonary Embolism

text: OBJECTIVES: This survey sought to characterize the national prescribing patterns and barriers to the use of thrombolytic agents in the treatment of pulmonary embolism, with a specific focus on treatment during actual or imminent cardiac arrest. DESIGN: A 19-question international, cross-sectional survey on thrombolytic use in pulmonary embolism was developed, validated, and administered. A multivariable logistic regression was conducted to determine factors predictive of utilization of thrombolytics in the setting of cardiac arrest secondary to pulmonary embolism. SETTING: International survey study. SUBJECTS: Physicians, pharmacists, nurses, and other healthcare professionals who were members of the Society of Critical Care Medicine. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Thrombolytic users were compared with nonusers. Respondents (n = 272) predominately were physicians (62.1%) or pharmacists (30.5%) practicing in an academic medical center (54.8%) or community teaching setting (24.6%). Thrombolytic users (n = 177; 66.8%) were compared with nonusers (n = 88; 33.2%) Thrombolytic users were more likely to work in pulmonary/critical care (80.2% thrombolytic use vs 59.8%; p < 0.01) and emergency medicine (6.8% vs 3.5%; p < 0.01). Users were more likely to have an institutional guideline or policy in place pertaining to the use of thrombolytics in cardiac arrest (27.8% vs 13.6%; p < 0.01) or have a pulmonary embolism response team (38.6% vs 19.3%; p < 0.01). Lack of evidence supporting use and the risk of adverse outcomes were barriers to thrombolytic use. Working in a pulmonary/critical care environment (odds ratio, 2.36; 95% CI, 1.24–4.52) and comfort level (odds ratio, 2.77; 95% CI, 1.7–4.53) were predictive of thrombolytic use in the multivariable analysis. CONCLUSIONS: Most survey respondents used thrombolytics in the setting of cardiac arrest secondary to known or suspected pulmonary embolism. This survey study adds important data to the literature surrounding thrombolytics for pulmonary embolism as it describes thrombolytic user characteristic, barriers to use, and common prescribing practices internationally.


title: Long-Term Cognitive Impairment Associated With Delirium in Acute Neurological Injury

text: OBJECTIVES: To characterize the risk of long-term cognitive impairment associated with delirium in acute neurologic injury patients. DESIGN: We analyzed a 10-year cohort of adult acute neurologic injury patients (stroke and traumatic brain injury) without preexisting mild cognitive impairment or dementia, utilizing administrative databases. Patients were followed for in-hospital delirium and mild cognitive impairment or dementia. We report incidence and adjusted hazard ratios for mild cognitive impairment or dementia associated with delirium. Subgroups analyzed include acute neurologic injury categories, dementia subtypes, repeated delirium exposure, and age strata. SETTING: We used state emergency department and state inpatient databases for New York, Florida, and California. All visits are included in the databases regardless of payer status. PATIENTS: We included adult patients with diagnosis of stroke and traumatic brain injury as acute neurologic injury. Patients with preexisting mild cognitive impairment or dementia were excluded. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among 911,380 acute neurologic injury patients, 5.2% were diagnosed with delirium. Mild cognitive impairment or dementia incidence among delirium patients was approximately twice that of nondelirium patients. In adjusted models, risk of mild cognitive impairment or dementia was higher among patients with delirium (adjusted hazard ratio, 1.58). Increased risk was observed across all subgroups including patients less than or equal to 55 years old. CONCLUSIONS: Identification, management, and prevention of in-hospital delirium could potentially improve long-term cognitive outcomes in acute neurologic injury patients.


title: Patient and Care Delivery Characteristics Associated With Harm From Neuromuscular Blockade

text: OBJECTIVES: To identify the prevalence of and evaluate factors associated with down-titration of sedation in patients receiving neuromuscular blockade. DESIGN: Retrospective cohort study. SETTING: Tertiary care teaching hospital in Boston, MA. PATIENTS: All patients over 18 years old admitted to the medical, surgical, or cardiac ICUs from 2013 to 2016, and who received cisatracurium for at least 24 hours. INTERVENTIONS: We examined patients for whom sedation was decreased despite accompanying ongoing neuromuscular blockade administration. MEASUREMENTS AND MAIN RESULTS: Of the 300 patients who met inclusion criteria (39% female, mean age of 57 yr old), 168 (56%) had sedation down-titrated while receiving neuromuscular blockade with a mean decrease in sedation dose of 18.7%. Factors associated with down-titration of sedation were bispectral index usage (90/168 [53.6%] vs 50/168 [29.8%] patients; p < 0.01; odds ratio, 1.82; 1.12–2.94), and bolus dose of neuromuscular blockade prior to continuous infusion (138/168 [82.1%] vs 79/168 [47.0%] patients; p < 0.0001). CONCLUSIONS: Down-titration of sedation among mechanically ventilated patients receiving neuromuscular blockade was common and was correlated with bispectral index monitor usage. Clinicians should be aware of the limitations of quantitative electroencephalography monitoring devices and recognize their potential to cause inappropriate down-titration of sedation. Substantial opportunity exists to improve the quality of care of patients receiving neuromuscular blockade through development of guidelines and standardized care pathways.