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.

Automated movement tracking of young autistic children during free play is correlated with clinical features associated with autism

LAY ABSTRACT

Play-based observations allow researchers to observe autistic children across a wide range of ages and skills. We recorded autistic children playing with toys in the center of a room and at a corner table while a caregiver remained seated off to the side and used video tracking technology to track children's movement and location. We examined how time children spent in room regions and whether or not they approached each region during play related to their cognitive, social, communication, and adaptive skills to determine if tracking child movement and location can meaningfully demonstrate clinical variation among autistic children representing a range of ages and skills. One significant finding was that autistic children who spent more time in the toy-containing center of the room had higher cognitive and language abilities, whereas those who spent less time in the center had higher levels of autism-related behaviors. In contrast, children who spent more time in the caregiver region had lower daily living skills and those who were quicker to approach the caregiver had lower adaptive behavior and language skills. These findings support the use of movement tracking as a complementary method of measuring clinical differences among autistic children. Furthermore, over 90% of autistic children representing a range of ages and skills in this study provided analyzable play observation data, demonstrating that this method allows autistic children of all levels of support needs to participate in research and demonstrate their social, communication, and attention skills without wearing any devices.

Associations between executive function and attention abilities and language and social communication skills in young autistic children

LAY ABSTRACT

Executive functioning describes a set of cognitive processes that affect thinking and behavior. Past research has shown that autistic individuals often have delays in the acquisition of executive function abilities. Our study explored how differences in executive function and attention abilities relate to social abilities and communication/language in 180 young autistic children. Data were gathered via caregiver report (questionnaires/interviews) and an assessment of vocabulary skills. The ability to sustain attention to a dynamic video was measured via eye tracking. We found that children with higher levels of executive function skills demonstrated lower levels of social pragmatic problems, a measure of having difficulties in social contexts. Furthermore, children who were able to sustain their attention longer to the video displayed higher levels of expressive language. Our results emphasize the importance of executive function and attention skills across multiple areas of functioning in autistic children, in particular those that involve language and social communication.

Automated Video Tracking of Autistic Children's Movement During Caregiver-Child Interaction: An Exploratory Study

Objective, quantitative measures of caregiver-child interaction during play are needed to complement caregiver or examiner ratings for clinical assessment and tracking intervention responses. In this exploratory study, we examined the feasibility of using automated video tracking, Noldus EthoVision XT, to measure 159 2-to-7-year-old autistic children's patterns of movement during play-based, caregiver-child interactions and examined their associations with standard clinical measures and human observational coding of caregiver-child joint engagement. Results revealed that autistic children who exhibited higher durations and velocity of movement were, on average, younger, had lower cognitive abilities, greater autism-related features, spent less time attending to the caregiver, and showed lower levels of joint engagement. After adjusting for age and nonverbal cognitive abilities, we found that children who remained in close proximity to their caregiver were more likely to engage in joint engagement that required support from the caregiver. These findings suggest that video tracking offers promise as a scalable, quantitative, and relevant measure of autism-related behaviors.

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.

Eye-tracking measures of social versus nonsocial attention are related to level of social engagement during naturalistic caregiver-child interactions in autistic children

Eye-tracking (ET) measures indexing social attention have been proposed as sensitive measures related to autism, but less is known about the relationship between social and nonsocial attention and naturalistic measures of social engagement and whether sex moderates this relationship. This study investigated ET measures of social attention as predictors of social engagement during a naturalistic caregiver-child interaction (CCI). Participants included 132, 2-7-year-old autistic children (77% male) and their caregivers. Participants engaged in a CCI and an ET task in which they viewed a video of an actor making dyadic bids toward the child with toys in the background. Pearson correlations and multiple regression analyzes revealed that ET measures correlated with social engagement behaviors, including degree of attention to the caregiver and objects, joint engagement with the caregiver, and language-based joint engagement. Children who spent more time looking at toys were more likely to be unengaged during social interaction. Those who spent more time looking at the actor's mouth were more likely to engage in coordinated play with and without language. Sex moderated the relationship between time looking at toys and unengagement during play; males who spent more time looking at toys spent more time unengaged during play, whereas females who spent more time looking at toys spent less time unengaged during play. Overall, ET measures of social and nonsocial attention correlated with the level of social engagement during naturalistic play, with some sex differences. Eye-tracking measures that predict interaction patterns may provide insight into promoting social engagement between caregivers and their autistic children and can inform outcome monitoring and intervention development.

