UK Haemoglobin Disorders Peer Review: A Quality Standards-based review programme for sickle cell disease and thalassaemia

We evaluated the impact of peer reviews in driving improvement in healthcare quality for people with haemoglobinopathy in the United Kingdom. We analysed compliance to four Quality Standards (QS)-based peer reviews from 2010 to 2020 to evaluate its impact in driving healthcare quality. Seventeen paediatric and 29 adult haemoglobinopathy centres were reviewed in 2010/11 and 2012/13 respectively; 33 paediatric and 33 adult centres were reviewed in 2014/16, and 32 paediatric and 32 adult centres were reviewed in 2018/2020. Compliance with QS and participant feedback were analysed to assess the impact of peer review programmes to drive improvement in quality of care. We noted that haemoglobinopathy centres significantly improved their compliance to QS between the first two review programmes, but not in the final review programme. In comparison to other disease-group reviews, the haemoglobinopathy departments were less able to address critical peer review recommendations in their own institutions. The peer review programme was unable to drive sustained improvement in healthcare quality, underscoring the need for sustained development and support for haemoglobinopathy services in the National Health Service. Further work is needed to understand why disparities exist among peer review-driven improvement initiatives within different disease groups.

Pharmacokinetics of oral tapentadol in cats

To evaluate pharmacokinetics of one dose of tapentadol hydrochloride orally administered to cats. Prospective experimental study. Five healthy adult mixed-breed cats. Each cat received 18.8 ± 1.0 mg/kg tapentadol orally. Venous blood samples were collected at time 0 (immediately prior to administration of tapentadol) 1, 2, 5, 10, 15, 30, 45, 60, 90 min, and 2, 4, 8, 12 to 24 h after drug administration. Plasma tapentadol concentrations and its metabolites were determined using ultra-performance liquid chromatography-tandem mass spectrometry. Geometric mean Tmax of tapentadol, desmethyltapentadol, tapentadol-O-glucuronide, and tapentadol-O-sulfate was 2.3, 7.0, 6.0, and 4.6 h, respectively. Mean Cmax of tapentadol, desmethyltapentadol, tapentadol-O-glucuronide, and tapentadol-O-sulfate was 637, 66, 1134, and 15,757 ng/mL, respectively, after administration. Mean half-life of tapentadol, desmethyltapentadol, tapentadol-O-glucuronide, and tapentadol-O-sulfate was 2.4, 4.7, 2.9, and 10.8 h. The relative exposure of tapentadol and its metabolites were tapentadol 2.65%, desmethyltapentadol 0.54%, tapentadol-O-glucuronide 6.22%, and tapentadol-O-sulfate 90.6%. Tapentadol-O-sulfate was the predominant metabolite following the administration of oral tapentadol in cats. Further studies are warranted to evaluate the association of analgesia with plasma concentrations of tapentadol.

Biliary Enterocytozoon bieneusi infection in a dog under immunomodulatory therapy

An 8-year-old female spayed Labrador retriever was presented for the evaluation of severe weight loss 10 weeks after starting an immunomodulatory treatment, including prednisolone and cyclosporine, for meningoencephalitis of unknown origin. Plasma biochemistry analysis showed mild to moderate increases in liver enzyme activities and a moderate decrease in urea concentration. Abdominal ultrasound revealed mild hepatomegaly and a large gall bladder with unremarkable wall and content. Cholecystocentesis was performed and bile was examined both cytologically and by molecular methods, which revealed the presence of Enterocytozoon bieneusi. Treatment was initiated with albendazole but was discontinued due to the development of severe neutropenia. The medical management was subsequently changed to fenbendazole and the dog made a complete recovery. This report describes the first case of clinical manifestation and successful treatment of biliary E. bieneusi infection in a dog.

Medication adherence assessment and reporting in cardiovascular randomised controlled trials

Background

Despite the knowledge that suboptimal adherence to medications may have an impact on the impact of treatment interventions, the assessment and reporting of medication adherence in cardiovascular randomised controlled trials has not been well studied. In this review we sought to study the differences in medication adherence assessment and reporting in cardiovascular randomised controlled trials (RCTs) comparing interventional procedures to medical therapy alone in four major cardiovascular conditions: coronary disease (CAD), atrial fibrillation (AF), heart failure (HF) and hypertension (HTN).

Methods

Comprehensive searches of PUBMED/MEDLINE, Clinicaltrials.gov and Cochrane Central Register of Controlled Trials (CENTRAL) were performed. Two independent authors screened and extracted general study data, adherence assessment methodology and adherence reporting characteristics from eligible RCTs.

Results

A total of 568 studies (257 HTN, 120 HF, 116 CAD and 75 AF RCTs) published between 2014–2019 were included in the review. Overall, only 44.7% of RCTs assessed adherence, 14.1% defined “good” adherence and 21.1% reported adherence results. HTN and CAD trials performed significantly better than HF and AF studies in all three parameters. Compared to drug trials, procedural trials were significantly less likely to assess adherence (21.1% vs 45.7%, p<0.001), define good adherence (7% vs 15.5%, p<0.001) or report adherence results (10.5% vs 21.3%, p=0.046). Adherence assessment practices were further significantly influenced by funding, placebo status and study outcome. Pill count/return of packaging was the most utilised method (49.5%) and direct observation the least utilised (1.1%). Adherence was calculated in 55.9% of RCTs with studies using different formulas and setting different thresholds for “good” adherence but most setting this at 80% adherence. Adherence reporting practices also varied significantly between RCTs. Most studies (53%) that assessed adherence, did not in fact report their results.

