The Impact of Intracranial Pressure Telesensors: An Observational Propensity-Matched Control Analysis of Service Demand and Costs

BACKGROUND AND OBJECTIVES

Implantable telemetric intracranial pressure (ICP) sensors (telesensors) enable routine, noninvasive ICP feedback, aiding clinical decision-making and attribution of pressure-related symptoms in patients with cerebrospinal fluid shunt systems. Here, we aim to explore the impact of these devices on service demand and costs in patients with adult hydrocephalus.

METHODS

We performed an observational propensity-matched control study, comparing patients who had an MScio/Sensor Reservoir (Christoph Miethke, GmbH & Co) against those with a nontelemetric reservoir inserted between March 2016 and March 2018. Patients were matched on demographics, diagnosis, shunt-type, and revision status. Service usage was recorded with frequencies of neurosurgical admissions, outpatient clinics, scans, and further surgical procedures in the 2 years before and after shunt insertion.

RESULTS

In total, 136 patients, 73 telesensors, and 63 controls were included in this study (48 matched pairs). Telesensor use led to a significant decrease in neurosurgical inpatient admissions, radiographic encounters, and procedures including ICP monitoring. After multivariate adjustment, the mean cumulative saving after 2 years was £5236 ($6338) in telesensor patients (£5498 on matched pair analysis). On break-even analysis, cost-savings were likely to be achieved within 8 months of clinical use, postimplantation. Telesensor patients also experienced a significant reduction in imaging-associated radiation (4 mSv) over 2 years.

CONCLUSION

The findings of this exploratory study reveal that telesensor implantation is associated with reduced service demand and provides net financial savings from an institutional perspective. Moreover, telesensor patients required fewer appointments, invasive procedures, and had less radiation exposure, indicating an improvement in both their experience and safety.

Ambulatory intracranial pressure in humans: ICP increases during movement between body positions

Introduction

Positional changes in intracranial pressure (ICP) have been described in humans when measured over minutes or hours in a static posture, with ICP higher when lying supine than when sitting or standing upright. However, humans are often ambulant with frequent changes in position self-generated by active movement.

Research question

We explored how ICP changes during movement between body positions.

Material and methods

Sixty-two patients undergoing clinical ICP monitoring were recruited. Patients were relatively well, ambulatory and of mixed age, body habitus and pathology. We instructed patients to move back and forth between sitting and standing or lying and sitting positions at 20 s intervals after an initial 60s at rest. We simultaneously measured body position kinematics from inertial measurement units and ICP from an intraparenchymal probe at 100 Hz.

Results

ICP increased transiently during movements beyond the level expected by body position alone. The amplitude of the increase varied between participants but was on average ∼5 mmHg during sit-to-stand, stand-to-sit and sit-to-lie movements and 10.8 mmHg [95%CI: 9.3,12.4] during lie-to-sit movements. The amplitude increased slightly with age, was greater in males, and increased with median 24-h ICP. For lie-to-sit and sit-to-lie movements, higher BMI was associated with greater mid-movement increase (β = 0.99 [0.78,1.20]; β = 0.49 [0.34,0.64], respectively).

Discussion and conclusion

ICP increases during movement between body positions. The amplitude of the increase in ICP varies with type of movement, age, sex, and BMI. This could be a marker of disturbed ICP dynamics and may be particularly relevant for patients with CSF-diverting shunts in situ.

Common governance model: a way to avoid data segregation between existing trusted research environment

Background

Trusted Research Environments provide a legitimate basis for data access along with a set of technologies to support implementation of the "five-safes" framework for privacy protection. Lack of standard approaches in achieving compliance with the "five-safes" framework results in a diversity of approaches across different TREs. Data access and analysis across multiple TREs has a range of benefits including improved precision of analysis due to larger sample sizes and broader availability of out-of-sample records, particularly in the study of rare conditions. Knowledge of governance approaches used across UK-TREs is limited.

Objective

To document key governance features in major UK-TRE contributing to UK wide analysis and to identify elements that would directly facilitate multi TRE collaborations and federated analysis in future.

