Modelling Adverse Events with the TOP Phenotyping Framework.

The detection and prevention of medication-related health risks, such as medication-associated adverse events (AEs), is a major challenge in patient care. A systematic review on the incidence and nature of in-hospital AEs found that 9.2% of hospitalised patients suffer an AE, and approximately 43% of these AEs are considered to be preventable. Adverse events can be identified using algorithms that operate on electronic medical records (EMRs) and research databases. Such algorithms normally consist of structured filter criteria and rules to identify individuals with certain phenotypic traits, thus are referred to as phenotype algorithms. Many attempts have been made to create tools that support the development of algorithms and their application to EMRs. However, there are still gaps in terms of functionalities of such tools, such as standardised representation of algorithms and complex Boolean and temporal logic. In this work, we focus on the AE delirium, an acute brain disorder affecting mental status and attention, thus not trivial to operationalise in EMR data. We use this AE as an example to demonstrate the modelling process in our ontology-based framework (TOP Framework) for modelling and executing phenotype algorithms. The resulting semantically modelled delirium phenotype algorithm is independent of data structure, query languages and other technical aspects, and can be run on a variety of source systems in different institutions.

Concept Graphs: A Novel Approach for Textual Analysis of Medical Documents.

The task of automatically analyzing the textual content of documents faces a number of challenges in general but even more so when dealing with the medical domain. Here, we can't normally rely on specifically pre-trained NLP models or even, due to data privacy reasons, (massive) amounts of training material to generate said models. We, therefore, propose a method that utilizes general-purpose basic text analysis components and state-of-the-art transformer models to represent a corpus of documents as multiple graphs, wherein important conceptually related phrases from documents constitute the nodes and their semantic relation form the edges. This method could serve as a basis for several explorative procedures and is able to draw on a plethora of publicly available resources. We test it by comparing the effectiveness of these so-called Concept Graphs with another recently suggested approach for a common use case in information retrieval, document clustering.

Growth Patterns of Children With Short Stature in Adulthood According to Auxological Status and Maturity at Birth.

CONTEXT: Prematurity carries a risk for impaired postnatal growth and long-term growth restriction. Especially children born SGA seem vulnerable for poor growth, as a persistent short stature can be observed in app 10-15% of these children. OBJECTIVE: In this study we aimed to recognize differences in growth patterns of children according to sex, maturity, and auxological status at birth facilitating earlier identification of small-for-gestational-age (SGA) children with adult short stature. METHODS: The growth data of 44 791 infants born between January 1, 1980, and December 30, 2012, among 2 pediatric cohorts with follow-up through December 31, 2020, were analyzed. A total of 5698 children with birth data had measurements at near final height (nfh) and at least 2 further points. RESULTS: Preterm children (gestational age < 37 weeks) had a significantly lower mean nfh SDS than term children (preterm, -0.61; term, -0.18) and a higher likelihood of nfh < third percentile (preterm, 20.5%; term, 12.2%). SGA born children also had a lower mean nfh SD score (SDS) than children born appropriate for gestational age (AGA) (SGA, -1.06; AGA, -0.15) and a higher likelihood of nfh < third percentile (SGA, 28.2%; AGA 10.1%). Of 1204 SGA children, 672 (56%) showed successful catch-up growth (CUG) to nfh greater than or equal to the 10th percentile (SGA-CU), and 532 children (44%) did not (SGA-S). The difference in their mean nfh SDS (SGA-CU, -0.12; SGA-S -2.26) can only partly be explained by the differences in mean mid-parental height SDS (SGA-CU, -0.3; SGA-S, -1.19). During the first year, SGA-CU showed higher CUG (SGA-CU, +1.2 SDS; SGA-S, +0.45 SDS), which helps to discriminate between groups earlier. CONCLUSION: Final growth outcome was influenced by prematurity and auxological status at birth, but not by sex. Height/length SDS increments during year 1 are instrumental to discern SGA children with later normal or short stature. While observing CUG until year 2 and 3 can add specificity, discrimination thereafter becomes difficult.

The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online.

BACKGROUND: Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains. OBJECTIVE: The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects. METHODS: Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. RESULTS: The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.

The Influence of Body Mass Index on the Growth Hormone Peak Response regarding Growth Hormone Stimulation Tests in Children.