Conclusion

Our findings expose significant inconsistencies in adherence assessment and reporting practices amongst cardiovascular RCTs. This is a systemic problem with important implications on research quality and reliability. We therefore recommend the incorporation of mandatory adherence assessment and reporting into international reporting guidelines for RCTs such as the CONSORT statement. We also propose a grading system which once validated may be used to appraise standards of adherence assessment and reporting in RCTs.

Funding Acknowledgement

Type of funding sources: None.

Machine learning can accurately detect abnormal aortic valves in CMR

Background

Improving the efficiency of CMR by acquiring fewer, and more targeted sequences, would improve the diagnostic yield and reduce patient recalls. An AI-assisted clinical decision support system (CDSS) could deliver this efficiency using adaptive scanning protocols which replicate the expertise of highly trained clinicians. Normal aortic valve anatomy on the three-chamber (3CH) cine CMR is a guide to rationalising subsequent sequences, and therefore is a suitable base case for developing an AI-CDSS for CMR.

Purpose

We propose a machine learning approach to differentiate between normal and abnormal aortic valves from the 3CH cine.

Methods

We curated a unique expert-annotated dataset of 1221 frames from eighty CMR studies. For each frame, AV landmarks (two hinge points and two leaflets), and stenotic and regurgitant jets were labelled by three cardiologists.

We then tested two AI models (Figure 1) to detect these AV abnormalities: A) a convolutional neural network (CNN), and B) a random forest approach.

A) Using heat map regression, the AV was localised, and the jets (if present) were identified as pathological curves. We then tracked and quantified the curves in the estimated heatmaps based on their proximity, the length, orientation and angle with respect to the hinge points.

B) We used a random forest approach to classify cases as normal or abnormal by using the characteristics of estimated pathological curves obtained from the heat map regression output.

We trained and evaluated our models on an unseen dataset of 1017 CMR studies obtained from different scanner types across three NHS hospitals. Each CMR study report was manually assigned a binary ground truth label for a normal or abnormal AV. In total 496/1017 patients had an abnormal AV. Of those abnormal cases, 184 patients had aortic stenosis, 222 aortic regurgitation and 90 cases had mixed valve disease.

We assessed the classification performance of our method with accuracy and an F1 score – a composite of precision and recall, where 1 is perfect; and heatmap regression performance for curves with mean absolute error.

Results

This machine learning approach classified abnormal aortic valves with good agreement to the ground truth labels with mean accuracy of 0.93 (representing approximately 451/496 patients) and mean F1 score of 0.91. The AV hinge points were localised with a mean distance error of 3.5 pixels. This was despite the small size of expert labelled data.

Conclusion

This machine learning solution successfully differentiated between normal and abnormal aortic valves from routine 3CH cine CMR views. More labelled datasets will enable further classification of pathology and severity, and greater accuracy. Our results represent an important stepping stone towards an AI-assisted CDSS for CMR.

Funding Acknowledgement

Type of funding sources: Other. Main funding source(s): This work was supported by the UKRI CDT in AI for Healthcare http://ai4health.io

Evaluation of a lateral-flow nanoparticle fluorescence assay for TB infection diagnosis

BACKGROUND:

Programmatic management of TB infection is a critical component of the WHO End TB Strategy. Interferon-gamma release assays (IGRAs) overcome some limitations of the tuberculin skin test, but implementation of IGRA testing in low-resource settings is challenging.

METHODS:

In this feasibility study, we evaluated performance of a novel digital lateral-flow assay, the QIAreach® QuantiFERON® TB (QIAreach-QFT) test, against the QuantiFERON®-TB Gold Plus (QFT-Plus) assay. A population with a mix of risk factors for TB infection (111 donors) were sampled over multiple days. A total of 207 individual blood samples were tested according to the manufacturer’s instructions.

RESULTS:

The overall percentage agreement was 95.6% (two-sided 95% CI 91.8–98), with a positive percentage agreement (i.e., sensitivity) of 100% (95% CI 94.7–100) and a negative percentage agreement (i.e., specificity) of 95.6% (95% CI 90.6–98.4). All QFT-Plus positive specimens with TB1-Nil and TB2-Nil values less than 1 IU/ml tested positive on QIAreach-QFT.

CONCLUSIONS:

QIAreach QFT is a deployable, accurate testing solution for decentralised testing. It has the potential to overcome key hurdles for TB infection screening in high-burden settings thus helping to achieve the WHO End TB programme goals.

Automated left ventricular dimension assessment using artificial intelligence

Background and purpose

Artificial intelligence (AI) has the potential to greatly improve efficiency and reproducibility of quantification in echocardiography, but to gain widespread use it must both meet expert standards of excellence and have a transparent methodology. We developed an online platform to enable multiple collaborators to annotate medical images for training and validating neural networks.

