Ontology for heart rate turbulence domain from the conceptual model of SNOMED-CT

HRT assessment reviewed: a systematic review of heart rate turbulence methodology

Heart rate turbulence (HRT) is a biphasic reaction to a ventricular premature contraction (VPC) mainly mediated by the baroreflex. It can be used for risk stratification in different disease patterns. Despite existing standards there is a lot of variation in terms of measuring and calculating HRT, which complicates research and application.

OBJECTIVE

This systematic review outlines and evaluates the methodological spectrum of HRT research, especially filtering criteria, parameter calculation and thresholds.

APPROACH

The analysis includes all research papers written in English that have been published before 12.10.2018, are listed on PubMed and involve calculation of HRT parameter values.

MAIN RESULTS

HRT assessment is still being performed in various ways and important specifications of the methodology are not given in many articles. Nevertheless, some suggestions regarding HRT methodology can be made: a normalised turbulence slope should be used to uncouple the parameter from heart rate and frequency of extrasystoles. Filtering criteria as formerly reviewed in the guidelines should be met and mentioned. The minimal number of VPC snippets (VPCSs) as well as new cut-off values for different risks need to be further evaluated. Most importantly, the exact and complete methodology must be described to ensure reproducibility and comparability.

SIGNIFICANCE

Methodical variation hinders comparability of research and medical application. Our continuing questions help to further standardise the measurement and calculation of HRT and increase its value for medical risk stratification.

An Interoperable System toward Cardiac Risk Stratification from ECG Monitoring

Many indices have been proposed for cardiovascular risk stratification from electrocardiogram signal processing, still with limited use in clinical practice. We created a system integrating the clinical definition of cardiac risk subdomains from ECGs and the use of diverse signal processing techniques. Three subdomains were defined from the joint analysis of the technical and clinical viewpoints. One subdomain was devoted to demographic and clinical data. The other two subdomains were intended to obtain widely defined risk indices from ECG monitoring: a simple-domain (heart rate turbulence (HRT)), and a complex-domain (heart rate variability (HRV)). Data provided by the three subdomains allowed for the generation of alerts with different intensity and nature, as well as for the grouping and scrutinization of patients according to the established processing and risk-thresholding criteria. The implemented system was tested by connecting data from real-world in-hospital electronic health records and ECG monitoring by considering standards for syntactic (HL7 messages) and semantic interoperability (archetypes based on CEN/ISO EN13606 and SNOMED-CT). The system was able to provide risk indices and to generate alerts in the health records to support decision-making. Overall, the system allows for the agile interaction of research and clinical practice in the Holter-ECG-based cardiac risk domain.

The Emergence of Openness in Open-Source Projects: The Case of OpenEhR

The meaning of openness in open source is both intrinsically unstable and dynamic, and tends to fluctuate with time and context. We draw on a very particular open-source project primarily concerned with building rigorous clinical concepts to be used in electronic health records called openEHR. openEHR explains how openness is a concept that is purposely engaged with, and how, in this process of engagement, the very meaning of open matures and evolves within the project. Drawing on rich longitudinal data related to openEHR we theorise the evolving nature of openness and how this idea emerges through two intertwined processes of maturation and metamorphosis. While metamorphosis allows us to trace and interrogate the mutational evolution in openness, maturation analyses the small, careful changes crafted to build a very particular understanding of openness. Metamorphosis is less managed and controlled, whereas maturation is representative of highly precise work carried out in controlled form. Both processes work together in open-source projects and reinforce each other. Our study reveals that openness emerges and evolves in open-source projects where it can be understood to mean rigour; ability to participate; open implementation; and an open process. Our work contributes to a deepening in the theorisation of what it means to be an open-source project. The multiple and co-existing meanings of ‘open’ imply that open-source projects evolve in nonlinear ways where each critical meaning of openness causes a reflective questioning by the community of its continued status and existence.

Using anchors from free text in electronic health records to diagnose postoperative delirium

OBJECTIVES

Postoperative delirium is a common complication after major surgery among the elderly. Despite its potentially serious consequences, the complication often goes undetected and undiagnosed. In order to provide diagnosis support one could potentially exploit the information hidden in free text documents from electronic health records using data-driven clinical decision support tools. However, these tools depend on labeled training data and can be both time consuming and expensive to create.

METHODS

The recent learning with anchors framework resolves this problem by transforming key observations (anchors) into labels. This is a promising framework, but it is heavily reliant on clinicians knowledge for specifying good anchor choices in order to perform well. In this paper we propose a novel method for specifying anchors from free text documents, following an exploratory data analysis approach based on clustering and data visualization techniques. We investigate the use of the new framework as a way to detect postoperative delirium.

RESULTS

By applying the proposed method to medical data gathered from a Norwegian university hospital, we increase the area under the precision-recall curve from 0.51 to 0.96 compared to baselines.

CONCLUSIONS

The proposed approach can be used as a framework for clinical decision support for postoperative delirium.

OWLing Clinical Data Repositories With the Ontology Web Language

Background

The health sciences are based upon information. Clinical information is usually stored and managed by physicians with precarious tools, such as spreadsheets. The biomedical domain is more complex than other domains that have adopted information and communication technologies as pervasive business tools. Moreover, medicine continuously changes its corpus of knowledge because of new discoveries and the rearrangements in the relationships among concepts. This scenario makes it especially difficult to offer good tools to answer the professional needs of researchers and constitutes a barrier that needs innovation to discover useful solutions.

Objective

The objective was to design and implement a framework for the development of clinical data repositories, capable of facing the continuous change in the biomedicine domain and minimizing the technical knowledge required from final users.

Methods

We combined knowledge management tools and methodologies with relational technology. We present an ontology-based approach that is flexible and efficient for dealing with complexity and change, integrated with a solid relational storage and a Web graphical user interface.

Results

Onto Clinical Research Forms (OntoCRF) is a framework for the definition, modeling, and instantiation of data repositories. It does not need any database design or programming. All required information to define a new project is explicitly stated in ontologies. Moreover, the user interface is built automatically on the fly as Web pages, whereas data are stored in a generic repository. This allows for immediate deployment and population of the database as well as instant online availability of any modification.

Conclusions

OntoCRF is a complete framework to build data repositories with a solid relational storage. Driven by ontologies, OntoCRF is more flexible and efficient to deal with complexity and change than traditional systems and does not require very skilled technical people facilitating the engineering of clinical software systems.