Method

We summarised three main characteristics across 15 major UK-based TREs: 1) data access environment; 2) data access requests and disclosure control procedures; and 3) governance models. We undertook case studies of collaborative analyses conducted in more than one TRE. We identified an array of TREs operating on an equivalent level of governance. We further identify commonly governed TREs with architectural considerations for achieving an equivalent level of information security management system standards to facilitate multi TRE functionality and federated analytics.

Results

All 15 UK-TREs allow pooling and analysis of aggregated research outputs only when they have passed human-operated disclosure control checks. Data access requests procedures are unique to each TRE. We also observed a variability in disclosure control procedures across various TREs with no or minimal researcher guidance on best practices for file out request procedures. In 2023, six TREs (40.0%) held ISO 20071 accreditation, while 9 TREs (56.2%) participated in four-nation analyses.

Conclusion

Secure analysis of individual-level data from multiple TREs is possible through existing technical solutions but requires development of a well-established governance framework meeting all stakeholder requirements and addressing public and patient concerns. Formation of a standard model could act as the catalyst for evolution of current TREs governance models to a multi TRE ecosystem within the UK and beyond.

Reference intervals for deconjugated urine metanephrines by Bhattacharya analysis

BACKGROUND

Urine metanephrines are used to screen for phaeochromocytoma or paraganglioma (PPGL). Current reference intervals (RI) derived in healthy individuals are not age or sex-stratified, and lower than in hypertensive patients, leading to high false positive rates. This study aims to determine age and sex-stratified RI from a contingent screening population.

METHODS

Patients with 24-h deconjugated urine metanephrines from 3/6/2010 to 27/8/2022 were included (2936 males, 5285 females), initially by liquid chromatography-electrochemical detection (LC-ECD) then liquid chromatography-tandem mass spectrometry (LC-MS/MS). Bhattacharya analysis was used after log transformation to determine age and sex-stratified RI for metanephrine excretion, normetanephrine excretion, metanephrine/creatinine and normetanephrine/creatinine ratios.

RESULTS

Normetanephrine excretion increases with age (RI: males: 18-<30 years: <3.4 µmol/24 h, 30-<40 years: <3.7 µmol/24 h, 40+ years: <5.3 µmol/24 h; females: 18-<30 years: <2.7 µmol/24 h, 30-<40 years: <3.1 µmol/24 h, 40+ years: <3.7 µmol/24 h), while metanephrine excretion was consistent across adulthood (RI: males: 18+ years: <1.8 µmol/24 h; females: 18+ years: <1.2 µmol/24 h). However, normetanephrine/creatinine and metanephrine/creatinine increase steadily with age after early adulthood, likely due to a decrease in muscle mass, with females having higher normetanephrine/creatinine and metanephrine/creatinine ratios.

CONCLUSIONS

Age and sex-stratified RI were derived for metanephrine excretion, normetanephrine excretion, metanephrine/creatinine and normetanephrine/creatinine ratios. This is expected to reduce false positives while flagging most PPGL.

Artefactually low creatinine by Beckman Coulter enzymatic method due to immunoglobulin M paraprotein interference

An 81-year-old man was admitted to hospital with symptomatic coronavirus disease (COVID-19) infection. He had a background of progressive chronic inflammatory demyelinating polyneuropathy associated with Waldenstrom's macroglobulinaemia. His plasma creatinine on four separate samples was inconceivably low (all ≤13 μmol/L), as measured by a Beckman Coulter enzymatic assay) after being 72 μmol/L 3 months earlier. On further investigation, his serum immunoglobulin M (IgM) was 15.4 g/L and his plasma creatinine measured by Roche enzymatic and Roche Jaffe methods was 62 μmol/L and 64 μmol/L, respectively. This was consistent with results post dilution studies and polyethylene glycol (PEG) precipitation on the Beckman Coulter assay. There was no evidence of similar interference when reviewing creatinine results from 10 other patients with IgM paraproteinaemia who had been tested in our laboratory. Clinicians and laboratorians are reminded that enzymatic creatinine is not free from interferences. IgM paraprotein negative interference of enzymatic creatinine is rare and specific to a patient's IgM and assay combination, but should be considered in patients with an unexplained low enzymatic creatinine result. Useful investigations to identify an interference include dilution studies, PEG precipitation and measuring creatinine on an alternative method such as Jaffe, mass spectrometry or an enzymatic method from a different platform.

