The identification and validity of congenital malformation diagnoses in UK electronic health records: A systematic review

PURPOSE: To describe the methods used to identify and validate congenital malformation diagnoses recorded in UK electronic health records, and the results of validation studies. METHODS: Medline and Embase were searched for publications between 1987 and 2019 that involved identifying congenital malformations from UK electronic health records using diagnostic codes. The methods and code-lists used to identify congenital malformations, and the methods and results of validations, were examined. RESULTS: We retrieved 54 eligible studies; 36 identified congenital malformations from primary care data and 18 from secondary care data alone or in combination with birth and/or death records. Identification in secondary care data relied on codes from the 'Q' chapter for congenital malformations in ICD-10. In contrast, studies using primary care data frequently used additional codes outside of the 'P' chapter for congenital malformation diagnoses in Read, although the exact codes used were not always clear. Eight studies validated diagnoses identified in primary care data. The positive predictive value was highest (80-100%) for congenital malformations overall, major malformations, and heart defects although the validity of the reference standard used was often uncertain. It was lowest for neural tube defects (71%) and developmental hip dysplasia (56%). CONCLUSIONS: Studies identifying congenital malformations from primary care data provided limited details about the methods used. The few validation studies were limited to diagnoses recorded in primary care. Further assessments of all measures of validity in both data sources and of other malformation subgroups are needed, using robust reference standards and adhering to reporting guidelines. This article is protected by copyright. All rights reserved

Dissociating anticipation from perception: Acute pain activates default mode network.

Few studies have explored the effect of acute pain on attentional networks and on the default mode network. Moreover, these studies convey conflicting results, seemingly caused by design. To reassess this issue, we studied 20 healthy subjects with functional magnetic resonance imaging while delivering painful electric shocks. The design was purposely constructed to separate rest, anticipation, and pain perception. We found that default mode network activity in response to pain was biphasic. It deactivated during anticipation when the dorsal attentional network was activated. During pain perception, the default mode network was activated, as were attentional networks. The left posterior fusiform gyrus showed the same dynamics as the default mode network, and its activity was negatively correlated to the subject\u27s pain intensity rating. The associative pregenual anterior cingulate cortex seemed to play a key role in these coactivations. These results concur with data from the literature showing that enhanced pain perception results in greater default mode network activity and that the anticorrelation between the default mode network and the dorsal attentional network disappears in chronic pain patients

PWSHAP: A Path-Wise Explanation Model for Targeted Variables

Predictive black-box models can exhibit high-accuracy but their opaque nature hinders their uptake in safety-critical deployment environments. Explanation methods (XAI) can provide confidence for decision-making through increased transparency. However, existing XAI methods are not tailored towards models in sensitive domains where one predictor is of special interest, such as a treatment effect in a clinical model, or ethnicity in policy models. We introduce Path-Wise Shapley effects (PWSHAP), a framework for assessing the targeted effect of a binary (e.g. treatment) variable from a complex outcome model. Our approach augments the predictive model with a user-defined directed acyclic graph (DAG). The method then uses the graph alongside on-manifold Shapley values to identify effects along causal pathways whilst maintaining robustness to adversarial attacks. We establish error bounds for the identified path-wise Shapley effects and for Shapley values. We show PWSHAP can perform local bias and mediation analyses with faithfulness to the model. Further, if the targeted variable is randomised we can quantify local effect modification. We demonstrate the resolution, interpretability and true locality of our approach on examples and a real-world experiment

Functional MRI comparison of passive and active movement: possible inhibitory role of supplementary motor area:

Recent studies have hypothesized that the supplementary motor area plays a role in motor inhibition. To study this possible role, we used functional MRI study to compare conditions, which require various level of inhibition of motor patterns. Seventeen healthy participants were scanned while executing – actively or passively – rhythmic opening/closing movements of their right hand, with and without congruent visual information. The contrast passive>active movement in the visual guidance condition which requires inhibition in order ‘not’ to perform the movement, yields to significant activation of areas commonly involved in the inhibitory brain circuitry among which, notably, controlateral supplementary motor area

Diabetes Mellitus in a Patient With Lafora Disease: Possible Links With Pancreatic β-Cell Dysfunction and Insulin Resistance

