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Graph-Representation of Patient Data: a Systematic Literature Review.

ABSTRACT: Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs. This systematic literature review aims to investigate the frontiers of the current research in the field of graphs representing and processing patient data. We want to show, which areas of research in this context need further investigation. The databases MEDLINE, Web of Science, IEEE Xplore and ACM digital library were queried by using the search terms health record, graph and related terms. Based on the "Preferred Reporting Items for Systematic Reviews and Meta-Analysis" (PRISMA) statement guidelines the articles were screened and evaluated using full-text analysis. Eleven out of 383 articles found in systematic literature review were finally included for analysis in this literature review. Most of them use graphs to represent temporal relations, often representing the connection among laboratory data points. Only two papers report that the graph data were further processed by comparing the patient graphs using similarity measurements. Graphs representing individual patients are hardly used in research context, only eleven papers considered such kind of graphs in their investigations. The potential of graph theoretical algorithms, which are already well established, could help increasing this research field, but currently there are too few papers to estimate how this area of research will develop. Altogether, the use of such patient graphs could be a promising technique to develop decision support systems for diagnosis, medication or therapy of patients using similarity measurements or different kinds of analysis.

SUBMITTER: Schrodt J

PROVIDER: S-EPMC7067737 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Graph-Representation of Patient Data: a Systematic Literature Review.

Schrodt Jens J Dudchenko Aleksei A Knaup-Gregori Petra P Ganzinger Matthias M

Journal of medical systems 20200312 4

Graph theory is a well-established theory with many methods used in mathematics to study graph structures. In the field of medicine, electronic health records (EHR) are commonly used to store and analyze patient data. Consequently, it seems straight-forward to perform research on modeling EHR data as graphs. This systematic literature review aims to investigate the frontiers of the current research in the field of graphs representing and processing patient data. We want to show, which areas of r ...[more]

PMID: 32166501

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Project description:BACKGROUND:In genomics and proteomics, membrane protein analysis have shown that such analyses are very important to support the understanding of complex biological processes. In Genome-wide investigations of membrane proteins a large number of short, distinct sequence motifs has been revealed. Such motifs found so far support the understanding of the folded membrane protein in the membrane environment. They provide important information about functional or stabilizing properties. Recently several integrative approaches have been proposed to extract meaningful information out of the membrane environment. However, many information based approaches deliver results having deficits of visualisation outputs. Outgoing from high-throughput protein data analysis, these outputs play an important role in the evaluation of high-dimensional protein data, to establish a biological relationship and ultimately to provide useful information for research. RESULTS:We have evaluated different resulting graphs generated from statistical analysis of consecutive motifs in helical structures of the membrane environment. Our results show that representative motifs with high occurrence in all investigated protein families are responsible for the general importance in alpha-helical membrane structure formation. Further, motifs which often occur with others in their function as so called "hubs" lead to the assumption, that these motifs constitute as important components in helical structures within the membrane. Otherwise, consecutive motifs and hubs which show a high occurrence in certain families only can be classified as important for family-specific functional characteristics. Summarized, we are able to bridge our graphical results from high-throughput analysis of membrane proteins over networking with databases to a biological context. CONCLUSIONS:Our results and the corresponding graphical visualisation support the understanding and interpretation of structure forming and functional motifs of membrane proteins. Our results are useful to interpret and refine results of common developed approaches. At last we show a simple way to visualise high-dimensional protein data in context to biological relevant information.

Project description:Background Gender as a social construct contributes to determine who migrates and which migration-related risks and opportunities emerge in all phases of the migration trajectory. Simultaneously, migration influences the individual as well as societal definition and perception of gender roles. An explicit gender perspective in migration-related epidemiological research can contribute to adequately analyse and interpret the health of migrants. This systematic review gives a comprehensive overview on how gender has been conceptualised, operationalised and measured in social epidemiologic studies aiming to assess the influence of gender on health among migrants. Methods We searched PubMed, Embase, CINAHL, the Cochrane Library, EconLit and PsycINFO and conducted backward reference searching. Reviewers independently selected studies, extracted data and conducted the quality assessment. Eligible studies actively aimed to understand, identify or explain the influence of gender on migrants’ health, whereby the role of gender can encompass a variety of mechanisms, processes or states of differentiation, discrimination and/or inequality. Results Almost all of the 43 studies were cross-sectional and focussed on health outcomes in the post-migration phase. The most common theme of research was the health of male migrants in the US, and in particular of men who have sex with men (MSM). All studies treated gender as a binary variable (men vs. women), without discussing additional types of gender identities. A minority of studies differentiated clearly between sex and gender. Gender was mostly operationalised through attitudes toward gender roles and gender-based discrimination, experienced at the individual level. Community and societal level gender measures capturing structural gender determinants were underrepresented. Conclusions The intersections of migration and gender suggested synergistic effects on health that only become visible when considering those two social determinants together. Future research needs to embrace a multilevel and non-binary understanding of gender and reflect on the influence of gender in the different phases of the migration journey. Systematic review registration PROSPERO CRD42019124698.

Project description:BackgroundFor the results of clinical trials to have external validity, the patients included in the study must be representative of the population presenting in the general clinical settings. A scoping literature review was performed to evaluate how the eligibility criteria used in anti-malarial efficacy and safety trials translate into patient selection.MethodsA search of the WorldWide Antimalarial Resistance Network (WWARN) Clinical Trials Publication Library, MEDLINE, The Cochrane Library, and clinicaltrials.gov was conducted to identify trials investigating anti-malarial efficacy and safety, published between 14th April 2001 and 31st December 2017. An updated search using the WWARN Clinical Trial Publication Library was undertaken to identify eligible publications from 1st January 2018 to 31st July 2021. The review included studies in patients of any age with uncomplicated malaria and any pharmaceutical therapeutic intervention administered. The proportion of trials with malaria-positive patients excluded was calculated and linked to the reported reason for exclusion. A subgroup analysis on eligibility criteria and trial baseline demographics was conducted to assess whether criteria are complied with when recruiting patients.ResultsOut of 847 studies, 176 (21%) trials were included in the final synthesis, screening a total of 157,516 malaria-positive patients, of whom 56,293 (36%) were enrolled and treated. Across the 176 studies included, 84 different inclusion and exclusion criteria were identified. The reason for exclusion of patients who tested positive for malaria was reported in 144 (82%) studies. Three criteria account for about 70% of malaria-positive patients excluded: mixed-species malaria infections or other specific Plasmodium species, parasite counts outside the set study ranges, and refusal of consent.ConclusionsNearly two-thirds of the malaria-positive subjects who present to health facilities are systematically excluded from anti-malarial treatment trials. Reasons for exclusions are largely under-reported. Anti-malarial treatment in the general population is informed by studies on a narrow selection of patients who do not fully represent the totality of those seeking antimalarial treatment in routine practice. While entry criteria ensure consistency across trials, pragmatic trials are also necessary to supplement the information currently available and improve the external validity of the findings of malaria clinical trials.

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Graph-Representation of Patient Data: a Systematic Literature Review.

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Graph-Representation of Patient Data: a Systematic Literature Review.

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