Genetic influences on epilepsy outcomes: A whole-exome sequencing and health care records data linkage study

OBJECTIVE

This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes.

METHODS

We linked whole-exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)-derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom.

RESULTS

We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty-six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure-free. There was no significant difference between the outcome groups in terms of the exome-wide and gene-based burden of rare and deleterious genetic variants.

SIGNIFICANCE

We successfully uploaded, annotated, and linked genetic sequence data and NLP-derived seizure frequency data to anonymized health care records in this proof-of-concept study. We did not detect a genetic influence on real-world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes.

The pursuit of approaches to federate data to accelerate Alzheimer's disease and related dementia research: GAAIN, DPUK, and ADDI

There is common consensus that data sharing accelerates science. Data sharing enhances the utility of data and promotes the creation and competition of scientific ideas. Within the Alzheimer's disease and related dementias (ADRD) community, data types and modalities are spread across many organizations, geographies, and governance structures. The ADRD community is not alone in facing these challenges, however, the problem is even more difficult because of the need to share complex biomarker data from centers around the world. Heavy-handed data sharing mandates have, to date, been met with limited success and often outright resistance. Interest in making data Findable, Accessible, Interoperable, and Reusable (FAIR) has often resulted in centralized platforms. However, when data governance and sovereignty structures do not allow the movement of data, other methods, such as federation, must be pursued. Implementation of fully federated data approaches are not without their challenges. The user experience may become more complicated, and federated analysis of unstructured data types remains challenging. Advancement in federated data sharing should be accompanied by improvement in federated learning methodologies so that federated data sharing becomes functionally equivalent to direct access to record level data. In this article, we discuss federated data sharing approaches implemented by three data platforms in the ADRD field: Dementia's Platform UK (DPUK) in 2014, the Global Alzheimer's Association Interactive Network (GAAIN) in 2012, and the Alzheimer's Disease Data Initiative (ADDI) in 2020. We conclude by addressing open questions that the research community needs to solve together.

Research-ready data: the C-Surv data model

Research-ready data (data curated to a defined standard) increase scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following stakeholder consultation, a standard data model (C-Surv) optimised for data discovery, was developed using data from 5 population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. Data preparation times were compared between cohort specific data models and C-Surv.It was concluded that adopting a common data model as a data standard for the discovery and analysis of research cohort data offers multiple benefits.

A population-level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK

ObjectivesUnder section 31 (s.31) of the UK Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm. We examined health vulnerabilities of parents involved in public law care proceedings in the two-year period prior to involvement. ApproachOur study created an anonymised individual-level population-based cohort, with a matched comparison group of parents in Wales who were not subject to care proceedings, matched on age, sex and deprivation. Family court data provided by Cafcass Cymru were linked to population-level healthcare records held within the Secure Anonymised Information Linkage (SAIL) Databank. Demographic characteristics, overall health service use and health profiles of parents of children subject to s.31 care proceedings between 2011 and 2019 were examined. ResultsData were available for 8,821 parents involved in care proceedings between 2011 and 2019, with a comparison group of 32,006 parents. Nearly half (47.6%) of cohort parents resided in the most deprived quintile. Higher levels of healthcare use were found for cohort mothers and fathers compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%). ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Impact of natural selection on global patterns of genetic variation and association with clinical phenotypes at genes involved in SARS-CoV-2 infection

Human genomic diversity has been shaped by both ancient and ongoing challenges from viruses. The current coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a devastating impact on population health. However, genetic diversity and evolutionary forces impacting host genes related to SARS-CoV-2 infection are not well understood. We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (angiotensin converting enzyme 2 [ACE2], transmembrane protease serine 2 [TMPRSS2], dipeptidyl peptidase 4 [DPP4], and lymphocyte antigen 6 complex locus E [LY6E]). We analyzed data from 2,012 ethnically diverse Africans and 15,977 individuals of European and African ancestry with electronic health records and integrated with global data from the 1000 Genomes Project. At ACE2, we identified 41 nonsynonymous variants that were rare in most populations, several of which impact protein function. However, three nonsynonymous variants (rs138390800, rs147311723, and rs145437639) were common among central African hunter-gatherers from Cameroon (minor allele frequency 0.083 to 0.164) and are on haplotypes that exhibit signatures of positive selection. We identify signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage compared with the chimpanzee genome. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19. Our study provides insights into global variation at host genes related to SARS-CoV-2 infection, which have been shaped by natural selection in some populations, possibly due to prior viral infections.