Lafora disease (LD) is a rare autosomal recessive disorder characterized by progressive myoclonic epilepsy followed by continuous neurological decline, culminating in death within 10 years. LD leads to accumulation of insoluble, abnormal, glycogen–like structures called Lafora bodies (LBs). It is caused by mutations in the gene encoding glycogen phosphatase (EPM2A) or the E3 ubiquitin ligase malin (EPM2B/NHLRC1). These two proteins are involved in an intricate, however, incompletely elucidated pathway governing glycogen metabolism. The formation of EPM2A and malin signaling complex promotes the ubiquitination of proteins participating in glycogen metabolism, where dysfunctional mutations lead to the formation of LBs. Herein, we describe a 13-years-old child with LD due to a NHLRC1 (c.386C > A, p.Pro129His) mutation, who has developed diabetes mellitus and was treated with metformin. We discuss how basic mechanisms of LD could be linked to β-cell dysfunction and insulin resistance

A genomewide scan for Attention-Deficit/Hyperactivity Disorder in an extended sample: Suggestive linkage on 17p11

Attention-deficit/hyperactivity disorder (ADHD [MIM 143465]) is a common, highly heritable neurobehavioral disorder of childhood onset, characterized by hyperactivity, impulsivity, and/or inattention. As part of an ongoing study of the genetic etiology of ADHD, we have performed a genomewide linkage scan in 204 nuclear families comprising 853 individuals and 270 affected sibling pairs (ASPs). Previously, we reported genomewide linkage analysis of a “first wave” of these families composed of 126 ASPs. A follow-up investigation of one region on 16p yielded significant linkage in an extended sample. The current study extends the original sample of 126 ASPs to 270 ASPs and provides linkage analyses of the entire sample, using polymorphic microsatellite markers that define an ∼10-cM map across the genome. Maximum LOD score (MLS) analysis identified suggestive linkage for 17p11 (MLS=2.98) and four nominal regions with MLS values >1.0, including 5p13, 6q14, 11q25, and 20q13. These data, taken together with the fine mapping on 16p13, suggest two regions as highly likely to harbor risk genes for ADHD: 16p13 and 17p11. Interestingly, both regions, as well as 5p13, have been highlighted in genomewide scans for autism

Roles for Treg expansion and HMGB1 signaling through the TLR1-2-6 axis in determining the magnitude of the antigen-specific immune response to MVA85A

© 2013 Matsumiya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedA better understanding of the relationships between vaccine, immunogenicity and protection from disease would greatly facilitate vaccine development. Modified vaccinia virus Ankara expressing antigen 85A (MVA85A) is a novel tuberculosis vaccine candidate designed to enhance responses induced by BCG. Antigen-specific interferon-γ (IFN-γ) production is greatly enhanced by MVA85A, however the variability between healthy individuals is extensive. In this study we have sought to characterize the early changes in gene expression in humans following vaccination with MVA85A and relate these to long-term immunogenicity. Two days post-vaccination, MVA85A induces a strong interferon and inflammatory response. Separating volunteers into high and low responders on the basis of T cell responses to 85A peptides measured during the trial, an expansion of circulating CD4+ CD25+ Foxp3+ cells is seen in low but not high responders. Additionally, high levels of Toll-like Receptor (TLR) 1 on day of vaccination are associated with an increased response to antigen 85A. In a classification model, combined expression levels of TLR1, TICAM2 and CD14 on day of vaccination and CTLA4 and IL2Rα two days post-vaccination can classify high and low responders with over 80% accuracy. Furthermore, administering MVA85A in mice with anti-TLR2 antibodies may abrogate high responses, and neutralising antibodies to TLRs 1, 2 or 6 or HMGB1 decrease CXCL2 production during in vitro stimulation with MVA85A. HMGB1 is released into the supernatant following atimulation with MVA85A and we propose this signal may be the trigger activating the TLR pathway. This study suggests an important role for an endogenous ligand in innate sensing of MVA and demonstrates the importance of pattern recognition receptors and regulatory T cell responses in determining the magnitude of the antigen specific immune response to vaccination with MVA85A in humans.This work was funded by the Wellcome Trust. MM has a Wellcome Trust PhD studentship and HM is a Wellcome Trust Senior Fello

Acanthamoeba keratitis: confirmation of the UK outbreak and a prospective case control study identifying contributing risk factors

