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.

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.

[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.

Preprints: An underutilized mechanism to accelerate outbreak science.

In an Essay, Michael Johansson and colleagues advocate the posting of research studies addressing infectious disease outbreaks as preprints.

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.

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.

[The opening of the French national health database: Opportunities and difficulties. The experience of the Gazel and Constances cohorts]. / L'ouverture du Système national d'information inter-régimes de l'assurance maladie (SNIIRAM) : des opportunités et des difficultés. L'expérience des cohortes Gazel et Constances.

BACKGROUND: In France, the national health database (SNIIRAM) is an administrative health database that collects data on hospitalizations and healthcare consumption for more than 60 million people. Although it does not record behavioral and environmental data, these data have a major interest for epidemiology, surveillance and public health. One of the most interesting uses of SNIIRAM is its linkage with surveys collecting data directly from persons. Access to the SNIIRAM data is currently relatively limited, but in the near future changes in regulations will largely facilitate open access. However, it is a huge and complex database and there are some important methodological and technical difficulties for using it due to its volume and architecture. METHODS: We are developing tools for facilitating the linkage of the Gazel and Constances cohorts to the SNIIRAM: interactive documentation on the SNIIRAM database, software for the verification of the completeness and validity of the data received from the SNIIRAM, methods for constructing indicators from the raw data in order to flag the presence of certain events (specific diagnosis, procedure, drug…), standard queries for producing a set of variables on a specific area (drugs, diagnoses during a hospital stay…). Moreover, the REDSIAM network recently set up aims to develop, evaluate and make available algorithms to identify pathologies in SNIIRAM. CONCLUSION: In order to fully benefit from the exceptional potential of the SNIIRAM database, it is essential to develop tools to facilitate its use.

International Trends in Health Science Librarianship Part 19: The Balkan States (Bulgaria and Croatia).

This is the 19th in a series of articles exploring international trends in health science librarianship in the 21st century. The focus of the present issue is the Balkan Region (Bulgaria and Croatia). The next regular feature column will investigate two other Balkan states - Serbia and Slovenia. JM.

Bioinformatic databases and resources in the public domain to aid HLA research.

Research in HLA as in any other field depends on information. Different groups have generated generic and specific resources and tools to support this research. The present review describes a qualified subset of these resources, which should cover the most important starting points for research in the HLA field. It discusses access to HLA allele sequences, allele frequencies, continues with general support to access to literature, DNA and protein sequence information, structural models, teaching books, databases with phenotypic datasets, alignment tools, peptide binding, statistical tools, guidelines and ambiguity coding. Following functionalities and databases have been included: IMGT/HLA, Immuno Polymorphism Database (IPD), allele frequencies*.net, a detailed look into NCBI (National Center of Biotechnology Information) with a subset of databases and tools, focusing on literature research, sequences, user-specific support tools and applications (PubMed, GenBank, MyNCBI, blast, Gene, MapViewer, Structure, CN3D, WorkBench, and dbMHC). This is followed by a brief survey of EBI-EMBL/Ensemble, the sequence alignment tool Clustal, the peptide and ligand databases SYFPEITHI and Immune Epitope Database, and last but not least statistical packages and HLA allele coding resources PyPop, the Immuno-genomics Data Analysis Working Group and the NMDP informatics section. All databases and tools can be freely accessed. Data linked to individuals, however, might require authorization by a data access committee.

[Epidemiological studies based on medical and administrative databases : a potential strength in France]. / Cohortes épidémiologiques et bases de données d'origine administrative: un rapprochement potentiellement fructueux.

Population-based epidemiological cohorts may include nowadays hundreds of thousands of subjects, followed-up during decades. France has a major potential strength: nationwide medical and social databases set up for administrative purposes. The main databases useful for epidemiology are the social security database which contains individual medical data from different sources, and the retirement fund database on employment and social benefits. These databases have several advantages: they cover the whole French population, with no lost to follow-up, data are often of good quality and it is possible to link them with individual surveys. However medical data are not always ascertained and an important methodological and practical work has to be done, and some legal and practical problems have to be solved for an optimal use.

Aggregating data for computational toxicology applications: The U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System.

Computational toxicology combines data from high-throughput test methods, chemical structure analyses and other biological domains (e.g., genes, proteins, cells, tissues) with the goals of predicting and understanding the underlying mechanistic causes of chemical toxicity and for predicting toxicity of new chemicals and products. A key feature of such approaches is their reliance on knowledge extracted from large collections of data and data sets in computable formats. The U.S. Environmental Protection Agency (EPA) has developed a large data resource called ACToR (Aggregated Computational Toxicology Resource) to support these data-intensive efforts. ACToR comprises four main repositories: core ACToR (chemical identifiers and structures, and summary data on hazard, exposure, use, and other domains), ToxRefDB (Toxicity Reference Database, a compilation of detailed in vivo toxicity data from guideline studies), ExpoCastDB (detailed human exposure data from observational studies of selected chemicals), and ToxCastDB (data from high-throughput screening programs, including links to underlying biological information related to genes and pathways). The EPA DSSTox (Distributed Structure-Searchable Toxicity) program provides expert-reviewed chemical structures and associated information for these and other high-interest public inventories. Overall, the ACToR system contains information on about 400,000 chemicals from 1100 different sources. The entire system is built using open source tools and is freely available to download. This review describes the organization of the data repository and provides selected examples of use cases.