A population level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK between 2011 and 2019

IntroductionUnder section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services. ObjectiveTo examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement. MethodsFamily court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used. ResultsNearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%). ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

A population level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK between 2011 and 2019

Introduction

Under section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services.

Objective

To examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement.

Methods

Family court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used.

Results

Nearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%).

Conclusion

This study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection (ACE2, TMPRSS2, DPP4, and LY6E). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2, we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2, we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Impact of natural selection on global patterns of genetic variation, and association with clinical phenotypes, at genes involved in SARS-CoV-2 infection

We investigated global patterns of genetic variation and signatures of natural selection at host genes relevant to SARS-CoV-2 infection ( ACE2, TMPRSS2, DPP4 , and LY6E ). We analyzed novel data from 2,012 ethnically diverse Africans and 15,997 individuals of European and African ancestry with electronic health records, and integrated with global data from the 1000GP. At ACE2 , we identified 41 non-synonymous variants that were rare in most populations, several of which impact protein function. However, three non-synonymous variants were common among Central African hunter-gatherers from Cameroon and are on haplotypes that exhibit signatures of positive selection. We identify strong signatures of selection impacting variation at regulatory regions influencing ACE2 expression in multiple African populations. At TMPRSS2 , we identified 13 amino acid changes that are adaptive and specific to the human lineage. Genetic variants that are targets of natural selection are associated with clinical phenotypes common in patients with COVID-19.

Markup: A Web-Based Annotation Tool Powered by Active Learning

Across various domains, such as health and social care, law, news, and social media, there are increasing quantities of unstructured texts being produced. These potential data sources often contain rich information that could be used for domain-specific and research purposes. However, the unstructured nature of free-text data poses a significant challenge for its utilisation due to the necessity of substantial manual intervention from domain-experts to label embedded information. Annotation tools can assist with this process by providing functionality that enables the accurate capture and transformation of unstructured texts into structured annotations, which can be used individually, or as part of larger Natural Language Processing (NLP) pipelines. We present Markup (https://www.getmarkup.com/) an open-source, web-based annotation tool that is undergoing continued development for use across all domains. Markup incorporates NLP and Active Learning (AL) technologies to enable rapid and accurate annotation using custom user configurations, predictive annotation suggestions, and automated mapping suggestions to both domain-specific ontologies, such as the Unified Medical Language System (UMLS), and custom, user-defined ontologies. We demonstrate a real-world use case of how Markup has been used in a healthcare setting to annotate structured information from unstructured clinic letters, where captured annotations were used to build and test NLP applications.

Protein-, polymer-, and silica-based luminescent nanomaterial probes for super resolution microscopy: a review

Super resolution microscopy was developed to overcome the Abbe diffraction limit, which effects conventional optical microscopy, in order to study the smaller components of biological systems. In recent years nanomaterials have been explored as luminescent probes for super resolution microscopy, as many have advantages over traditional fluorescent dye molecules. This review will summarize several different types of nanomaterial probes, covering quantum dots, carbon dots, and dye doped nanoparticles. For the purposes of this review the term "nanoparticle" will be limited to polymer-based, protein-based, and silica-based nanoparticles, including core-shell structured nanoparticles. Luminescent nanomaterials have shown promise as super-resolution probes, and continued research in this area will yield new advances in both materials science and biochemical microscopy at the nanometer scale.