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

Inequities in Receipt of the North Carolina Medicaid Waiver Among Individuals with Intellectual Disability or Autism Spectrum Disorder

OBJECTIVE

We examined characteristics associated with receiving the North Carolina Home and Community-Based Services Waiver for intellectual and developmental disabilities (I/DDs) and its association with emergency department (ED) utilization.

METHOD

Through analysis of the North Carolina 2017 to 2018 Medicaid claims and enrollment data, we examined characteristics (age, sex, race and ethnicity, geography, diagnosis (intellectual disability [ID] with or without autism spectrum disorders or autism spectrum disorder without ID) associated with receiving the NC I/DD Waiver and the association of this Wavier with ED utilization. We identified patients with at least 1 International Classification of Diseases-10-CM diagnosis code for an ID or autism spectrum disorder. We excluded patients with missing county information and whose enrollment in the NC I/DD Waiver program began after October 1, 2017.

RESULTS

Only 22% of 53,531 individuals with I/DD in North Carolina received the Waiver. Non-Hispanic Blacks and Hispanic individuals were less likely to receive the Waiver than non-Hispanic White individuals. Adults (>21 years old), men, and urban residents were more likely to receive the Waiver. Individuals who received the Waiver were 31% less likely to use the ED.

CONCLUSION

Innovative strategies are needed to provide equitable access to the NC I/DD Waiver and provide services to the 14,000 people with I/DD currently waiting to receive the Waiver. Through the Waiver, those with I/DD can access preventative and therapeutic outpatient services and decrease their need for ED care. These findings highlight the need for policy reform to address inequities in access to the Waiver for individuals with I/DD.

Pragmatic adaptations of telehealth-delivered caregiver coaching for children with autism in the context of COVID-19: Perspectives from the United States and South Africa

LAY ABSTRACT

COVID-19 caused many autism spectrum disorder caregiver-coaching studies to move to telehealth. Telehealth can increase the diversity of people who take part in research. This matters because most autism spectrum disorder studies have included people who have resources, are White, and live in North America and Europe. When study participants are similar, it is hard to understand which interventions can help different types of people who live in different parts of the world. While telehealth may allow more people to take part in research, it needs to "fit" the local context and consider the "digital divide" because many people around the world have no access to computers and the Internet. This short report describes changes to two research studies that include caregiver coaching based on the Early Start Denver Model in the United States and South Africa. We describe how the local context, including technology and Internet access, guided the telehealth approach. By doing so, we highlight ways to make telehealth available to more people around the world. The pandemic can help us understand how telehealth can "fit" diverse places and support high-quality research. It is important that study changes are tracked and we assess how well the changes work. COVID-19 telehealth changes to caregiver coaching can result in new ways to reach more people around the world.

Shorter average look durations to dynamic social stimuli are associated with higher levels of autism symptoms in young autistic children

LAY ABSTRACT

Many studies of autism look at the differences in how autistic research participants look at certain types of images. These studies often focus on where research participants are looking within the image, but that does not tell us everything about how much they are paying attention. It could be useful to know more about how well autistic research participants can focus on an image with people in it, because those who can look at images of people for longer duration without stopping may be able to easily learn other skills that help them to interact with people. We measured how long autistic research participants watched the video without breaking their attention. The video sometimes had a person speaking, and at other times had toys moving and making sounds. We measured the typical amount of time autistic research participants could look at the video before they looked away. We found that research participants with more severe autism tended to look at the video for shorter amounts of time. The ability to focus without stopping may be related to social skills in autistic people.