Methods

Using our online collaborative platform 9 expert echocardiographers labelled 2056 images that comprised the training dataset. They labelled the four points from where the standard parasternal long axis (PLAX) measurements (interventricular septum, posterior wall, left ventricular dimension) would be made. Using these labelled images we trained a 2d convolutional neural network to replicate these labels. Separately, we curated an external validation dataset of the systolic and diastolic frames of 100 PLAX acquisitions. Each of these images were labelled twice by 13 different experts, and the average of the 26 measurements was taken as the consensus standard.

We then compared the individual experts and the AI measurements on the external validation dataset to the consensus standard, and calculated the precision standard deviation (SD) of the signed differences from the consensus standard.

Results

For diastolic septum thickness, the AI had a precision SD of 1.8 mm (ICC 0.81; 95% CI 0.73 to 0.97), compared with 2.0 mm for the individual experts (ICC 0.64; 95% CI 0.57 to 0.72). For diastolic posterior wall thickness, the AI had a precision SD 1.4 mm (ICC 0.54; 95% CI 0.38 to 0.66), and the individual experts 2.2 mm (ICC 0.37; 95% CI 0.29 to 0.46).

The AI's precision SD for left ventricular internal dimension was 3.5 mm (ICC 0.93, 95% CI 0.90 to 0.94), and for individual experts was 4.4mm (ICC 0.82, 95% CI 0.78 to 0.95). Both the experts and AI performed better in diastole than systole (precision SD AI 2.5mm vs 4.3mm, p<0.0001; experts 3.3mm vs 5.3mm, p<0.0001).

Conclusions

AI trained by a group of echocardiography experts was able to perform PLAX measurements which matched the reference standard more closely than any individual expert's own measurements.

This open, collaborative approach may be a model for the development of AI that is explainable to, and trusted by clinicians.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperil BRC ITMATDr Howard was additionally funded by Wellcome. Online collaborative platformResults of AI and experts

Fully automated global longitudinal strain assessment using artificial intelligence developed and validated by a UK-wide echocardiography expert collaborative

Background

Left ventricular longitudinal strain has been reported to deliver reproducibility, sensitivity and prognostic value over and above ejection fraction. However, it currently relies on uninspectable proprietary algorithms and suffers from a lack of widespread clinical use. Uptake may be improved by increasing user trust through greater transparency.

Purpose

We therefore developed a machine-learning based method, trained, and validated with accredited experts from our AI Echocardiography Collaborative. We make the dataset, code, and trained network freely available under an open-source license.

Methods

AI enables strain to be calculated without relying on speckle tracking by directly locating key points and borders across frames. Strain can then be calculated as the fractional shortening of the left ventricular perimeter. We first curated a dataset of 7523 images, including 2587 apical four chamber, each labelled by a single expert from our collaboration of 17 hospitals, using our online platform (Figure 1). Using both this dataset and a semi-supervised approach, we trained a 3d convolutional neural network to identify the annulus, apex, and the endocardial border throughout the cardiac cycle.

Separately, we constructed an external validation dataset of 100 apical 4 chamber video-loops. The systolic and diastolic frame were identified, and each image was separately labelled by 11 experts. From these labels we then derived the expert consensus strain for each of the 100 video loops. These experts also ordered all 100 echocardiograms by their visual grading of left ventricular longitudinal function. Finally, a single expert calculated strain using two different proprietary commercial packages (A and B).

Results

Consensus strain measurements (obtained by averaging individual assessments by the 11 experts) across the 100 cases ranged from −4% to −27%, with strong correlations with the individual experts and machine methods (Figure 2). Using each cases' consensus across experts as the gold standard, median error from consensus was 3.1% for individual experts, 3.4% for Propriety A, 2.6% for Proprietary B, 2.6% for our AI.

Using the visual grading of longitudinal strain as the reference, the 11 individual experts and 4 machine methods each showed significant correlation: coefficients ranged from 0.55 to 0.69 for experts, and for Proprietary A was 0.68, Proprietary B 0.69, and our AI 0.69.

Conclusions

Our open-source, vendor-independent AI-based strain measure automatically produces values that agree with expert consensus, as strongly as the individual experts do. It also agrees with the subjective visual ranking by longitudinal function. Our open-source AI strain performs at least as well as closed-source speckle-based approaches, and may enable increased clinical and research use of longitudinal strain.

Funding Acknowledgement

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NIHR Imperial BRC ITMAT.Dr Howard was additionally funded by Wellcome. Figure 1. Collaborative online platformFigure 2. Correlations between strain methods

Direct Measurements of DT Fuel Preheat from Hot Electrons in Direct-Drive Inertial Confinement Fusion

Hot electrons generated by laser-plasma instabilities degrade the performance of laser-fusion implosions by preheating the DT fuel and reducing core compression. The hot-electron energy deposition in the DT fuel has been directly measured for the first time by comparing the hard x-ray signals between DT-layered and mass-equivalent ablator-only implosions. The electron energy deposition profile in the fuel is inferred through dedicated experiments using Cu-doped payloads of varying thickness. The measured preheat energy accurately explains the areal-density degradation observed in many OMEGA implosions. This technique can be used to assess the viability of the direct-drive approach to laser fusion with respect to the scaling of hot-electron preheat with laser energy.

