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.


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.


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.


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.


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


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.


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.


title: Inflammation Profiling of Critically Ill Coronavirus Disease 2019 Patients

text: OBJECTIVES: Coronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019. DESIGN: Daily blood inflammation profiling with immunoassays. SETTING: Tertiary care ICU and academic laboratory. SUBJECTS: All patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Age- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1–3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2–7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality. CONCLUSIONS: While many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.


title: The Epidemiology of Respiratory Failure in the United States 2002–2017: A Serial Cross-Sectional Study

text: OBJECTIVES: Respiratory failure with mechanical ventilation is a limited labor-intensive resource that is associated with high mortality. Understanding the longitudinal national epidemiology is essential for the organization of healthcare resources. DESIGN: Serial cross-sectional study. SETTING: The 2002–2017 Healthcare Utilization Project’s National Inpatient Sample datasets. INTERVENTIONS: None. MEASUREMENTS: We use six diagnosis codes and five procedural codes from International Classification of Diseases, 9th Revision, Clinical Modification, and 19 diagnosis codes and 15 procedures codes from International Classification of Diseases, 10th Revision, Clinical Modification to examine national epidemiology of different case definitions for respiratory failure. RESULTS: In the United States in 2017, there were an estimated 1,146,195 discharges with a diagnosis of respiratory failure and procedural code for mechanical ventilation, with an average length of stay of 10.5 days and hospital charge of $158,443. Over the study period, there was an 83% increase in incidence from 249 to 455 cases per 100,000 adults with a 48% decrease in hospital mortality from 34% to 23%. Exploring a case definition that captures only diagnosis codes for respiratory failure, there was a 197% increase in annual incidence, from 429 to 1,275 cases per 100,000 adults with a 57% decrease in hospital mortality from 28% to 12%. For invasive mechanical ventilation without a requisite diagnosis code, there was no change in incidence over the study period, with the 2017 incidence at 359 cases per 100,000 adults, but a 19% decrease in hospital mortality from 37% to 30%. For the noninvasive mechanical ventilation procedural codes, there was a 437% increase in incidence from 41 to 220 cases per 100,000 adults, with a 38% decrease in hospital mortality from 16% to 10%. CONCLUSIONS: Examining different case definitions for respiratory failure, there was a large increase in the population incidence and decrease in the hospital mortality for respiratory failure diagnosis codes with more modest changes procedural codes for invasive mechanical ventilation. There was a large increase in incidence of noninvasive mechanical ventilation.


Cardiovascular and cardiometabolic prevention: high-level priority in the era of COVID-19


title: Impact of Fiber-Based Enteral Nutrition on the Gut Microbiome of ICU Patients Receiving Broad-Spectrum Antibiotics: A Randomized Pilot Trial

text: OBJECTIVES: Dietary fiber increases the abundance of bacteria that metabolize fiber into short-chain fatty acids and confers resistance against gut colonization with multidrug-resistant bacteria. This pilot trial estimated the effect of fiber on gut short-chain fatty acid–producing bacteria in the ICU. DESIGN: Randomized, controlled, open label trial. SETTING: Medical ICU. PATIENTS: Twenty ICU adults receiving broad-spectrum IV antibiotics for sepsis. INTERVENTION: 1:1 randomization to enteral nutrition with mixed soy- and oat-derived fiber (14.3 g fiber/L) versus calorie- and micronutrient-identical enteral nutrition with 0 g/L fiber. MEASUREMENTS: Rectal swabs and whole stools were collected at baseline and on study Days 3, 7, 14, and 30. The primary outcome was within-individual change in the cumulative relative abundance of short-chain fatty acid–producing taxa from baseline to Day 3 based on 16S sequencing of rectal swabs. The secondary outcome was Day 3 cumulative short-chain fatty acid levels based on mass spectrometry of whole stools. Analyses were all intent to treat. MAIN RESULTS: By Day 3, the fiber group received a median of 32.1 g fiber cumulatively (interquartile range, 17.6–54.6) versus 0 g fiber (interquartile range, 0–4.0) in the no fiber group. The median within-individual change in short-chain fatty acid producer relative abundance from baseline to Day 3 was +61% (interquartile range −51 to +1,688) in the fiber group versus −46% (interquartile range, −78 to +13) in the no fiber group (p = 0.28). Whole stool short-chain fatty acid levels on Day 3 were a median of 707 μg short-chain fatty acids/g stool (interquartile range, 190–7,265) in the fiber group versus 118 μg short-chain fatty acids/g stool (interquartile range, 22–1,195) in the no fiber group (p = 0.16). CONCLUSIONS: Enteral fiber was associated with nonsignificant trends toward increased relative abundance of short-chain fatty acid–producing bacteria and increased short-chain fatty acid levels among ICU patients receiving broad-spectrum IV antibiotics. Larger studies should be undertaken and our results can be used for effect size estimates.