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

Distance from Typical Scan Path When Viewing Complex Stimuli in Children with Autism Spectrum Disorder and its Association with Behavior

Eye-tracking is often used to study attention in children with autism spectrum disorder (ASD). Previous research has identified multiple atypical patterns of attention in children with ASD based on areas-of-interest analysis. Fewer studies have investigated gaze path, a measure which is dependent on the dynamic content of the stimulus presented. Here, rather than looking at proportions of looking time to areas of interest, we calculated mean fixations frame-by-frame in a group of typically developing children (36 to 72 months) and determined the distance from those typical fixations for 155 children with ASD (27-95 months). Findings revealed that distance from the typical scan path among the children with ASD was associated with lower communication abilities and greater ASD symptomatology.

A scalable computational approach to assessing response to name in toddlers with autism

BACKGROUND

This study is part of a larger research program focused on developing objective, scalable tools for digital behavioral phenotyping. We evaluated whether a digital app delivered on a smartphone or tablet using computer vision analysis (CVA) can elicit and accurately measure one of the most common early autism symptoms, namely failure to respond to a name call.

METHODS

During a pediatric primary care well-child visit, 910 toddlers, 17-37 months old, were administered an app on an iPhone or iPad consisting of brief movies during which the child's name was called three times by an examiner standing behind them. Thirty-seven toddlers were subsequently diagnosed with autism spectrum disorder (ASD). Name calls and children's behavior were recorded by the camera embedded in the device, and children's head turns were coded by both CVA and a human.

RESULTS

CVA coding of response to name was found to be comparable to human coding. Based on CVA, children with ASD responded to their name significantly less frequently than children without ASD. CVA also revealed that children with ASD who did orient to their name exhibited a longer latency before turning their head. Combining information about both the frequency and the delay in response to name improved the ability to distinguish toddlers with and without ASD.

CONCLUSIONS

A digital app delivered on an iPhone or iPad in real-world settings using computer vision analysis to quantify behavior can reliably detect a key early autism symptom-failure to respond to name. Moreover, the higher resolution offered by CVA identified a delay in head turn in toddlers with ASD who did respond to their name. Digital phenotyping is a promising methodology for early assessment of ASD symptoms.

Computational Methods to Measure Patterns of Gaze in Toddlers With Autism Spectrum Disorder

Importance

Atypical eye gaze is an early-emerging symptom of autism spectrum disorder (ASD) and holds promise for autism screening. Current eye-tracking methods are expensive and require special equipment and calibration. There is a need for scalable, feasible methods for measuring eye gaze.

Objective

Using computational methods based on computer vision analysis, we evaluated whether an app deployed on an iPhone or iPad that displayed strategically designed brief movies could elicit and quantify differences in eye-gaze patterns of toddlers with ASD vs typical development.

Design, Setting, and Participants

A prospective study in pediatric primary care clinics was conducted from December 2018 to March 2020, comparing toddlers with and without ASD. Caregivers of 1564 toddlers were invited to participate during a well-child visit. A total of 993 toddlers (63%) completed study measures. Enrollment criteria were aged 16 to 38 months, healthy, English- or Spanish-speaking caregiver, and toddler able to sit and view the app. Participants were screened with the Modified Checklist for Autism in Toddlers-Revised With Follow-up during routine care. Children were referred by their pediatrician for diagnostic evaluation based on results of the checklist or if the caregiver or pediatrician was concerned. Forty toddlers subsequently were diagnosed with ASD.

Exposures

A mobile app displayed on a smartphone or tablet.

Main Outcomes and Measures

Computer vision analysis quantified eye-gaze patterns elicited by the app, which were compared between toddlers with ASD vs typical development.

Results

Mean age of the sample was 21.1 months (range, 17.1-36.9 months), and 50.6% were boys, 59.8% White individuals, 16.5% Black individuals, 23.7% other race, and 16.9% Hispanic/Latino individuals. Distinctive eye-gaze patterns were detected in toddlers with ASD, characterized by reduced gaze to social stimuli and to salient social moments during the movies, and previously unknown deficits in coordination of gaze with speech sounds. The area under the receiver operating characteristic curve discriminating ASD vs non-ASD using multiple gaze features was 0.90 (95% CI, 0.82-0.97).