Making the Most of Big Data in Plastic Surgery: Improving Outcomes, Protecting Patients, Informing Service Providers

ABSTRACT

In medicine, "big data" refers to the interdisciplinary analysis of high-volume, diverse clinical and lifestyle information on large patient populations. Recent advancements in data storage and electronic record keeping have enabled the expansion of research in this field. In the United Kingdom, Big data has been highlighted as one of the government's "8 Great Technologies," and the Medical Research Council has invested more than £100 million since 2012 in developing the Health Data Research UK infrastructure. The recent Royal College of Surgeons Commission of the Future of Surgery concluded that analysis of big data is one of the 4 most likely avenues to bring some of the most innovative changes to surgical practice in the 21st century.In this article, we provide an overview of the nascent field of big data analytics in plastic and highlight how it has the potential to improve outcomes, increase safety, and aid service planning.We outline the current resources available, the emerging role of big data within the subspecialties of burns, microsurgery, skin and breast cancer, and how these data can be used. We critically review the limitations and considerations raised with big data, offer suggestions regarding database optimization, and suggest future directions for research in this exciting field.

Effect of cognitive load on drivers' State and task performance during automated driving: Introducing a novel method for determining stabilisation time following take-over of control

This research paper explores the impact of cognitive load on drivers' physiological state and driving performance during an automated driving to manual control transition scenario, using a driving simulator. Whilst driving in the automated mode, cognitive load was manipulated using the "N-Back" task, which participants engaged with via a visual display. Results suggest that non-optimal levels of workload during the automated driving conditions impair driving performance, especially lateral control of the vehicle, and the magnitude of this impairment varied with increasing cognitive load. In addition to these findings, the present paper introduces a novel method for determining stabilisation times of both driver state and driving performance indicators following a transition of vehicle control. Using this method we demonstrate that mean and standard deviation of lane position impairments were found to take longer to stabilise following transition to manual driving following a higher level of cognitive load during the automated driving period, taking up to 22 s for driving performance to normalise after take-over. In addition, heart rate parameters take between 20 and 30 s to stabilise following a planned take-over request. Finally, this paper demonstrates how the magnitude of cognitive load can be estimated in context of automated driving using physiological measures, captured by consumer electronic devices. We discuss the impact our findings have on the design of SAE Level 3 systems. Relevant suggestions are provided to the research community and automakers working on future implementation of vehicles capable of conditional automation.

Markup: A Web-Based Clinical Annotation Tool with Enhanced Ontology Mapping

IntroductionUnstructured free-text clinical notes often contain valuable information relating to patient symptoms, prescriptions and diagnoses. These can assist with better care for patients and novel healthcare research if transformed into accessible, structured clinical text. In particular, Natural Language Processing (NLP) algorithms can produce such structured outputs, but require gold standard data to train and validate their accuracy. While existing tools such as Brat and Webanno provide interfaces to manually annotate text, there is a lack of capability to efficiently annotate complex clinical information. Objectives and ApproachWe present Markup, an open-source, web-based annotation tool developed for use within clinical contexts by domain experts to produce gold standard annotations for NLP development. Markup incorporates NLP and Active Learning technologies to enable rapid and accurate annotation of unstructured documents. Markup supports custom user configurations, automated annotation suggestions, and automated mapping to existing clinical ontologies such as the Unified Medical Language System (UMLS), the Systematized Nomenclature of Medicine - Clinical Terms (SNOMED-CT), or custom, user-defined ontologies. ResultsMarkup has been tested on Epilepsy clinic letters, where captured annotations were used to build and test NLP applications. Markup allowed for inter-annotator statistics to be calculated in the case of multiple annotators. Re-annotation, following iterations of annotation definitions, was incorporated for flexibility. UMLS codes, certainty context, and multiple components from complex phrases were all able to be captured and exported in a structured format. Conclusions / ImplicationsMarkup allows gold standard annotations to be collected efficiently across unstructured text and is optimized to capture health-specific information. These annotations are important to develop and validate NLP algorithms that automate the capture of important information from clinic letters at scale.