title: Framework and Outcomes of a Critical Care Pharmacy Visiting Clinical Professor Program

text: OBJECTIVES: Experiences with utilizing a visiting clinical professor program to mentor institutions and collaborate on best practices in critical care pharmacy are described to provide a framework for these services and a synopsis of key outcomes. DESIGN: The Society of Critical Care Medicine Clinical Pharmacy and Pharmacology Section implemented a visiting clinical professor program to address the need for collaboration, idea-sharing, mentorship, and diffusion of innovation to clinicians in critical care practice. SETTING: Critical care pharmacy departments at 12 medical centers. SUBJECTS: Twelve visiting clinical professors and host institutions from 2007-2018. INTERVENTION: After an application is submitted to the section steering committee, an experienced clinician is paired with an institution, and a site visit is planned in collaboration with the visiting clinical professor program coordinators. The expert clinician visits the institution to share their insights and best practices based on visit goals and objectives. Reflective debriefing with both the host institution and the visiting clinical professor occurs after the visit. MEASUREMENTS AND MAIN RESULTS: The program has demonstrated numerous benefits including shared best practices related to critical care clinical services, expansion and refinement of care delivery models, development and optimization of research programs, and advancement of new training programs including specialty pharmacy residencies. Both the site and visiting professor find these partnerships beneficial, which has resulted in sustained success of the program over an 11-year period. Key resultant deliverables after visits have included new pharmacist positions, advancement of pharmacy services, and expanded access to academic opportunities. CONCLUSIONS: A professional organization led visiting clinical professor program is viable, sustainable, and yields clear benefit for critical care pharmacy programs across the country. Application of this framework to other areas of pharmacy practice may be an avenue to share best practices and advance pharmacy services.


title: Gender Difference Is Associated With Severity of Coronavirus Disease 2019 Infection: An Insight From a Meta-Analysis

text: OBJECTIVES: Coronavirus disease 2019 is a novel infection now causing pandemic around the world. The gender difference in regards to the severity of coronavirus disease 2019 infection has not been well described thus far. Our aim was to investigate how gender difference can affect the disease severity of coronavirus disease 2019 infection. DATA SOURCES: A comprehensive literature search of PubMed and Embase databases was conducted from December 1, 2019, to March 26, 2020. An additional manual search of secondary sources was conducted to minimize missing relevant studies. There were no language restrictions. STUDY SELECTION: Studies were included in our meta-analysis if it was published in peer-reviewed journals and recorded patient characteristics of severe versus nonsevere or survivor versus nonsurvivor in coronavirus disease 2019 infection. DATA EXTRACTION: Two investigators independently screened the search, extracted the data, and assessed the quality of the study. DATA SYNTHESIS: Our search identified 15 observational studies with a total of 3,494 patients (1,935 males and 1,559 females) to be included in our meta-analysis. Males were more likely to develop severe coronavirus disease 2019 infection compared with females (odds ratio, 1.31; 95% CI, 1.07–1.60). There was no significant heterogeneity (I(2) = 12%) among the studies. CONCLUSIONS: This meta-analysis suggests that the male gender may be a predictor of more severe coronavirus disease 2019 infection. Further accumulation of evidence from around the world is warranted to confirm our findings.


