EUAdb: A resource for COVID-19 test development and comparison.

Due to the sheer number of COVID-19 (coronavirus disease 2019) cases there is a need for increased world-wide SARS-CoV-2 testing capability that is both efficient and effective. Having open and easy access to detailed information about these tests, their sensitivity, the types of samples they use, etc. would be highly useful to ensure their reproducibility, to help clients compare and decide which tests would be best suited for their applications, and to avoid costs of reinventing similar or identical tests. Additionally, this resource would provide a means of comparing the many innovative diagnostic tools that are currently being developed in order to provide a foundation of technologies and methods for the rapid development and deployment of tests for future emerging diseases. Such a resource might thus help to avert the delays in testing and screening that was observed in the early stages of the pandemic and plausibly led to more COVID-19-related deaths than necessary. We aim to address these needs via a relational database containing standardized ontology and curated data about COVID-19 diagnostic tests that have been granted Emergency Use Authorizations (EUAs) by the FDA (US Food and Drug Administration). Simple queries of this actively growing database demonstrate considerable variation among these tests with respect to sensitivity (limits of detection, LoD), controls and targets used, criteria used for calling results, sample types, reagents and instruments, and quality and amount of information provided.

[Health data in France: Abundant but complex]. / Les données de santé en France - Abondantes mais complexes.

TITLE: Les données de santé en France - Abondantes mais complexes. ABSTRACT: Alors que l'application de traçage des contacts (contact tracing) StopCovid (transformée à la mi-octobre 2020 en TousAntiCovid), débattue au Parlement1 en raison des inquiétudes qu'elle suscitait concernant la confidentialité des données personnelles et les libertés individuelles du fait qu'elle permet d'alerter un utilisateur s'il s'est trouvé à proximité d'une personne atteinte de la COVID-19, a été adoptée par près de 12 millions de personnes2, un dispositif concernant les données individuelles de santé, aux conséquences potentiellement beaucoup plus importantes pour les citoyens et leurs données personnelles, a commencé à se mettre en place suite à la Loi du 24 juillet 2019 (Loi n° 2019-774) relative à l'organisation et à la transformation du système de santé3 : la plateforme des données de santé, communément appelée Health Data Hub, constituée sous la forme d'un groupement d'intérêt public (GIP). Il ne s'agit plus de simplement signaler qu'on a croisé une personne anonyme infectée par le SARS-Cov-2, mais de réunir, dans une infrastructure informatique unique, un immense ensemble de données personnelles particulièrement sensibles concernant la totalité de la population française. Ce projet suscite désormais un certain intérêt médiatique et un début d'inquiétude. Mais cette inquiétude ne concerne presque uniquement que le fait que ces données sont déposées et gérées dans un cloud appartenant à une société américaine, un nuage informatique qui tombe sous le coup de la loi américaine de 2018 dite « CLOUD act4 ¼, qui ouvre la possibilité d'un transfert des données personnelles vers les États-Unis, comme s'en est inquiété récemment le Conseil d'État.5 Cet aspect est certes très important, mais il masque également de très nombreux enjeux liés au partage des données de santé, et qui sont largement méconnus de la population. Nous nous proposons de rappeler, tout d'abord, ce que sont les données de santé, ce qu'elles apportent et la nécessité d'en faciliter le partage, mais aussi les difficultés rencontrées pour leur accès et leur utilisation. Nous expliquerons ensuite, dans un deuxième article, en quoi cette plateforme des données de santé, telle qu'elle est conçue et pilotée par les pouvoirs publics pour répondre à ces difficultés et pour promouvoir l'intelligence artificielle en santé, est un projet qui soulève de fortes inquiétudes pour les citoyens et la société dans son ensemble. Même si les problèmes posés se présentent sous une forme différente selon les pays, notre propos concernera spécifiquement la situation en France.

[Production of knowledge using data collected by associations of patients: The fibromyalgia example]. / Production de savoirs à partir de données collectées par les associations de malades - L'exemple de la fibromyalgie.