Conclusions and Relevance

The app reliably measured both known and new gaze biomarkers that distinguished toddlers with ASD vs typical development. These novel results may have potential for developing scalable autism screening tools, exportable to natural settings, and enabling data sets amenable to machine learning.

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.

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.

Educational classifications of autism spectrum disorder and intellectual disability among school‐aged children in North Carolina: Associations with race, rurality, and resource availability

Disparities exist in the recognition of autism spectrum disorder (ASD) and intellectual disability (ID) in racial/ethnic minorities in the United States. This study examined whether rurality, race/ethnicity, and low resource availability are associated with disparities in primary educational classifications of ASD and ID in North Carolina (NC). Descriptive maps were created. Multilevel logistic regression models examined two separate outcomes (mild ID vs. ASD; moderate/severe ID vs. ASD). For the interaction term included in the model (race/ethnicity and residence), predicted probabilities were estimated and plotted. The effects of other covariates were also estimated. Rural counties had fewer students with ASD and a greater number of students with ID compared to urban counties. The majority of students with ASD were non-Hispanic Whites, while the majority of students with ID were non-Hispanic Blacks. Compared to non-Hispanic White students, non-Hispanic Black students were overrepresented in the ID classification and underrepresented in the ASD classification across urban and rural areas. Indicators of low resource availability were also associated with higher probabilities of ID vs. ASD classification. Differences in primary educational classification based on urban-rural divide, race/ethnicity, and resource availability are important to understand as they may point to disparities that could have significant policy and service implications. Because disparities manifest through complex interactions between environmental, socioeconomic and system-level factors, reduction in these disparities will require broader approaches that address structural determinants. Future research should utilize disparity frameworks to understand differences in primary educational classifications of ASD and ID in the context of race/ethnicity and rurality. LAY SUMMARY: Rural counties in North Carolina had fewer students with ASD and a greater number of students with ID compared to urban counties. Compared to non-Hispanic White students, non-Hispanic Black students were over-represented in the ID educational classification and underrepresented in the ASD classification. Differences in classification of ASD and ID based on urban-rural divide, race/ethnicity, and resource availability may point to disparities that could have significant policy and service implications. Autism Res 2021, 14: 1046-1060. © 2021 International Society for Autism Research, Wiley Periodicals LLC.

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

Gastrointestinal problems are associated with increased repetitive behaviors but not social communication difficulties in young children with autism spectrum disorders

LAY ABSTRACT

Individuals with autism spectrum disorder are more likely than typically developing individuals to experience a range of gastrointestinal abnormalities, including chronic diarrhea, constipation, food sensitivities, and abdominal pain. These gastrointestinal symptoms have been associated with higher levels of irritability and aggressive behavior, but less is known about their relationship with core autism spectrum disorder symptoms. We investigated the relationship between autism spectrum disorder symptom severity and gastrointestinal symptoms while accounting for three associated behavioral symptom domains (Irritability, Aggressiveness, and Specific Fears), in a sample of 176 children (140 males and 36 females) ages 2-7 years old with autism spectrum disorder. A large majority (93.2%) of the sample had at least one reported gastrointestinal symptom, and most (88.1%) participants had more than one gastrointestinal symptom. Various types of gastrointestinal symptoms were reported; the most common symptoms reported were constipation, food limits, gas/bloating, and stomach pain. After accounting for each associated behavioral symptom domain, repetitive behaviors and stereotypies were significantly associated with gastrointestinal symptom severity. Increased severity of autism spectrum disorder symptoms was correlated with increased gastrointestinal symptom severity. Social and communication difficulties were not significantly associated with gastrointestinal symptom severity after accounting for associated behavioral symptoms. Our findings replicate a previously described association between irritability and aggression and gastrointestinal symptoms. Furthermore, we found that repetitive behaviors, but not social or communication symptoms, are associated with gastrointestinal symptom severity, even after accounting for associated behavioral symptoms. This suggests that gastrointestinal symptoms may exacerbate repetitive behaviors, or vice versa, independent from other associated behavioral symptoms.