British Columbia’s Health Data Platform: Unleashing the Power of a Data Environment Commons for Health and Health System Improvement

IntroductionThere is no power for change greater than a community discovering what it cares about.1 The Health Data Platform (HDP) will democratize British Columbia’s (population of approximately 4.6 million) health sector data by creating common enabling infrastructure that supports cross-organization analytics and research used by both decision makers and cademics. HDP will provide streamlined, proportionate processes that provide timelier access to data with increased transparency for the data consumer and provide shared data related services that elevate best practices by enabling consistency across data contributors, while maintaining continued stewardship of their data. HDP will be built in collaboration with Swansea University following an agile pragmatic approach starting with a minimum viable product. Objectives and ApproachBuild a data sharing environment that harnesses the data and the understanding and expertise about health data across academe, decision makers, and clinicians in the province by: Enabling a common harmonized approach across the sector on: Data stewardship Data access Data security and privacy Data management Data standards To: Enhance data consumer data access experience Increase process consistency and transparency Reduce burden of liberating data from a data source Build trust in the data and what it is telling us and therefore the decisions made Increase data accessibility safely and responsibly Working within the jurisdiction’s existing legislation, the Five Safes Privacy and Security Framework will be implemented, tailored to address the requirements of data contributors. ResultsThe minimum viable product will provide the necessary enabling infrastructure including governance to enable timelier access, safely to administrative data to a limited set of data consumers. The MVP will be expanded with another release planned for early 2021. Conclusion / ImplicationsCollaboration with Swansea University has enabled BC to accelerate its journey to increasing timelier access to data, safely and increasing the maturity of analytics by creating the enabling infrastructure that promotes collaboration and sharing of data and data approaches. 1 Margaret Wheatley

Creating A Research Ready Data Asset and Empowering Dynamic and Efficient Research: The Sail Dementia E-Cohort (SDEC)

IntroductionResearch can often be slow to start and require duplication of effort which in lots of cases has previously been completed to generate research-ready-data-assets (RRDA). Within the UK, two programmes: Dementias Platform UK (DPUK) that brings together over 50 different dementia-related cohorts and Secure Anonymised Information Linkage (SAIL) Databank, which provides access to longitudinal population-scale person-level data for every person in Wales have tried to tackle this challenge of creation, use and management of RRDA’s. Objectives and ApproachCombining clinical, data and management expertise from DPUK and SAIL, we hoped to construct a RRDA that was easily accessible and well described for a dementia e-cohort. Welsh residents with available primary care records were included, with clinical and demographic information including follow-up times, several dementia indicators using validated diagnostic code lists, information on every dementia-related diagnostic event and several covariates and co-morbidities. SDeC was made available to researchers and can be modified according to appropriate study designs, with learning from projects used to update the SDeC to improve future uses. Interactive visualisations effectively summarise cohort characteristics, aiding researchers to quickly determine cohort eligibility for dementia studies. ResultsSDeC contains data from 4.6 million participants in SAIL, with 1.5 million meeting cohort inclusion criteria, resulting in 24.3 million person-years of follow-up. Of these, 146,323 (10%) developed all-cause dementia during follow-up, with 90,150 (60%) having dementia subtype codes. We made this resource available to researchers who had never used SAIL before, with limited experience of population-scale routine-data, and projects have proceeded with one managing to proceed from point of initial access to submission of publication in less than 6-months. Conclusion / ImplicationsSDeC provides a reproducible dynamic method for completing dementia research, and expediting learning and understanding of the use of these data, with further developments and maintenance planned to increase the complexity and detail available to researchers over time.

Understanding and responding to COVID-19 in Wales: protocol for a privacy-protecting data platform for enhanced epidemiology and evaluation of interventions

INTRODUCTION

The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions.

METHODS AND ANALYSIS

Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection.

ETHICS AND DISSEMINATION

The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals.

IFCC Interim Guidelines on Biochemical/Hematological Monitoring of COVID-19 Patients

Routine biochemical and hematological tests have been reported to be useful in the stratification and prognostication of pediatric and adult patients with diagnosed coronavirus disease (COVID-19), correlating with poor outcomes such as the need for mechanical ventilation or intensive care, progression to multisystem organ failure, and/or death. While these tests are already well established in most clinical laboratories, there is still debate regarding their clinical value in the management of COVID-19, particularly in pediatrics, as well as the value of composite clinical risk scores in COVID-19 prognostication. This document by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Task Force on COVID-19 provides interim guidance on: (A) clinical indications for testing, (B) recommendations for test selection and interpretation, (C) considerations in test interpretation, and (D) current limitations of biochemical/hematological monitoring of COVID-19 patients. These evidence-based recommendations will provide practical guidance to clinical laboratories worldwide, underscoring the contribution of biochemical and hematological testing to our collective pandemic response.