Framework for large-scale automatic curation of heterogeneous cardiac MRI (ACUR MRI)

Funding Acknowledgements

Type of funding sources: Public grant(s) – National budget only. Main funding source(s): UKRI CDT in AI for Healthcare http://ai4health.io and British Heart Foundation

Background 

Data curation is an important process that structures and organises data, supporting research and the development of artificial intelligence models. However, manually curating a large volume of medical data is a time-consuming, repetitive and costly process that puts additional strain on clinical experts. The curation becomes more complex and demanding as more data sources are used. This leads to an introduction of disparity in the data structure and protocols. 

Purpose 

Here, we propose an automatic framework to curate large volumes of heterogenous cardiac MRI scans acquired across different sites and scanner vendors. Our framework requires minimal expert involvement throughout and works directly on DICOM images from the scanner or PACS.  The resulting structured standardised data allow for straightforward image analysis, hypothesis testing and the training and application of artificial intelligence models. 

Methods 

It is broken down into three main components

anonymisation, cataloguing and outlier detection (see Figure 1). Anonymisation automatically removes any identifiable patient information from the DICOM image attributes. These data are replaced with anonymised labels, whilst maintaining relevant longitudinal information from each patient. DICOM attributes are also used to automatically group the different images according to imaging sequence (e.g. CINE, Delayed-Enhancement, T1 maps), acquisition geometry (e.g. short-axis, 2-chamber, 4-chamber) and imaging attributes (e.g. slice thickness, TE, TR), for easier querying. The sorting characteristics are flexible and can easily be defined by the user. Finally, we detect and flag, for subsequent manual inspection, any outliers within those groups, based on the similarity levels of chosen DICOM attributes. This framework additionally offers interactive image visualisation to allow users to assess its performance in real time. 

Results 

We tested the performance of ACUR CMRI on 26,668 CMR image series (723,531 images) from 858 patient examinations, which took place across two sites in four different scanners. With an average execution time per patient of 100 seconds, ACUR was able to sort imaging data with 1191 different sequence names into 43 categories. The framework can be freely downloaded from https://bitbucket.org/cmr-ai-working-group/acur/. 

Conclusions 

We present ACUR, an automatic framework to curate large volumes of heterogeneous cardiac MRI data. We show how it can quickly and automatically curate data, grouping it according to desired imaging characteristics defined in DICOM attributes. The proposed framework is flexible and ideally suited as a pre-processing tool for large biomedical imaging data studies.

Pre-analytical stability of sorbitol dehydrogenase in equine heparinized plasma

Sorbitol dehydrogenase (SDH) activity is one of the most sensitive and specific markers for hepatocellular injury in horses, but its reported lability makes it impractical for use in many clinical settings. To date, stability of SDH in equine samples has only been evaluated in a limited number of studies in serum samples of horses with activities within reference intervals. The objective of the study was to determine pre-analytical stability of equine SDH activity in heparinized plasma stored at different temperatures for up to 72 h. Twenty client-owned horses admitted to a veterinary teaching hospital for any reason were included in the study. Blood samples collected in lithium-heparin tubes were immediately centrifuged and SDH activity was analyzed within 1 h of collection (T0). Aliquots of plasma were stored at room temperature, 4 °C and -20 °C and SDH activity was re-analyzed after 4 h (T4), 24 h (T24) and 72 h (T72). A significant difference from values measured at T0 was found for samples stored at room temperature (P = 0.022) and -20 °C (P < 0.001), but not at 4 °C. The activity of SDH was within ±20% of that measured at T0 for all samples under all temperature conditions stored for 4 h, and for all samples stored at 4 °C for 24 h. Bland-Altman plots revealed narrow limits of agreement at T4 for all storage temperatures and at T24 for samples stored at 4 °C. The mean absolute percentage error and 95th percentile of the absolute percentage error were lower for samples stored at 4 °C than those stored at room temperature or -20 °C. The activity of SDH has adequate stability for 4 h regardless of storage temperature and 24 h if stored at 4 °C across a wide range of values. Knowledge of the pre-analytical stability of SDH may permit its broader use in assessing hepatic disorders in horses.

His resynchronization therapy produces more physiological ventricular repolarisation compared with biventricular pacing

Funding Acknowledgements

Type of funding sources: Foundation. Main funding source(s): British Heart Foundation

BACKGROUND

Biventricular pacing (BVP) is known to shorten activation time in patients with heart failure and left bundle branch block (LBBB) but its effects on repolarisation are not well studied. His bundle pacing (HBP) can correct LBBB to deliver cardiac resynchronization therapy (HBP-CRT), producing more physiological ventricular activation time and pattern than BVP. It is not known whether this translates to more physiological repolarisation, and if so whether the effect is mediated through its effects on activation.

PURPOSE

We measured the effects of HBP-CRT and BVP on left ventricular repolarisation using non-invasive epicardial mapping (ECGI).