To respond to the social challenge of medical knowledge democratisation, numerous initiatives have been developed: information, training or consultation of patients or research applications funded by associations of patients. Only a few numbers of collaborations are initiated by the persons directly involved (patients and relatives) or fulfill association research need. We have adopted and tested such an approach with the French fibromyalgia association (Fibromyalgie France). Our work demonstrates the interest to use data collected by associations of patients to answer to their questioning or to rise further relevant research questions. Such participative approach will have a pertinent and significant impact on the knowledge of diseases and on the development of collaborative actions of research, providing a better answer to patient needs, while being methodologically rigorous.

TITLE: Production de savoirs à partir de données collectées par les associations de malades - L'exemple de la fibromyalgie. ABSTRACT: Pour répondre au défi sociétal de démocratisation de l'accès à la connaissance, différentes initiatives de recherches participatives se développent : actions d'information, de formation ou de consultation des citoyens ou par l'intermédiaire de demandes de financement par des chercheurs auprès des associations. Cependant, peu des collaborations chercheurs-malades sont à l'initiative des personnes concernées, les patients et leurs familles. Nous avons adopté et testé cette démarche à la demande et en coopération avec l'association Fibromyalgie France.

National diabetes registries: do they make a difference?

AIMS: The global epidemic of diabetes mellitus continues to expand, including its large impact on national health care. Measuring diabetes outcomes and their causes of variation highlights areas for improvement in care and efficiency gains; large registries carry this potential. By means of a systematic review, we aimed to give an overview of national registries worldwide by quantifying their data and assessing their influence on diabetes care. METHODS: The literature on MEDLINE up to March 31, 2020, was searched, using keywords diabetes mellitus, national, registry, registration, and/or database. National disease-specific registries from corresponding articles were included. Database characteristics and clinical variables were obtained. All registries were compared to the ICHOM standard set of outcomes. RESULTS: We identified 12 national clinical diabetes registries, comprising a total of 7,181,356 diabetic patients worldwide. Nearly all registries recorded weight, HbA1c, lipid profile, and insulin treatment; the recording of other variables varied to a great extent. Overall, registries corresponded fairly well with the ICHOM set. Most registries proved to monitor and improve the quality of diabetes care using guidelines as a benchmark. The effects on national healthcare policy were more variable and often less clear. CONCLUSIONS: National diabetes registries confer clear insights into diagnostics, complications, and treatment. The extent to which registries influenced national healthcare policy was less clear. A globally implemented standard outcome set has the potential to improve concordance between national registries, enhance the comparison and exchange of diabetes outcomes, and allocate resources and interventions where most needed.

Shaping a data-driven era in dementia care pathway through computational neurology approaches.

BACKGROUND: Dementia is caused by a variety of neurodegenerative diseases and is associated with a decline in memory and other cognitive abilities, while inflicting an enormous socioeconomic burden. The complexity of dementia and its associated comorbidities presents immense challenges for dementia research and care, particularly in clinical decision-making. MAIN BODY: Despite the lack of disease-modifying therapies, there is an increasing and urgent need to make timely and accurate clinical decisions in dementia diagnosis and prognosis to allow appropriate care and treatment. However, the dementia care pathway is currently suboptimal. We propose that through computational approaches, understanding of dementia aetiology could be improved, and dementia assessments could be more standardised, objective and efficient. In particular, we suggest that these will involve appropriate data infrastructure, the use of data-driven computational neurology approaches and the development of practical clinical decision support systems. We also discuss the technical, structural, economic, political and policy-making challenges that accompany such implementations. CONCLUSION: The data-driven era for dementia research has arrived with the potential to transform the healthcare system, creating a more efficient, transparent and personalised service for dementia.

Construction and Use of Body Weight Measures from Administrative Data in a Large National Health System: A Systematic Review.