INTRODUCTION: Several studies have analyzed the association between the maximal growth hormone serum level obtained during a growth hormone stimulation test (GHMax) and the body mass index-standard deviation score (BMI-SDS). However, as sample sizes were quite small, our study aimed to analyze the association between GHMax and BMI-SDS within a large cohort of 991 children. Further, we investigated other influencing factors, like test type, age, sex, puberty, and preterm birth. METHODS: Children with short stature (height <10th percentile) received growth hormone stimulation tests with arginine or glucagon at the Department of Paediatric Endocrinology of the University of Leipzig Medical Center. The study population included a total of 1,438 tests (633 tests on girls, 805 tests on boys), with the majority consisting of prepubertal children (tests = 1,138). The mean age at testing was 7.74 years. Analyses were carried out on the entire cohort as well as stratified by test types. We performed univariate and multivariate analyses using linear mixed-effect models to assess the effects on GHMax. RESULTS: GHMax and BMI-SDS were significantly negatively associated with an effect size of ß = -1.10 (p < 0.001), independent from the test type. The GHMax values were significantly (p < 0.001) higher for glucagon (mean value: 9.65 ng/mL) than those for arginine tests (mean value: 8.50 ng/mL). Age, sex, premature birth, and puberty were not significantly related to GHMax values. CONCLUSION: We confirmed the negative association between GHMax and weight status of short children found in previous studies. Therefore, considering BMI-SDS may be helpful in the assessment of growth hormone stimulation tests in short-statured children, but it should not be the determining factor for a treatment decision.

Improving Findability of Digital Assets in Research Data Repositories Using the W3C DCAT Vocabulary.

Research data management requires stable, trustworthy repositories to safeguard scientific research results. In this context, rich markup with metadata is crucial for the discoverability and interpretability of the relevant resources. SEEK is a web-based software to manage all important artifacts of a research project, including project structures, involved actors, documents and datasets. SEEK is organized along the ISA model (Investigation - Study - Assay). It offers several machine-readable serializations, including JSON and RDF. In this paper, we extend the power of RDF serialization by leveraging the W3C Data Catalog Vocabulary (DCAT). DCAT was specifically designed to improve interoperability between digital assets on the Web and enables cross-domain markup. By using community-consented gold standard vocabularies and a formal knowledge description language, findability and interoperability according to the FAIR principles are significantly improved.

Age- and weight group-specific weight gain patterns in children and adolescents during the 15 years before and during the COVID-19 pandemic.

BACKGROUND/OBJECTIVES: There is a concern that measures aiming to limit a further spread of COVID-19, e.g., school closures and social distancing, cause an aggravation of the childhood obesity epidemic. Therefore, we compared BMI trends during the 15 years before and during the COVID-19 pandemic. SUBJECTS/METHODS: To assess the change in weight dynamics during the first months of COVID-19, we compared the trends of 3-month change in BMI-SDS (ΔBMI-SDS) and the proportions of children showing a high positive (HPC) or high negative (HNC) weight change between 2005 and 2019 and the respective changes from 2019 (pre-pandemic) to 2020 (after the onset of anti-pandemic measures) in more than 150,000 children (9689 during the pandemic period). The period of 3 months corresponds approximately to the first lockdown period in Germany. RESULTS: During the COVID-19 pandemic, we found a substantial weight gain across all weight and age groups, reflected by an increase in the 3-month change in BMI-SDS (ß = 0.05, p < 0.001), an increase in the proportion of children showing HPC (OR = 1.4, p < 0.001), and a decrease in the proportion of children showing HNC (OR = 0.7, p < 0.001). Besides, we found the same trends since 2005 on a low but stable level with a yearly increase of ΔBMI-SDS by ß = 0.001 (p < 0.001), the odds of HPC increased by ORhigh_pos = 1.01 (p < 0.001), and the odds of HNC decreased by ORhigh_neg = 0.99 (p < 0.001). These rather small effects accumulated to ß = 0.02, ORhigh_pos = 1.14, and ORhigh_pos = 0.85 over the whole period 2005-2019. Alarmingly, both the long-term and the short-term effects were most pronounced in the obese subgroup. CONCLUSIONS: There are positive dynamics in different measures of weight change, indicating a positive trend in weight gain patterns, especially within the group of children with obesity. These dynamics are likely to be escalated by COVID-19-related measures. Thus, they may lead to a significant further aggravation of the childhood obesity pandemic.