METHODS

Patients were recruited in two groups. 1) Patients scheduled for clinically indicated BVP procedures for heart failure with LBBB, 2) Individuals with narrow QRS, normal ventricular function and intact conduction systems. Using non-invasive electrocardiographic imaging, we identified patients with LBBB in whom HBP shortened ECGI-derived left ventricular (LV) activation time by &gt;10ms. We compared the effects of HBP and BVP on ECGI-derived dispersion of LV repolarisation times and activation-recovery intervals (a surrogate for action potential duration).

RESULTS

21 patients in whom HBP shortened LV activation time by &gt;10ms and an equal number of individuals with narrow intrinsic QRS were recruited. LV repolarisation dispersion was reduced by HBP-CRT (-42.0 ms, 95% confidence interval (CI): -52.3 to -31.7 ms, p &lt;0.001) but not by BVP (11.9 ms, 95% CI: -6.24 to 30.1 ms, p = 0.182). The mean within-patient change in LV repolarisation dispersion from BVP to HBP-CRT was -56.5 ms (95% CI: -70.5 to -42.5 ms, p &lt; 0.001). LV repolarisation dispersion with HBP-CRT was not different from individuals with narrow intrinsic QRS (2.75 ms, 95% CI: -16.2 to 21.7 ms, p = 0.981). The magnitude of reduction in LV repolarisation dispersion with HBP-CRT from intrinsic LBBB appeared similar to the magnitude of LV activation time shortening (-54.9 ms, 95% CI: -68.2 to -41.6 ms, p &lt; 0.001). However, LV activation-recovery interval dispersion was also reduced by HBP-CRT (-44.3 ms, 95% CI: -69.2 to -19.3 ms, p &lt; 0.001). Repolarisation mapping demonstrated normalisation of repolarisation pattern by HBP-CRT.

CONCLUSIONS

HBP-CRT can normalise repolarisation dispersion, producing more physiological repolarisation compared with BVP, which does not resolve the repolarisation abnormality of LBBB. HBP-CRT improves repolarisation through both activation resynchronization and modulation of action-potential duration. If these acute results translate to longer term outcomes, HBP-CRT may reduce the risk of ventricular arrhythmias in heart failure with LBBB to a greater extent than BVP. Abstract Figure. Epicardial Repolarisation Maps

908 Personal Protective Equipment (PPE) Guidance During A Global Pandemic: A Statistical Analysis of National Perceived Confidence, Knowledge, And Educational Deficits Amongst U.K. Based Doctors

Introduction

March 11th, 2020 saw the World Health Organisation declare a global pandemic following the eruption of the novel coronavirus disease 2019. Unprecedented global demand for personal protective equipment (PPE) was complicated by limited availability and conflicting guidance from healthcare bodies. This study aimed to assess perceived confidence and knowledge of Public Health England’s PPE guidance amongst doctors of varying specialties and grades.

Method

A nationwide 11-point survey comprising of multiple-choice questions (MCQs) and a Likert scale assessing perceived confidence (1=not confident, 5=very confident) was disseminated to U.K. based doctors using multiple platforms.

Results

Data collated from 697 respondents revealed average perceived confidence was low. Notably, 59% felt they had received insufficient education regarding up-to-date guidance, with 81% advocating further training. Anaesthetics and ophthalmology were the highest and lowest scoring specialties in knowledge based MCQs, achieving 59% and 31% respectively. Subsequent statistical analysis revealed significant differences between specialties."

Conclusions

Ensuring consistency in published PPE guidance and education can develop doctor’s confidence and knowledge of appropriate PPE use. The absence of a unified consensus and global education regarding the use of PPE poses significant ramifications for patient and healthcare professional (HCP) safety whilst risking further depletion of already sparse resources.

Guideline on the peri-operative management of patients with sickle cell disease: Guideline from the Association of Anaesthetists

Sickle cell disease is a multisystem disease characterised by chronic haemolytic anaemia, painful vaso-occlusive crises and acute and chronic end-organ damage. It is one of the most common serious inherited single gene conditions worldwide and has a major impact on the health of affected individuals. Peri-operative complications are higher in patients with sickle cell disease compared with the general population and may be sickle or non-sickle-related. Complications may be reduced by meticulous peri-operative care and transfusion, but unnecessary transfusion should be avoided, particularly to reduce the risk of allo-immunisation. Planned surgery and anaesthesia for patients with sickle cell disease should ideally be undertaken in centres with experience in caring for these patients. In an emergency, advice should be sought from specialists with experience in sickle cell disease through the haemoglobinopathy network arrangements. Emerging data suggest that patients with sickle cell disease are at increased risk of COVID-19 infection but may have a relatively mild clinical course. Outcomes are determined by pre-existing comorbidities, as for the general population.

Prevalence of cardiac abnormalities in sickle cell disease identified using cardiac magnetic resonance imaging

Background

Sickle cell disease (SCD) affects thousands of individuals in the United Kingdom causing significant morbidity and mortality. Modern therapies have been successful in increasing life expectancy, however these patients have an increased risk of cardiovascular complications and the extent to which sickle cell disease affects cardiac function is not well understood. Cardiac magnetic resonance imaging (MRI) is the gold standard imaging modality for evaluating myocardial function. It is known that sickle cell patients can present with pulmonary hypertension, left ventricular diastolic dysfunction, and atrial enlargement however the prevalence of other cardiac abnormalities has not been sufficiently investigated with cardiac MRI. In addition, the European Society of Cardiology (ESC) updated their definition of Heart Failure in 2016 and therefore will need to be re-assessed in this population.