OBJECTIVE: Administrative data are increasingly used in research and evaluation yet lack standardized guidelines for constructing measures using these data. Body weight measures from administrative data serve critical functions of monitoring patient health, evaluating interventions, and informing research. This study aimed to describe the algorithms used by researchers to construct and use weight measures. METHODS: A structured, systematic literature review of studies that constructed body weight measures from the Veterans Health Administration was conducted. Key information regarding time frames and time windows of data collection, measure calculations, data cleaning, treatment of missing and outlier weight values, and validation processes was collected. RESULTS: We identified 39 studies out of 492 nonduplicated records for inclusion. Studies parameterized weight outcomes as change in weight from baseline to follow-up (62%), weight trajectory over time (21%), proportion of participants meeting weight threshold (46%), or multiple methods (28%). Most (90%) reported total time in follow-up and number of time points. Fewer reported time windows (54%), outlier values (51%), missing values (34%), or validation strategies (15%). CONCLUSIONS: A high variability in the operationalization of weight measures was found. Improving methods to construct clinical measures will support transparency and replicability in approaches, guide interpretation of findings, and facilitate comparisons across studies.

Researchers' And Medical Student' Experience in Reference Management Software in a Low-Income Country.

INTRODUCTION: Although the use of Reference Management Software (RMS) is increasing in developed countries, they seem to be unknown and less used in low-income countries. AIM: To discover the major trends in the use of RMS among researchers and Ph.D. students in Tunisia, as a low-income country. METHODS: A hardcopy survey was filled out by researchers and Ph.D. students during an educational seminar at the faculty of medicine of Sfax in 2016 with the aim to collect qualitative data to determine the participants' knowledge and use of RMS. RESULTS: The survey collected 121 participants, among them, 53.7% know RMS. Mendeley proved to be the best-known software (41.5%), followed by Zotero (35.3%) and Endnote (23%). Training sessions in RMS were taken by 5% of participants. Among the 121 participants, 26.5%of them use RMS., Mendeley was the most used (46.9%), followed by EndNote (28.1%) and Zotero (25%). The most commonly popular feature in RMS is inserting citations (66.9%). Therefore, the analysis, of the reasons behind the choice of RMS proves that the software was used because it is convenient (38.4%),  most known (38.4%),  easy (30.7%), or suggested by colleagues (30.7%). The free and open-source software was preferred by 81% of the participants. g. However, 50.4% ignore the fact that Zotero is free. Several types and sources of captured citations were unknown by 53.8% and 59% of the rest of the participants. CONCLUSION: The results clearly show that the lack of awareness about RMS in Tunisia is due to the absence of a formal training. As a result, the need for such training is highly important for researchers to be able to benefit from the different advantages of RMS while conducting their academic medical education.

The construction and application of an ultrasound and anatomical cross-sectional database of structural malformations of the fetal heart.

OBJECTIVES: Establish a fetal heart anatomical cross-sectional database that correlates with screening transverse ultrasound images suggested by international professional organizations to detect congenital heart defects. METHODS: Fetuses with suspected congenital heart defects identified using the following cardiac image sequences obtained from transverse slices beginning from the upper abdomen and ending in the upper thorax were the subjects of this study: (1) four-chamber view, (2) left ventricular outflow tract view, (3) three-vessel right ventricular outflow tract view, and (4) the three-vessel tracheal view. A database of digital two-dimensional images of the transverse sweep was created for fetuses with confirmed congenital heart defects. In addition, using four-dimensional ultrasound spatial-temporal image correlation, selected transverse ultrasound images were acquired as part of the database. Ultrasound-detected congenital heart defects were confirmed postnatally from pathological specimens of the heart and lungs using a cross-sectional technique that mirrored the ultrasound images described above. When anatomical specimens were not available, prenatal ultrasound-detected congenital heart defects were confirmed using postnatal echocardiography and/or following surgery. RESULTS: The four screening views described in the Methods section identified 160 fetuses that comprised the database. Forty-five datasets consisted of both ultrasound and anatomical cross-sectional images. Thirteen percent (6/45) only had abnormalities of the four-chamber view (eg, endocardial cushion defects). Twenty-four percent (11/45) had abnormalities of the four-chamber view as well as right and left outflow tracts (eg, complex malformations). Of these, 10 of 11 had an abnormal tracheal view. Sixteen percent (7/45) had an abnormal four-chamber view and abnormal right outflow tract (eg, pulmonary stenosis). Thirty-three percent (15/45) had a normal four-chamber view but had abnormal right and left outflow tracts as well as an abnormal tracheal view (eg, tetralogy of Fallot, D-transposition of the great arteries). CONCLUSIONS: Combining both ultrasound and anatomical imaging may be of assistance in training imagers to recognize cardiovascular pathology when performing the screening examination of the fetal heart.