BACKGROUND/AIMS: Acanthamoeba keratitis (AK) is a chronic debilitating corneal infection principally affecting contact lens (CL) users. Studies were designed to test claims that the UK incidence may have increased in 2012–2014 and to evaluate potential causes. METHODS: Annualised incidence data were collected from January 1984 to December 2016. Case-control study subjects were recruited between 14 April 2011 and 05 June 2017. Reusable CL users with AK were recruited retrospectively and prospectively. Controls were reusable CL users, recruited prospectively, with any disorder other than AK. Multivariable analysis of questionnaire data measured independent risk factors for AK. RESULTS: The current outbreak of AK started in 2010–2011 with an incidence threefold higher than in 2004–2009. Risk factors for AK were: Oxipol disinfection, CLs made of group IV CL materials, poor CL hygiene, deficient hand hygiene, use of CLs while swimming or bathing, being white British, and for those in social classes 4–9. CONCLUSION: AK is a largely preventable disease. The current outbreak is unlikely to be due to any one of the identified risk factors in isolation. Improving CL and hand hygiene, avoiding CLs contamination with water and use of effective CL disinfection solutions, or daily disposable CLs, will reduce the incidence of AK. In the longer-term, water avoidance publicity for CL users can be expected to reduce the incidence further. Ongoing surveillance of AK numbers will identify changes in incidence earlier. Evaluation of Acanthamoeba contamination in end-user drinking water would contribute to our understanding of regional variations in the risk of exposure

The presupplementary area within the language network: a resting state functional magnetic resonance imaging functional connectivity analysis

The presupplementary motor area (pre-SMA) is involved in volitional selection. Despite the lateralization of the language network and different functions for both pre-SMA, few studies have reported the lateralization of pre-SMA activity and very little is known about the possible lateralization of pre-SMA connectivity. Via functional connectivity analysis, we sought to understand how the language network may be connected to other intrinsic connectivity networks (ICNs) through the pre-SMA. We performed a spatial independent component analysis of resting state functional magnetic resonance imaging in 30 volunteers to identify the language network. Subsequently, we applied seed-to-voxel functional connectivity analyses centered on peaks detected in the pre-SMA. Three signal peaks were detected in the pre-SMA. The left rostral pre-SMA intrinsic connectivity network (LR ICN) was left lateralized in contrast to bilateral ICNs associated to right pre-SMA peaks. The LR ICN was anticorrelated with the dorsal attention network and the right caudal pre-SMA ICN (RC ICN) anticorrelated with the default mode network. These two ICNs overlapped minimally. In contrast, the right rostral ICN overlapped the LR ICN. Both right ICNs overlapped in the ventral attention network (vATT). The bilateral connectivity of the right rostral pre-SMA may allow right hemispheric recruitment to process semantic ambiguities. Overlap between the right pre-SMA ICNs in vATT may contribute to internal thought to external environment reorientation. Distinct ICNs connected to areas involved in lexico-syntactic selection and phonology converge in the pre-SMA, which may constitute the resolution space of competing condition-action associations for speech production

Healthcare resource utilisation and mortality outcomes in international migrants to the UK: analysis protocol for a linked population-based cohort study using Clinical Practice Research Datalink (CPRD), Hospital Episode Statistics (HES) and the Office for National Statistics (ONS) [version 2; peer review: 1 approved with reservations, 1 not approved]

An estimated 14.2% (9.34 million people) of people living in the UK in 2019 were international migrants. Despite this, there are no large-scale national studies of their healthcare resource utilisation and little is known about how migrants access and use healthcare services. One ongoing study of migration health in the UK, the Million Migrants study, links electronic health records (EHRs) from hospital-based data, national death records and Public Health England migrant and refugee data. However, the Million Migrants study cannot provide a complete picture of migration health resource utilisation as it lacks data on migrants from Europe and utilisation of primary care for all international migrants. Our study seeks to address this limitation by using primary care EHR data linked to hospital-based EHRs and national death records.  Our study is split into a feasibility study and a main study. The feasibility study will assess the validity of a migration phenotype, a transparent reproducible algorithm using clinical terminology codes to determine migration status in Clinical Practice Research Datalink (CPRD), the largest UK primary care EHR. If the migration phenotype is found to be valid, the main study will involve using the phenotype in the linked dataset to describe primary care and hospital-based healthcare resource utilisation and mortality in migrants compared to non-migrants. All outcomes will be explored according to sub-conditions identified as research priorities through patient and public involvement, including preventable causes of inpatient admission, sexual and reproductive health conditions/interventions and mental health conditions. The results will generate evidence to inform policies that aim to improve migration health and universal health coverage