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.

A Phase II Randomized Clinical Trial of the Safety and Efficacy of Intravenous Umbilical Cord Blood Infusion for Treatment of Children with Autism Spectrum Disorder

OBJECTIVE

To evaluate whether umbilical cord blood (CB) infusion is safe and associated with improved social and communication abilities in children with autism spectrum disorder (ASD).

STUDY DESIGN

This prospective, randomized, placebo-controlled, double-blind study included 180 children with ASD, aged 2-7 years, who received a single intravenous autologous (n = 56) or allogeneic (n = 63) CB infusion vs placebo (n = 61) and were evaluated at 6 months postinfusion.

RESULTS

CB infusion was safe and well tolerated. Analysis of the entire sample showed no evidence that CB was associated with improvements in the primary outcome, social communication (Vineland Adaptive Behavior Scales-3 [VABS-3] Socialization Domain), or the secondary outcomes, autism symptoms (Pervasive Developmental Disorder Behavior Inventory) and vocabulary (Expressive One-Word Picture Vocabulary Test). There was also no overall evidence of differential effects by type of CB infused. In a subanalysis of children without intellectual disability (ID), allogeneic, but not autologous, CB was associated with improvement in a larger percentage of children on the clinician-rated Clinical Global Impression-Improvement scale, but the OR for improvement was not significant. Children without ID treated with CB showed significant improvements in communication skills (VABS-3 Communication Domain), and exploratory measures including attention to toys and sustained attention (eye-tracking) and increased alpha and beta electroencephalographic power.

CONCLUSIONS

Overall, a single infusion of CB was not associated with improved socialization skills or reduced autism symptoms. More research is warranted to determine whether CB infusion is an effective treatment for some children with ASD.

Infusion of human umbilical cord tissue mesenchymal stromal cells in children with autism spectrum disorder

Ongoing neuroinflammation may contribute to symptoms of autism spectrum disorder (ASD) in at least a portion of affected individuals. Mesenchymal stromal cells (MSCs) have demonstrated the capacity to modulate neuroinflammation, but safety and feasibility of MSC administration in children with ASD have not been well established. In this open-label, phase I study, 12 children with ASD between 4 and 9 years of age were treated with intravenous (IV) infusions of human cord tissue mesenchymal stromal cells (hCT-MSCs), a third-party MSC product manufactured from unrelated donor umbilical cord tissue. Children received one, two, or three doses of 2 × 10⁶ cells per kilogram at 2-month intervals. Clinical and laboratory evaluations were performed in person at baseline and 6 months and remotely at 12 months after the final infusion. Aside from agitation during the IV placement and infusion in some participants, hCT-MSCs were well tolerated. Five participants developed new class I anti-human leukocyte antigen (HLA) antibodies, associated with a specific lot of hCT-MSCs or with a partial HLA match between donor and recipient. These antibodies were clinically silent and not associated with any clinical manifestations to date. Six of 12 participants demonstrated improvement in at least two ASD-specific measures. Manufacturing and administration of hCT-MSCs appear to be safe and feasible in young children with ASD. Efficacy will be evaluated in a subsequent phase II randomized, placebo-controlled clinical trial.

Brief Report: Classifying Rates of Students with Autism and Intellectual Disability in North Carolina: Roles of Race and Economic Disadvantage

We examined special education classifications among students aged 3-21 in North Carolina public schools, highlighting autism spectrum disorder (ASD) and intellectual disability (ID). Results revealed variability by county in ASD and ID prevalence, and in county-level ratios of ID vs. ASD classifications. Sociodemographic characteristics predicted proportion of ASD or ID within a county; correlations showed an association between race and ID, but not ASD. County's median household income predicted proportion of students classified as ASD and ID (opposite directions), controlling for number of students and gender. Variability was unlikely related to biological incidence, and more likely related to district/school practices, or differences in resources. Disparities warrant further examination to ensure that North Carolina's youth with disabilities access necessary, appropriate resources.

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.