title: Pediatric Sepsis Definition—A Systematic Review Protocol by the Pediatric Sepsis Definition Taskforce

text: OBJECTIVES: Sepsis is responsible for a substantial proportion of global childhood morbidity and mortality. However, evidence demonstrates major inaccuracies in the use of the term “sepsis” in clinical practice, coding, and research. Current and previous definitions of sepsis have been developed using expert consensus but the specific criteria used to identify children with sepsis have not been rigorously evaluated. Therefore, as part of the Society of Critical Care Medicine’s Pediatric Sepsis Definition Taskforce, we will conduct a systematic review to synthesize evidence on individual factors, clinical criteria, or illness severity scores that may be used to identify children with infection who have or are at high risk of developing sepsis-associated organ dysfunction and separately those factors, criteria, and scores that may be used to identify children with sepsis who are at high risk of progressing to multiple organ dysfunction or death. DATA SOURCES: We will identify eligible studies by searching the following databases: MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. STUDY SELECTION: We will include all randomized trials and cohort studies published between January 1, 2004, and March 16, 2020. DATA EXTRACTION: Data extraction will include information related to study characteristics, population characteristics, clinical criteria, and outcomes. DATA SYNTHESIS: We will calculate sensitivity and specificity of each criterion for predicting sepsis and conduct a meta-analysis if the data allow. We will also provide pooled estimates of overall hospital mortality. CONCLUSIONS: The potential risk factors, clinical criteria, and illness severity scores from this review which identify patients with infection who are at high risk of developing sepsis-associated organ dysfunction and/or progressing to multiple organ dysfunction or death will be used to inform the next steps of the Pediatric Sepsis Definition Taskforce.


title: Obese communities among the best predictors of COVID-19-related deaths

text: INTRODUCTION: Coronavirus disease 2019 (COVID-19) is the largest outbreak to strike the world since the Spanish flu in 1918. Visual examination of the world map shows a wide variation of death tolls between countries. The main goal of our series is to determine the best predictors of such discrepancy. METHODS: This is a retrospective study in which the rate of COVID-19 deaths was correlated with each of the following independent variables: total tests per 1 million population, gross domestic product (GDP), average temperatures per country, ultraviolet index, median age, average BMI per country, food supply, Bacille Calmette-Guerin compulsory status, and passenger traffic. RESULTS: BMI per country proved to be the second best predictor of death rate with an R value of 0.43, and GDP being the best predictor with R = 0.65. CONCLUSION: This article shows a tight correlation between average BMI, food supply per country, and COVID-19-related deaths. Such predisposing factors might operate by upregulating the inflammation pathway in heavily struck countries, leading to easier triggering of the infamous cytokine storm syndrome. Obesity also increases cardiovascular and respiratory morbidities, which are coupled to increased ICU demand and deaths among infected cases. Video abstract: http://links.lww.com/CAEN/A25.


title: The Efficacy of Albumin Dialysis in the Reversal of Refractory Vasoplegic Shock Due to Amlodipine Toxicity

text: OBJECTIVES: Calcium channel blockers are highly protein-bound medications frequently used in the management of hypertension. Overdose results in severe hypotension and is the fourth most common cause of toxicity-related deaths in the United States. Management is mostly supportive, with currently no standard role for targeted drug removal. The protein-bound nature of these medications presents the option of utilizing albumin dialysis for their removal and for the reversal of associated shock. DESIGN AND SUBJECTS: We present two cases of life-threatening intentional amlodipine overdoses successfully treated with albumin dialysis. Both patients experienced profound distributive shock in the setting of preserved cardiac contractility that was refractory to maximal vasoactive agent support. INTERVENTIONS AND RESULTS: After initiation of albumin dialysis, the patients showed rapid hemodynamic improvement and were able to be weaned off vasopressor support. CONCLUSIONS: These cases demonstrate the safety and efficacy of albumin dialysis in the management of near-fatal calcium channel blocker overdoses related to amlodipine and offer an additional therapeutic option apart from conventional supportive care. Importantly, these cases were not associated with impaired cardiac contractility, thereby making venoarterial extracorporeal membrane oxygenation a less preferable option. Furthermore, this therapeutic benefit of albumin dialysis can potentially be extended to the management of toxicity related to other highly protein-bound drugs and toxins.