[Introduction into the world of biobanks in human health]. / Les biobanques, des structures essentielles à la recherche médicale.

TITLE: Les biobanques, des structures essentielles à la recherche médicale. ABSTRACT: Le Master Biobanks and Complex Data Management forme les managers des biobanques. Créé en 2017 à l'Université Côte d'Azur par le Professeur Paul Hofman, ce master prépare les étudiants au management des biobanques (humaines, animales, plantes et autres organismes vivants) et des données complexes. Au-delà du stockage des collections d'échantillons biologiques, il faut en assurer la qualité, la conservation, la disponibilité auprès des réseaux de chercheurs en respectant la législation et l'éthique. Les enseignements du master se partagent entre les compétences disciplinaires en qualité, hygiène et sécurité, réglementation, bioéthique, biobankonomics et les enseignements techniques réalisés à la biobanque du CHU de Nice, puis mis en pratique lors de deux stages de 6 mois.

[What place for French morbidity registries in the era of big data?] / Quelle place pour les registres de morbidité à l'ère des données massives de santé ?

The recent opening of massive health databases, as well as the development of methods and tools adapted to their data processing, questions the French model of "morbidity registry". In France in 2019, nearly 61 health registries were operating. As defined by law, these registries identify exhaustively all patients with a given disease in a given territory. Established several decades ago, these registries are part of the French surveillance system that is used for research and evaluation purposes. Since the advent of recent technological progress, large-scale databases are made available to researchers and it is possible with these databases to answer questions initially assigned to the registries. What is the place of such registries in this new context: are they obsolete or still useful? Should they be opposed to the new tools or are they complementary to them, and if so, what is their place in the new French public health ecosystem? The objective of this work was to assess the roles and missions of existing registries and to reflect on their positioning in this new environment. The French model of registry is sometimes questioned because of the complexity of its circuits, requiring a significant amount of human resources. However, the data that constitute them, validated by cross-checking information from several sources, are of very high quality, and make it possible to validate the data in the new databases (National Health Data System (NSDS) or Hospital Data Warehouses). Registries and new databases are in fact complementary, and far from jeopardizing this model, the recent opening of these databases represents an opportunity for registries to modernize their operations and respond to new missions.

Using national electronic health care registries for comparing the risk of psychiatric re-hospitalisation in six European countries: Opportunities and limitations.

Psychiatric re-hospitalisation rates have been of longstanding interest as health care quality metric for planners and policy makers, but are criticized for not being comparable across hospitals and countries due to measurement unclarities. The objectives of the present study were to explore the interoperability of national electronic routine health care registries of six European countries (Austria, Finland, Italy, Norway, Romania, Slovenia) and, by using variables found to be comparable, to calculate and compare re-hospitalisation rates and the associated risk factors. A "Methods Toolkit" was developed for exploring the interoperability of registry data and protocol led pilot studies were carried out. Problems encountered in this process are described. Using restricted but comparable data sets, up to twofold differences in psychiatric re-hospitalisation rates were found between countries for both a 30- and 365-day follow-up period. Cumulative incidence curves revealed noteworthy additional differences. Health system characteristics are discussed as potential causes for the differences. Multi-level logistic regression analyses showed that younger age and a diagnosis of schizophrenia/mania/bipolar disorder consistently increased the probability of psychiatric re-hospitalisation across countries. It is concluded that the advantage of having large unselected study populations of national electronic health care registries needs to be balanced against the considerable efforts to examine the interoperability of databases in cross-country comparisons.