Purpose

To evaluate the prevalence of cardiac abnormalities in the sickle cell population using cardiac MRI and based on the recently updated diagnostic criteria.

Methods

We conducted a retrospective review including all patients with sickle cell disease at a large tertiary hospital in London, United Kingdom who had been referred for cardiac MRI between 2011 and 2019. Data was collected data on various measures of cardiac function including: left ventricular ejection fraction (LVEF), left ventricular hypertrophy, left and right atrial enlargement, regional wall motion abnormalities, valvular disease, myocardial scarring, and cardiac iron load.

Results

82 patients and 123 cardiac MRI scans were reviewed in this study. 68% of patients were female and the average age at time of scan was 37 years. The average left ventricular ejection fraction was 57% (n=82). Cardiac abnormalities were identified in 60% of patients. The most common cardiac abnormalities reported were: valvular regurgitation (46%; n=28), left atrial enlargement (28%; n=19), right atrial enlargement (16%; n=11), left ventricular hypertrophy (11%; n=8), regional wall motion abnormalities (10%; n=7), and myocardial scar with late gadolinium enhancement (9%; n=7). 28% of the patients were diagnosed with Heart Failure; 11% of the patients satisfied the diagnostic criteria for HFpEF (Heart failure with preserved ejection fraction, n=9), 10% with HFrEF (Heart Failure with reduced ejection fraction, n=8), and 7% with HFmrEF (Heart Failure with mid-range ejection fraction, n=6).

Conclusion

Sickle cell disease affects cardiac function in the majority of patients resulting in numerous cardiac abnormalities. We have described the overall extent of these effects using data from cardiac MRI scans, which has not been commonly used thus far. This has implications for both the diagnosis and subsequent management of cardiac abnormalities in this population, and it can be used to further investigate and guide the development of targeted treatments for these patients.

Funding Acknowledgement

Type of funding source: None

Prevalence and pattern of energy drink intake among Australian adolescents

BACKGROUND

Energy drinks (ED) are popular among young people despite evidence of associated health risks. Research into the prevalence and pattern of ED intake among young people is sparse. The present study investigates the prevalence and pattern of ED intake among a large sample of adolescents, including how many consume them, how often, for what reasons and in what contexts.

METHODS

In 2018, all students in grades 7-12 attending 25 randomly selected Western Australian schools were invited to complete an online self-report survey about EDs.

RESULTS

Of the 3688 respondents, 51.2% reported consuming an ED. Of these 'ever consumers', 23.4% drank them monthly, 19.2% weekly and 2% every day. The average age of first intake was 10.7 years. One-fifth (19.7%) of 'ever consumers' reported consuming more than two EDs in 1 day. Reasons for ED use included taste, to boost energy levels, sport performance and studying.

CONCLUSIONS

The findings add to limited international evidence about adolescent ED use and provide valuable information to help ensure interventions to reduce intake address the underlying reasons and contexts of ED consumption.

Doppler coherence imaging of scrape-off-layer impurity flows in the HL-2A tokamak

A new Doppler coherence imaging spectroscopy interferometer has been developed on the HL-2A tokamak for the scrape-off-layer impurity flow measurement. Its spatial resolution is estimated to be up to ∼0.8 mm in the horizontal direction and ∼9 mm in the vertical direction, with a field of view of ∼34°. Its typical temporal resolution is about 1 ms. This salient feature allows for time-resolved 2D measurements in short-time phenomena on HL-2A, such as edge localized modes. Group delay and interference fringe pattern were calibrated with a dedicated calibration system. The robustness of group delay calibration and the feasibility of the extrapolation model for fringe pattern calibration are demonstrated. In this paper, we report the details of the optical instruments, calibration, and the initial experimental results of this Doppler coherence imaging spectroscopy interferometer.

Laser calibration of the DIII-D coherence imaging system

In this paper, we describe an in situ calibration technique for Coherence Imaging Spectroscopy (CIS) that measures 2-D images of ion flows on DIII-D. A low power CW diode laser that is tuneable in the range 464-468 nm along with a precision wavemeter (10^-5 nm resolution) is used to characterize the interferometer phase as a function of wavelength in the region of C iii (465 nm) and He ii (468 nm). The interferometer is stabilized both mechanically and thermally to minimize drift during the calibration. Optical stirring and an integration sphere are used to obtain spatially uniform calibration images. The quality of the calibration data enables a measurement of phase versus wavelength over approximately 10 fringes of the interferometer. These coefficients can also be related to the geometry of the optics and the birefringent crystal of the interferometer. On DIII-D, the integration sphere with the laser light is inserted into the CIS optical system between shots and the laser image and wavelength are automatically recorded, providing a zero velocity reference.