title: Recombinant Human Proteoglycan-4 Mediates Interleukin-6 Response in Both Human and Mouse Endothelial Cells Induced Into a Sepsis Phenotype

text: OBJECTIVES: Sepsis is a leading cause of death in the United States. Putative targets to prevent systemic inflammatory response syndrome include antagonism of toll-like receptors 2 and 4 and CD44 receptors in vascular endothelial cells. Proteoglycan-4 is a mucinous glycoprotein that interacts with CD44 and toll-like receptor 4 resulting in a blockade of the NOD-like receptor pyrin domain-containing-3 pathway. We hypothesized that endothelial cells induced into a sepsis phenotype would have less interleukin-6 expression after recombinant human proteoglycan 4 treatment in vitro. DESIGN: Enzyme-linked immunosorbent assay and reverse transcriptase-quantitative polymerase chain reaction to measure interleukin-6 protein and gene expression. SETTING: Research laboratory. SUBJECTS: Human umbilical vascular endothelial cells, human lung microvascular endothelial cells, and transgenic mouse (wild type) (Cd44(+/+)/Prg4(+/+)), Cd44(–/–) (Cd44(tm1Hbg)Prg4(+/+)), Prg4(GT/GT) (Cd44(+/+) Prg4(tm2Mawa/J)), and double knockout (Cd44(tm1Hbg) Prg4(tm2Mawa/J)) lung microvascular endothelial cells. INTERVENTIONS: Cells were treated with 100 or 250 ng/mL lipopolysaccharide-Escherichia coli K12 and subsequently treated with recombinant human proteoglycan 4 after 30 minutes. Interleukin-6 levels in conditioned media were measured via enzyme-linked immunosorbent assay and gene expression was measured via reverse transcriptase-quantitative polymerase chain reaction with ΔΔ–Ct analysis. Additionally, human umbilical vascular endothelial cells and human lung microvascular endothelial cells were treated with 1:10 diluted plasma from 15 patients with sepsis in culture media. After 30 minutes, either 50 or 100 µg/mL recombinant human proteoglycan 4 was administered. Interleukin-6 protein and gene expression were assayed. Proteoglycan 4 levels were also compared between control and sepsis patient plasma. MEASUREMENTS AND MAIN RESULTS: Human umbilical vascular endothelial cell, human lung microvascular endothelial cell, and mouse lung microvascular endothelial cell treated with lipopolysaccharide had significantly increased interleukin-6 protein compared with controls. Recombinant human proteoglycan-4 significantly reduced interleukin-6 in human and mouse endothelial cells. Interleukin-6 gene expression was significantly increased after lipopolysaccharide treatment compared with controls. This response was reversed by 50 or 100 µg/mL recombinant human proteoglycan-4 in 80% of sepsis samples in human umbilical vascular endothelial cells and in 60–73% in human lung microvascular endothelial cells. In Cd44(–/–) genotypes of the mouse lung microvascular endothelial cells, recombinant human proteoglycan-4 significantly reduced interleukin-6 protein levels after lipopolysaccharide treatment, indicating that Cd44 is not needed for recombinant human proteoglycan-4 to have an effect in a toll-like receptor 4 agonist inflammation model. Patient sepsis samples had higher plasma levels of native proteoglycan-4 than controls. INTERPRETATION AND CONCLUSIONS: Recombinant human proteoglycan-4 is a potential adjunct therapy for sepsis patients and warrants future in vivo model studies.


title: Mechanical Ventilation, Sedation and Neuromonitoring of Patients with Aneurysmal Subarachnoid Hemorrhage in Germany: Results of a Nationwide Survey

text: OBJECTIVE: Current evidence-based guidelines for the management of aneurysmal subarachnoid hemorrhage (aSAH) focus primarily on timing, modality and technique of aneurysm occlusion, and on prevention and treatment of delayed cerebral ischemia. Significant aspects of management in the intensive care unit (ICU) during the later course of aSAH such as ventilation and sedation (VST) remain unaddressed. aSAH patients present unique challenges not accounted for in general ICU recommendations and guidelines, which is why we attempted to further characterize ICU practices in aSAH patients in Germany. METHODS: We conducted a nationwide survey on ICU practices in aSAH in Germany. Secondarily, we assessed the existence of and compliance with current guidelines regarding ICU practices. The questionnaire was designed in interdisciplinary fashion and distributed online through the kwiksurvey(®) platform (Bristol, UK). RESULTS: A total of 50 responses were received, accounting for a response rate of 49%. Twenty-one were university hospitals (UH), 23 high-volume centers (HVC), 6 low-volume centers (LVC). Half of the participating centers do not take into consideration WFNS at presentation to indicate ventilation. While 42% of centers rely on the P/F ratio to indicate ventilation, 62% of them have a cutoff value of < 200, and 38% of < 100. While most UH and HVC used propofol for the first phase of sedation (95%), LVC employed benzodiazepines (100%). Sedation deepening was done with ketamine in UH (75%) and HVC (60%), whereas LVC used predominantly clonidine (100%). CONCLUSIONS: Our study clearly demonstrates that attitudes and practices pertaining to ICU management in aSAH are enormously heterogeneous, reflecting the lack of good quality evidence and differing interpretations thereof. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s12028-020-01029-8) contains supplementary material, which is available to authorized users.