Ontological Modelling and Execution of Phenotypic Queries in the Leipzig Health Atlas.

Sharing data is of great importance for research in medical sciences. It is the basis for reproducibility and reuse of already generated outcomes in new projects and in new contexts. FAIR data principles are the basics for sharing data. The Leipzig Health Atlas (LHA) platform follows these principles and provides data, describing metadata, and models that have been implemented in novel software tools and are available as demonstrators. LHA reuses and extends three different major components that have been previously developed by other projects. The SEEK management platform is the foundation providing a repository for archiving, presenting and secure sharing a wide range of publication results, such as published reports, (bio)medical data as well as interactive models and tools. The LHA Data Portal manages study metadata and data allowing to search for data of interest. Finally, PhenoMan is an ontological framework for phenotype modelling. This paper describes the interrelation of these three components. In particular, we use the PhenoMan to, firstly, model and represent phenotypes within the LHA platform. Then, secondly, the ontological phenotype representation can be used to generate search queries that are executed by the LHA Data Portal. The PhenoMan generates the queries in a novel domain specific query language (SDQL), which is specific for data management systems based on CDISC ODM standard, such as the LHA Data Portal. Our approach was successfully applied to represent phenotypes in the Leipzig Health Atlas with the possibility to execute corresponding queries within the LHA Data Portal.

COVID-19 pandemic and families' utilization of well-child clinics and pediatric practices attendance in Germany.

OBJECTIVE: The COVID-19 pandemic and the measures implemented to stop the pandemic had a broad impact on our daily lives. Besides work and social life, health care is affected on many levels. In particular, there is concern that attendance in health care programs will drop or hospital admissions will be delayed due to COVID-19-related anxieties, especially in children. Therefore, we compared the number of weekly visits to 78 German pediatric institutions between 2019 and 2020. RESULTS: We found no significant differences during the first 10 weeks of the year. However, and importantly, from April, the weekly number of visits was more than 35% lower in 2020 than in 2019 (p = 0.005). In conclusion, the COVID-19 pandemic seems to relate to families´ utilization of outpatient well-child clinics and pediatric practice attendance in Germany.

Ontological representation, classification and data-driven computing of phenotypes.

BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable phenotype algorithms to solve these tasks is a challenging problem, caused by various reasons. Firstly, the term 'phenotype' has no generally agreed definition and its meaning depends on context. Secondly, the phenotypes are most commonly specified as non-computable descriptive documents. Recent attempts have shown that ontologies are a suitable way to handle phenotypes and that they can support clinical research and decision making. The SMITH Consortium is dedicated to rapidly establish an integrative medical informatics framework to provide physicians with the best available data and knowledge and enable innovative use of healthcare data for research and treatment optimisation. In the context of a methodological use case 'phenotype pipeline' (PheP), a technology to automatically generate phenotype classifications and annotations based on electronic health records (EHR) is developed. A large series of phenotype algorithms will be implemented. This implies that for each algorithm a classification scheme and its input variables have to be defined. Furthermore, a phenotype engine is required to evaluate and execute developed algorithms. RESULTS: In this article, we present a Core Ontology of Phenotypes (COP) and the software Phenotype Manager (PhenoMan), which implements a novel ontology-based method to model, classify and compute phenotypes from already available data. Our solution includes an enhanced iterative reasoning process combining classification tasks with mathematical calculations at runtime. The ontology as well as the reasoning method were successfully evaluated with selected phenotypes including SOFA score, socio-economic status, body surface area and WHO BMI classification based on available medical data. CONCLUSIONS: We developed a novel ontology-based method to model phenotypes of living beings with the aim of automated phenotype reasoning based on available data. This new approach can be used in clinical context, e.g., for supporting the diagnostic process, evaluating risk factors, and recruiting appropriate participants for clinical and epidemiological studies.

A Comprehensive Cohort Analysis Comparing Growth and GH Therapy Response in IGF1R Mutation Carriers and SGA Children.