Adult cavernous haemangioma of the vocal cords with a unique presentation of acute respiratory distress: a case report

Laryngeal haemangiomas can commonly be seen in children, and first-line treatment is usually propranolol. However, in adults, cavernous haemangioma of the vocal cord(s) is an extremely rare condition - with this being the only published adult case presenting with acute respiratory distress - the mainstay of treatment is surgical excision under microlaryngoscopy. Presentation in adults can be unpredictable, but primarily consists of hoarseness which can be associated with, dyspnoea, dysphagia, and haemoptysis - and in one documented case stenosis of the aero-digestive tract led to death. Due to these airway difficulties, surgery can often prove challenging. In this study, we explore the unusual case of a previously well 71-year-old gentleman presenting to the Emergency Department, with worsening shortness of breath as his primary complaint. Uniquely, in this case, an awake fibre-optic intubation was undertaken to manage the difficult airway and a microlaryngoscopy was performed. A 20x10x15mm lesion was excised, which had characteristics in keeping with a cavernous haemangioma on microscopic examination.

Data Resource: population level family justice administrative data with opportunities for data linkage

INTRODUCTION

Although there has been considerable progress in the use of administrative data for applied health research, the family justice field lags behind. Better use of administrative data are essential to enhance understanding of how the family justice system is working, as well as the characteristics of, and outcomes for, children and families. The Family Justice Data Partnership (FJDP) supports this aim through analyses of core family justice and linked datasets in the SAIL Databank (Secure Anonymised Information Linkage). Cafcass Cymru provide expert advice for children involved in family court proceedings in Wales, ensuring decisions are made in the best interests of the child. We provide an overview of Cafcass Cymru data. We also describe and illustrate linkage to administrative datasets within SAIL.

METHODS

Cafcass Cymru data was transferred to SAIL using a standardised approach to provide de-identified data with Anonymised Linking Fields (ALF) for successfully matched records. Three cohorts were created: all individuals involved in family court applications; all individuals with an ALF allowing subsequent health data linkage; and all individuals with a Residential Anonymised Linking Field (RALF) enabling area-level deprivation analysis.

RESULTS

Cafcass Cymru application data are available for child protection matters (public law, range 2011-2019, n=12,745), and child arrangement disputes (private law, range 2005-2019, n=52,023). An 80% data linkage match rate was achieved. 40% had hospital admissions within two years pre or post application; 54% had emergency department attendances and 61% had outpatient appointments. Individuals were more likely to reside in deprived areas regardless of law type.

CONCLUSION

Cafcass Cymru data can be accessed through the SAIL Databank. The FJDP will continue to enhance research opportunities for all to better understand the family justice system, and outcomes for those involved, such as health and wellbeing for children and family members.

The Dementias Platform UK (DPUK) Data Portal

The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure 'lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee.

Breaking the cycle of frustration: Applying Neisser's Perceptual Cycle Model to drivers of semi-autonomous vehicles

Semi-autonomous cars are already on the road and highly autonomous cars will soon be with us. Little is understood about how drivers will adapt to the changing relationship with their vehicle, but to ensure safety and consumer acceptance, this insight is vital. To this end, an on-road study in a semi-autonomous vehicle was undertaken with six UK drivers. The 'think aloud' technique was employed and video and audio footage of their interaction with the vehicle was captured. Neisser's (1976) Perceptual Cycle Model (PCM) was used to analyse the data and three case studies are presented to highlight how poor synergy between driver and semi-autonomous vehicles can occur from the lens of Schema, Action or World information. Seven key design considerations are proposed to ensure a more positive and safer interaction between driver and autonomous vehicle to guide focus by manufacturers. Further evidence for the existence of a 'counter cycle' (Plant and Stanton, 2015) within the PCM is found and how this relates to the challenges of using verbal protocals expressed during a fast moving dynamic task is discussed.