Anita Zaidi


Jacques Acar


The clinical relevance of the clinical cytological grading in patients with chronic rhinosinusitis with nasal polyps


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Editor’s note: “family business scholars, lead the charge!”


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JCF Year in Review


title: The pattern of neonatal gastro-intestinal perforation in upper Egypt

text: BACKGROUND: Neonatal gastro-intestinal perforation [NGIP] is one of the major problems in pediatric surgical practice. Although the outcomes of neonatal surgery have improved markedly over the past decade the mortality rates of neonates with NGIP are still high. The aim of this study was to present the possible etiological factors, clinical findings, and operative procedures of NIP in our locality. RESULTS: A total of 34 neonates with NGIP were included in this study. The median age at presentation was (15.8 ± 7.0 SD) days. The median interval between presentation and surgical interference was (2.0 ± 1.1 SD).Necrotizing enterocolitis [NEC] was the commonest cause of neonatal gastro-intestinal perforation. The commonest site of perforation was the colon [11cases]. The overall mortality rate was 11 cases [32.4%]. The main cause of mortality was neonatal NEC [6 cases]. Eight cases [40 %] died out of 20 cases which the interval between the presentation and interference were more than one day. CONCLUSIONS: Neonatal gastro-intestinal perforations are still associated with high mortality rate in our institutions, and delayed diagnosis with increased interval between the presentation and surgical intervention are associated with increased mortality. In our locality, although NEC is the commonest cause of NGIP, the iatrogenic cause is relatively higher than reported.


title: The impact of tracheostomy timing on clinical outcomes and adverse events in intubated patients with infratentorial lesions: early versus late tracheostomy

text: We evaluated the association between the timing of tracheostomy and clinical outcomes in patients with infratentorial lesions. We performed a retrospective observational cohort study in a neurosurgical intensive care unit (ICU) at a tertiary academic medical center from January 2014 to December 2018. Consecutive adult patients admitted to the ICU who underwent resection of infratentorial lesions as well as tracheostomy were included for analysis. Early tracheostomy was defined as performed on postoperative days 1–10 and late tracheostomy on days 10–20 after operation. Univariate and multivariate analyses were used to compare the characteristics and outcomes between both cohorts. A total of 143 patients were identified, and 96 patients received early tracheostomy. Multivariable analysis identified early tracheostomy as an independent variable associated with lower occurrence of pneumonia (odds ratio, 0.25; 95% CI, 0.09–0.73; p = 0.011), shorter stays in ICUs (hazard ratio, 0.4; 95% CI, 0.3–0.6; p = 0.03), and earlier decannulation (hazard ratio, 0.5; 95% CI, 0.4–0.8; p = 0.003). However, no significant differences were observed between the early and late tracheostomy groups regarding hospital mortality (p > 0.999) and the modified Rankin scale after 6 months (p = 0.543). We also identified postoperative brainstem deficits, including cough, swallowing attempts, and extended tongue as well as GCS < 8 at ICU admission as the risk factors independently associated with patients underwent tracheostomy. There is a significant association between early tracheostomy and beneficial clinical outcomes or reduced adverse event occurrence in patients with infratentorial lesions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10143-020-01339-7) contains supplementary material, which is available to authorized users.


title: Epistemic Consultants and the Regulation of Policy Knowledge in the Obama Administration

text: The agencies of the government of the United States of America, such as the Food and Drug Administration or the Environmental Protection Agency, intervene in American society through the collection, processing, and diffusion of information. The Presidency of Barack Obama was notable for updating and redesigning the US government’s information infrastructure. The White House enhanced mass consultation through open government and big data initiatives to evaluate policy effectiveness, and it launched new ways of communicating with the citizenry. In this essay we argue that these programs spelled out an emergent epistemology based on two assumptions: dispersed knowledge and a critique of judgment. These programs have redefined the evidence required to justify and design regulatory policy and conferred authority to a new kind of expert, which we call epistemic consultants.


Proceedings from the Editorial Board Meeting of The AJC in 2019