CONTEXT: IGF1 receptor mutations (IGF1RM) are rare; however, patients exhibit pronounced growth retardation without catch-up. Although several case reports exist, a comprehensive statistical analysis investigating growth profile and benefit of recombinant human growth hormone (rhGH) treatment is still missing. OBJECTIVE AND METHODS: Here, we compared IGF1RM carriers (n = 23) retrospectively regarding birth parameters, growth response to rhGH therapy, near final height, and glucose/insulin homeostasis to treated children born small for gestational age (SGA) (n = 34). Additionally, health profiles of adult IGF1RM carriers were surveyed by a questionnaire. RESULTS: IGF1RM carriers were significantly smaller at rhGH initiation and had a diminished first-year response compared to SGA children (Δ height standard deviation score: 0.29 vs. 0.65), resulting in a lower growth response under therapy. Interestingly, the number of poor therapy responders was three times higher for IGF1RM carriers than for SGA patients (53 % vs. 17 %). However, most IGF1RM good responders showed catch-up growth to the levels of SGA patients. Moreover, we observed no differences in homeostasis model assessment of insulin resistance before treatment, but during treatment insulin resistance was significantly increased in IGF1RM carriers compared to SGA children. Analyses in adult mutation carriers indicated no increased occurrence of comorbidities later in life compared to SGA controls. CONCLUSION: In summary, IGF1RM carriers showed a more pronounced growth retardation and lower response to rhGH therapy compared to non-mutation carriers, with high individual variability. Therefore, a critical reevaluation of success should be performed periodically. In adulthood, we could not observe a significant influence of IGF1RM on metabolism and health of carriers.

Spreadsheet Model Generator (SMOG): A Lightweight Tool for Object-Spreadsheet Mapping.

In the life science domain, experts are usually familiar with spreadsheet software and often use it in their daily work to collect and structure required domain knowledge. The processing and analysis of spreadsheet data is an important task that must be supported by efficient software solutions. A typical application scenario is for example an integration of spreadsheet data (specified or derived) in an ontology to provide reasoning or search. Different converter tools were developed to support a spreadsheet-to-ontology transformation. Such tools allow often only a relatively simple structure of the spreadsheet template or they require complex mapping processes to map the spreadsheet and ontological entities. In many cases, it is impossible to use the existing converter tools because the spreadsheet data must be processed first before the derived data can be integrated into the ontology. In such cases, an efficient and fast development of customized software solutions is of great importance. In this paper, we present a general spreadsheet processing framework to efficiently read and write spreadsheet data. The Spreadsheet Model Generator (SMOG) provides a simple mechanism to automatically generate the Java object model and mappings between object code and spreadsheet entities. Our solution greatly simplifies the implementation of spreadsheet access methods and enables an efficient development of spreadsheet-based applications. The SMOG has already been used successfully in several biomedical projects under real world conditions.

Growth prediction of small for gestational age infants within the first weeks after birth.

ABSTRACT: Being born small for gestational age (SGA) in length is a sign of growth failure due to malnutrition in pregnancy or other serious disorders. In previous publications it was shown that SGA born neonates may experience a compensatory growth spurt (catch-up growth) in infancy and childhood (Olbertz et al. in press). The timing of this growth spurt, however, was not well described. We analyzed longitudinal data of 5,138 SGA infants and children, collected by licensed physicians in Germany and centrally stored in the Database Management System of CrescNet at the University of Leipzig. We confirm that SGA born infants undergo a catch-up in height SDS after birth and up to 2 years of life. 2,712 SGA newborns out of 2,846 showed catch-up in length SDS. The catch-up occurred already during the 4th to 16th postnatal weeks. We analyzed infants who did not show a catch-up within this time period, or even had a loss in height SDS. These infants have a significant lower height SDS throughout the first 5 years after birth and especially in the timeframe of 60th to 64th month after birth (-1.33 mean height SDS in catch-up group, -2.49 in non-catch-up group, p-value < 0.001, CI = [0.827, 1.483]). Even though the medical reasons for the lack of catch-up growth in young SGA infants may not be known, absence of this catch-up within the 4th to 16th postnatal week can be used to early identify SGA infants with high risk of growth failure within the following 5 years.

Growth and Final Height Among Children With Phenylketonuria.