Coherence-imaging spectroscopy for 2D distribution of ion temperature and flow velocity in a laboratory magnetosphere

A coherence-imaging spectroscopy (CIS) technique was developed to investigate plasma confinement in a dipole system that imitates a planetary magnetosphere. Optical interference generated using birefringent crystals enables two-dimensional Doppler spectroscopy to measure ion temperatures and flow velocities in plasmas. CIS covers the entire dynamics of the pole areas as well as of the core and edge areas on a dipole confinement device. The two-dimensional visualization of these quantities in the magnetospheric-plasma device RT-1 was demonstrated using CIS.

A Type 1 Diabetes Genetic Risk Score Predicts Progression of Islet Autoimmunity and Development of Type 1 Diabetes in Individuals at Risk

OBJECTIVE

We tested the ability of a type 1 diabetes (T1D) genetic risk score (GRS) to predict progression of islet autoimmunity and T1D in at-risk individuals.

RESEARCH DESIGN AND METHODS

We studied the 1,244 TrialNet Pathway to Prevention study participants (T1D patients' relatives without diabetes and with one or more positive autoantibodies) who were genotyped with Illumina ImmunoChip (median [range] age at initial autoantibody determination 11.1 years [1.2-51.8], 48% male, 80.5% non-Hispanic white, median follow-up 5.4 years). Of 291 participants with a single positive autoantibody at screening, 157 converted to multiple autoantibody positivity and 55 developed diabetes. Of 953 participants with multiple positive autoantibodies at screening, 419 developed diabetes. We calculated the T1D GRS from 30 T1D-associated single nucleotide polymorphisms. We used multivariable Cox regression models, time-dependent receiver operating characteristic curves, and area under the curve (AUC) measures to evaluate prognostic utility of T1D GRS, age, sex, Diabetes Prevention Trial-Type 1 (DPT-1) Risk Score, positive autoantibody number or type, HLA DR3/DR4-DQ8 status, and race/ethnicity. We used recursive partitioning analyses to identify cut points in continuous variables.

RESULTS

Higher T1D GRS significantly increased the rate of progression to T1D adjusting for DPT-1 Risk Score, age, number of positive autoantibodies, sex, and ethnicity (hazard ratio [HR] 1.29 for a 0.05 increase, 95% CI 1.06-1.6; P = 0.011). Progression to T1D was best predicted by a combined model with GRS, number of positive autoantibodies, DPT-1 Risk Score, and age (7-year time-integrated AUC = 0.79, 5-year AUC = 0.73). Higher GRS was significantly associated with increased progression rate from single to multiple positive autoantibodies after adjusting for age, autoantibody type, ethnicity, and sex (HR 2.27 for GRS >0.295, 95% CI 1.47-3.51; P = 0.0002).

CONCLUSIONS

The T1D GRS independently predicts progression to T1D and improves prediction along T1D stages in autoantibody-positive relatives.

Verification of Doppler coherence imaging for 2D ion velocity measurements on DIII-D

Coherence Imaging Spectroscopy (CIS) has emerged as a powerful tool for investigating complex ion phenomena in the boundary of magnetically confined plasma devices. The combination of Fourier-transform interferometry and high-resolution fast-framing cameras has made it possible to make sensitive velocity measurements that are also spatially resolved. However, this sensitivity makes the diagnostic vulnerable to environmental effects including thermal drifts, vibration, and magnetic fields that can influence the velocity measurement. Additionally, the ability to provide an absolute calibration for these geometries can be impacted by differences in the light-collection geometry between the plasma and reference light source, spectral impurities, and the presence of thin-films on in-vessel optics. This paper discusses the mitigation of these effects and demonstration that environmental effects result in less than 0.5 km/s error on the DIII-D CIS systems. A diagnostic comparison is used to demonstrate agreement between CIS and traditional spectroscopy once tomographic artifacts are accounted for.

Tibial plateau angles with and without cranial cruciate ligament rupture

The tibial plateau angles (TPA) of dogs with and without cranial cruciate ligament (CrCL) injuries were evaluated and further compared to the TPAs of dogs from a previous population and of wolves. Similar TPA measurements were found in all groups, suggesting that any possible changes in breeding practises, breed preferences, nutrition or other factors have not significantly influenced the TPA over time. Moreover, a difference was not found in the TPA between any group and the group affected with CrCL injury, suggesting that the TPA is not a clinically relevant predisposing factor in the development of canine CrCL rupture.

Topological cell clustering in the ATLAS calorimeters and its performance in LHC Run 1

The reconstruction of the signal from hadrons and jets emerging from the proton-proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.

Validation of a Point-of-Care Quantitative Equine IgG Turbidimetric Immunoassay and Comparison of IgG Concentrations Measured with Radial Immunodiffusion and a Point-of-Care IgG ELISA

BACKGROUND

Point-of-care (POC) diagnostic tests with good sensitivity and specificity are needed for diagnosing failure of transfer of passive immunity (FTPI) in foals. Turbidimetric immunoassays (TIA) have these characteristics and provide quantitative results. A commercially available TIA-based POC test (POC-TIA) has not been validated in horses.

OBJECTIVE

To validate a POC-TIA and compare results of POC-TIA, a POC-ELISA, and radial immunodiffusion (RID).

ANIMALS

Heparinized blood samples (n = 127) from 48 hospitalized foals (<12 hour to 48 days).