Epidemic preparedness: why is there a need to accelerate the development of diagnostics?

Global epidemics of infectious diseases are increasing in frequency and severity. Diagnostics are needed for rapid identification of the cause of the epidemic to facilitate effective control and prevention. Lessons learned from the recent Ebola virus and Zika virus epidemics are that delay in developing the right diagnostic for the right population at the right time has been a costly barrier to disease control and prevention. We believe that it is possible to accelerate and optimise diagnostic development through a five-pronged strategy: by doing a global landscape analysis of diagnostic availability worldwide; through strategic partnerships for accelerating test development, in particular with vaccine companies to identify novel diagnostic targets; by creating and sharing repositories of data, reagents, and well characterised specimens for advancing the development process; by involving key public and private stakeholders, including appropriate regulatory bodies and policy makers, to ensure rapid access for researchers to diagnostics; and last, by fostering an enabling environment for research and access to diagnostics in the countries that need them. The need is great, but not insurmountable and innovative and faster development pathways are urgently required to address current shortfalls.

From Plant Compounds to Botanicals and Back: A Current Snapshot.

This work aims at giving an updated picture of the strict interaction between main plant biologically active compounds and botanicals. The main features of the emerging class of dietary supplements, the botanicals, are highlighted. Focus is also on the definition of actual possibilities of study approach and research strategies. Examples of innovative directions are given: assessment of interaction of bioactive compounds, chemometrics and the new goal of biorefineries. Current models of existing databases, such as plant metabolic pathways, food composition, bioactive compounds, dietary supplements, and dietary markers, are described as usable tools for health research. The need for categorization of botanicals as well as for the implementation of specific and dedicated databases emerged, based on both analytical data and collected data taken from literature throughout a harmonized and standardized approach for the evaluation of an adequate dietary intake.

[Health data]. / Les données de santé.

Healthcare is considered as one of the most promising areas where big data can be applied to foster innovation for the benefit of patients and of the whole system. Healthcare analytics have the potential to accelerate R&D, increase knowledge on diseases and risk factors, improve treatments, develop personalised medicine, help physicians with decision support systems… The access to data is also a driving force for patients' empowerment and for the democratic debate. However, there are also concerns about the societal, economic and ethic impacts of this wave of digitization and of the growing use of data, algorithms and artificial intelligence. Given the issues at stake, collecting and analysing data generated by health care systems is a strategic challenge in all countries; in that respect the French National System of Health Data (a national data warehouse linking data from several sources and giving a vision of the care pathways for the entire population, with a ten-year history) is an asset, but it has to be completed and enriched with data from electronic health records.

The need for appropriate registration of pregnancy outcomes under newer oral glucose-lowering therapies.

Because of the increase in type 2 diabetes (T2DM) in young adults, women of childbearing age are frequently treated with newer glucose-lowering therapies, and an increase in unintentional exposure to therapies unapproved for use during pregnancy is expected. The clinician is left with the dilemma of deciding between discontinuation of a novel agent that is providing excellent glycaemic control, while switching to other agents may cause deterioration of glycaemia, and continued use of novel agents that may have uncertain effects on the unborn child. For T2DM, pregnancy data are collected only via spontaneous reporting systems. Therefore, we evaluated the available data on pregnancy outcomes under newer glucose-lowering agents in pharmaceutical safety databases. We found that data on pregnancy outcomes with new glucose-lowering agents in T2DM are scarce, with a high risk of bias towards negative outcomes, limiting their usefulness in robustly assessing safety. Because of the lack of information at present, these agents are not recommended for use during pregnancy or when planning pregnancy. To better guide clinical practice, structured systems of assessing pregnancy outcomes in women receiving these novel agents are urgently needed.