BACKGROUND AND OBJECTIVES: Growth is an important criterion to evaluate health in childhood and adolescence, especially in patients depending on special dietary treatment. Phenylketonuria (PKU) is the most common inherited disease of amino acid metabolism. Patients with PKU depend on a special phenylalanine-restricted diet, low in natural protein. The study aimed to evaluate growth, growth rate, and target height in 224 patients with PKU. METHODS: Retrospective, longitudinal analysis of standardized, yearly measurements of height, weight, and calculated growth rate (SD score [SDS]) of patients with PKU aged 0 to 18 years were conducted by using the national computerized CrescNet database. Inclusion was restricted to patients carried to term with a confirmed diagnosis of PKU or mild hyperphenylalaninemia determined by newborn screening and early treatment initiation. RESULTS: From birth to adulthood, patients with PKU were significantly shorter than healthy German children (height SDS at 18 years: -0.882 ± 0.108, P < .001). They missed their target height by 3 cm by adulthood (women: P = .02) and 5 cm (men: P = .01). In patients receiving casein hydrolysate during childhood, this was more pronounced compared with patients receiving amino acid mixtures (P < .001). Growth rate was significantly reduced during their first 2 years of life and in puberty (growth rate SDS: -1.1 to -0.5 m/year, P < .001 and -0.5; P < .02). CONCLUSIONS: Early diagnosed, treated, and continuously monitored patients with PKU showed reduced height from birth onward. During the last 2 decades, this phenomenon attenuated, probably because of advances in PKU therapy related to protein supplements and special low-protein foods.

Further stabilization and even decrease in the prevalence rates of overweight and obesity in German children and adolescents from 2005 to 2015: a cross-sectional and trend analysis.

OBJECTIVE: Recently several industrialized countries reported a stabilization or even a decrease in childhood overweight and obesity prevalence rates. In Germany, this trend started in 2004. The present study therefore aimed to evaluate whether this trend has continued or even leads in a clear direction. Design/Setting/Subjects BMI (>90th percentile (overweight), >97th percentile (obesity)) from the CrescNet database was analysed in 326 834 children and adolescents according to three age groups (4-7·99, 8-11·99 and 12-16 years), gender and between time points (2005-2015). RESULTS: Trend analysis from 2005 to 2010 demonstrated that the prevalence of overweight and obesity decreased significantly in boys and girls in the entire group (4-16 years) and in 4-7·99-year-olds. From 2010 to 2015 there was a significant decrease in boys for overweight and obesity in the entire group and for overweight among 8-11·99-year-olds. Within the cross-sectional analysis, prevalence rates for overweight decreased significantly for both genders in the age groups of 4-7·99 and 8-11·99 years (2005 v. 2015). For obesity, prevalence rates showed a significant decrease for boys (2005 v. 2015) and girls (2005 v. 2010) in 4-7·99-year-olds. CONCLUSIONS: We observed a further stabilization of overweight and obesity prevalence rates for all age groups and even a decrease in the rates for the younger ages (4-7·99 years, 8-11·99 years). As other industrialized countries have also reported similar trends, it seems that the epidemic of childhood overweight and obesity is reaching a turning point in the industrial part of the world.

Light-Weighted Automatic Import of Standardized Ontologies into the Content Management System Drupal.

The amount of ontologies, which are utilizable for widespread domains, is growing steadily. BioPortal alone, embraces over 500 published ontologies with nearly 8 million classes. In contrast, the vast informative content of these ontologies is only directly intelligible by experts. To overcome this deficiency it could be possible to represent ontologies as web portals, which does not require knowledge about ontologies and their semantics, but still carries as much information as possible to the end-user. Furthermore, the conception of a complex web portal is a sophisticated process. Many entities must be analyzed and linked to existing terminologies. Ontologies are a decent solution for gathering and storing this complex data and dependencies. Hence, automated imports of ontologies into web portals could support both mentioned scenarios. The Content Management System (CMS) Drupal 8 is one of many solutions to develop web presentations with less required knowledge about programming languages and it is suitable to represent ontological entities. We developed the Drupal Upper Ontology (DUO), which models concepts of Drupal's architecture, such as nodes, vocabularies and links. DUO can be imported into ontologies to map their entities to Drupal's concepts. Because of Drupal's lack of import capabilities, we implemented the Simple Ontology Loader in Drupal (SOLID), a Drupal 8 module, which allows Drupal administrators to import ontologies based on DUO. Our module generates content in Drupal from existing ontologies and makes it accessible by the general public. Moreover Drupal offers a tagging system which may be amplified with multiple standardized and established terminologies by importing them with SOLID. Our Drupal module shows that ontologies can be used to model content of a CMS and vice versa CMS are suitable to represent ontologies in a user-friendly way. Ontological entities are presented to the user as discrete pages with all appropriate properties, links and tags.