METHODS

Prospective validation study. IgG concentrations were measured using RID (gold standard), POC-TIA, and POC-ELISA. Agreement between assays was assessed using Bland-Altman analysis. Sensitivity and specificity were calculated using ROC curves. Inter- and intra-assay coefficients of variation (CVs) and linearity were evaluated for POC-TIA.

RESULTS

The mean bias (95% limits of agreement) between RID and POC-TIA was -4 (-185 to 176), 27 (-201 to 255), and 308 (-377 to 993) mg/dL for samples with IgG concentrations of <400, 400-800, and >800 mg/dL, respectively. Sensitivity and specificity at optimal cutoff were 94 and 100% for the POC-TIA and 94 and 100% for the POC-ELISA to detect IgG <400 mg/dL, and 85 and 87% (POC-TIA) and 69 and 79% (POC-ELISA) to detect IgG ≤800 mg/dL. Intra- and interassay CVs for POC-TIA ranged between 1.6-3.8 and 11.9-18.8%, respectively. Linearity of the dilution series was preserved (R² > 0.96).

CONCLUSIONS AND CLINICAL IMPORTANCE

The POC-TIA provided unambiguous results and had sufficient sensitivity, specificity, accuracy, and precision to be used as an alternative to other POC tests to assess FTPI in foals.

Performance of algorithms that reconstruct missing transverse momentum in [Formula: see text]= 8 TeV proton-proton collisions in the ATLAS detector

The reconstruction and calibration algorithms used to calculate missing transverse momentum ([Formula: see text] ) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton-proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the [Formula: see text] reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton-proton collisions at a centre-of-mass energy of 8 [Formula: see text] during 2012, and results are shown for a data sample corresponding to an integrated luminosity of [Formula: see text]. The simulation and modelling of [Formula: see text]  in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for [Formula: see text] , and estimates of the systematic uncertainties in the [Formula: see text]  measurements are presented.

Test of CP invariance in vector-boson fusion production of the Higgs boson using the Optimal Observable method in the ditau decay channel with the ATLAS detector

A test of CP invariance in Higgs boson production via vector-boson fusion using the method of the Optimal Observable is presented. The analysis exploits the decay mode of the Higgs boson into a pair of [Formula: see text] leptons and is based on 20.3 [Formula: see text] of proton-proton collision data at [Formula: see text] = 8 [Formula: see text] collected by the ATLAS experiment at the LHC. Contributions from CP-violating interactions between the Higgs boson and electroweak gauge bosons are described in an effective field theory framework, in which the strength of CP violation is governed by a single parameter [Formula: see text]. The mean values and distributions of CP-odd observables agree with the expectation in the Standard Model and show no sign of CP violation. The CP-mixing parameter [Formula: see text] is constrained to the interval [Formula: see text] at 68% confidence level, consistent with the Standard Model expectation of [Formula: see text].

Stokes-Doppler coherence imaging for ITER boundary tomography

An optical coherence imaging system is presently being designed for impurity transport studies and other applications on ITER. The wide variation in magnetic field strength and pitch angle (assumed known) across the field of view generates additional Zeeman-polarization-weighting information that can improve the reliability of tomographic reconstructions. Because background reflected light will be somewhat depolarized analysis of only the polarized fraction may be enough to provide a level of background suppression. We present the principles behind these ideas and some simulations that demonstrate how the approach might work on ITER. The views and opinions expressed herein do not necessarily reflect those of the ITER Organization.

Performance of pile-up mitigation techniques for jets in [Formula: see text] collisions at [Formula: see text] TeV using the ATLAS detector

The large rate of multiple simultaneous proton-proton interactions, or pile-up, generated by the Large Hadron Collider in Run 1 required the development of many new techniques to mitigate the adverse effects of these conditions. This paper describes the methods employed in the ATLAS experiment to correct for the impact of pile-up on jet energy and jet shapes, and for the presence of spurious additional jets, with a primary focus on the large 20.3 [Formula: see text] data sample collected at a centre-of-mass energy of [Formula: see text]. The energy correction techniques that incorporate sophisticated estimates of the average pile-up energy density and tracking information are presented. Jet-to-vertex association techniques are discussed and projections of performance for the future are considered. Lastly, the extension of these techniques to mitigate the effect of pile-up on jet shapes using subtraction and grooming procedures is presented.

Search for gluinos in events with an isolated lepton, jets and missing transverse momentum at [Formula: see text] = 13 Te V with the ATLAS detector

The results of a search for gluinos in final states with an isolated electron or muon, multiple jets and large missing transverse momentum using proton-proton collision data at a centre-of-mass energy of [Formula: see text] are presented. The dataset used was recorded in 2015 by the ATLAS experiment at the Large Hadron Collider and corresponds to an integrated luminosity of 3.2 fb[Formula: see text]. Six signal selections are defined that best exploit the signal characteristics. The data agree with the Standard Model background expectation in all six signal selections, and the largest deviation is a 2.1 standard deviation excess. The results are interpreted in a simplified model where pair-produced gluinos decay via the lightest chargino to the lightest neutralino. In this model, gluinos are excluded up to masses of approximately 1.6 Te V depending on the mass spectrum of the simplified model, thus surpassing the limits of previous searches.

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton-proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon-nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction.