Associations between type 1 diabetes and educational outcomes: an Aotearoa/New Zealand nationwide birth cohort study using the Integrated Data Infrastructure.

AIMS/HYPOTHESIS: Type 1 diabetes is one of the most common chronic diseases of childhood. It is hypothesised that the metabolic and psychosocial consequences of type 1 diabetes may affect educational outcomes; however, existing literature presents conflicting results. This study aimed to assess whether educational outcomes differ for young people with and without type 1 diabetes in Aotearoa/New Zealand (NZ). METHODS: This was a nationwide 9 year birth cohort study of all people born in NZ from 1993 to 2001 using linked administrative data held within the Integrated Data Infrastructure, a national research database containing linked health and non-health data. Educational outcomes of high school attainment, high school attendance and university enrolment were measured from age 13 years until 20 years. Generalised linear regression models with log link and Gaussian distributions were used to compare educational outcomes between those with and those without type 1 diabetes, adjusting for sociodemographic and maternal characteristics. RESULTS: Of the 442,320 children in the birth cohort, type 1 diabetes was identified in 2058 (0.47%) (mean [SD] age of type 1 diabetes diagnosis 7.7 [3.4] years). Educational outcomes were significantly lower for children with type 1 diabetes than for those without type 1 diabetes, including for any high school qualification (RR 0.97 [95% CI 0.95, 0.99]), university entrance-level high school attainment (RR 0.88 [95% CI 0.84, 0.92]), regular high school attendance (RR 0.91 [95% CI 0.85, 0.97]) and university enrolment (RR 0.93 [95% CI 0.88, 0.98]), even after adjusting for sociodemographic and maternal factors. In addition, educational outcomes were substantially lower for those with post type 1 diabetes diagnosis hospitalisations for diabetic ketoacidosis and hypoglycaemia. CONCLUSIONS/INTERPRETATION: In this whole NZ birth cohort study, type 1 diabetes was associated with lower educational outcomes spanning secondary school and into university enrolment. Ongoing efforts to support students with type 1 diabetes are needed, particularly for those with a greater risk profile.

An Artificial Neural Network for Nasogastric Tube Position Decision Support.

Purpose: To develop and validate a deep learning model for detection of nasogastric tube (NGT) malposition on chest radiographs and assess model impact as a clinical decision support tool for junior physicians to help determine whether feeding can be safely performed in patients (feed/do not feed). Materials and Methods: A neural network ensemble was pretrained on 1 132 142 retrospectively collected (June 2007-August 2019) frontal chest radiographs and further fine-tuned on 7081 chest radiographs labeled by three radiologists. Clinical relevance was assessed on an independent set of 335 images. Five junior emergency medicine physicians assessed chest radiographs and made feed/do not feed decisions without and with artificial intelligence (AI)-generated NGT malposition probabilities placed above chest radiographs. Decisions from the radiologists served as ground truths. Model performance was evaluated using receiver operating characteristic analysis. Agreement between junior physician and radiologist decision was determined using the Cohen κ coefficient. Results: In the testing set, the ensemble achieved area under the receiver operating characteristic curve values of 0.82 (95% CI: 0.78, 0.86), 0.77 (95% CI: 0.71, 0.83), and 0.98 (95% CI: 0.96, 1.00) for satisfactory, malpositioned, and bronchial positions, respectively. In the clinical evaluation set, mean interreader agreement for feed/do not feed decisions among junior physicians was 0.65 ± 0.03 (SD) and 0.77 ± 0.13 without and with AI support, respectively. Mean agreement between junior physicians and radiologists was 0.53 ± 0.05 (unaided) and 0.65 ± 0.09 (AI-aided). Conclusion: A simple classifier for NGT malposition may help junior physicians determine the safety of feeding in patients with NGTs.Keywords: Neural Networks, Feature Detection, Supervised Learning, Machine Learning Supplemental material is available for this article. Published under a CC BY 4.0 license.

NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data.

Current PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Results obtained with NiftyPAD were compared with the well-established software packages PPET and QModeling for a range of kinetic models. Clinical data from eight subjects scanned with four different amyloid tracers were used to validate the computational performance. NiftyPAD achieved [Formula: see text] correlation with PPET, with absolute difference [Formula: see text] for linearised Logan and MRTM2 methods, and [Formula: see text] correlation with QModeling, with absolute difference [Formula: see text] for basis function based SRTM and SRTM2 models. For the recently published SRTM ASL method, which is unavailable in existing software packages, high correlations with negligible bias were observed with the full scan SRTM in terms of non-displaceable binding potential ([Formula: see text]), indicating reliable model implementation in NiftyPAD. Together, these findings illustrate that NiftyPAD is versatile, flexible, and produces comparable results with established software packages for quantification of dynamic PET data. It is freely available ( https://github.com/AMYPAD/NiftyPAD ), and allows for multi-platform usage. The modular setup makes adding new functionalities easy, and the package is lightweight with minimal dependencies, making it easy to use and integrate into existing processing pipelines.

It Takes a Village: Partnerships in Primary School Relationships and Sexuality Education in Aotearoa.

The implementation of relationships and sexuality education as part of Health and Physical Education in The New Zealand Curriculum (Ministry of Education, Ministry of Education. (2007). The New Zealand Curriculum. Learning Media Limited.) involves a range of people sharing their perspectives in order to shape the subject on paper and in practice. This paper presents the findings of a qualitative collective case study in three primary schools in Aotearoa. Experimenting with Appreciative Inquiry, we found that connections and conversations between a wide variety of people and organisations have a critical role to play in relation to planning and teaching relationships and sexuality education in schools: (i) Schools and teachers working in partnership with colleagues within and across schools, (ii) connections with whanau and relationships with learners, and (iii) access to wider supports and services. Our findings suggest that having conversations and establishing and maintaining productive partnerships between a variety of people are critical if relationships and sexuality education is to live up to its potential and meet learners' needs.

Microneedle-based devices for point-of-care infectious disease diagnostics.

Recent infectious disease outbreaks, such as COVID-19 and Ebola, have highlighted the need for rapid and accurate diagnosis to initiate treatment and curb transmission. Successful diagnostic strategies critically depend on the efficiency of biological sampling and timely analysis. However, current diagnostic techniques are invasive/intrusive and present a severe bottleneck by requiring specialist equipment and trained personnel. Moreover, centralised test facilities are poorly accessible and the requirement to travel may increase disease transmission. Self-administrable, point-of-care (PoC) microneedle diagnostic devices could provide a viable solution to these problems. These miniature needle arrays can detect biomarkers in/from the skin in a minimally invasive manner to provide (near-) real-time diagnosis. Few microneedle devices have been developed specifically for infectious disease diagnosis, though similar technologies are well established in other fields and generally adaptable for infectious disease diagnosis. These include microneedles for biofluid extraction, microneedle sensors and analyte-capturing microneedles, or combinations thereof. Analyte sampling/detection from both blood and dermal interstitial fluid is possible. These technologies are in their early stages of development for infectious disease diagnostics, and there is a vast scope for further development. In this review, we discuss the utility and future outlook of these microneedle technologies in infectious disease diagnosis.

The practice of the alcohol industry as health educator: a critique.

Adolescence marks a developmental period with heightened vulnerability to alcohol use and its consequences. In this viewpoint paper, we examine the involvement of the alcohol industry in alcohol and other drug (AoD) education from both an alcohol harm reduction and a school-based health education perspective, using the example of the Smashed programme to illustrate our critique. We issue caution to schools that are invited to participate.

Utilising feedback from patients and their families as a learning strategy in a Foundation Degree in palliative and supportive care: a qualitative study.

BACKGROUND: In the UK, support workers provide much of the care that palliative care patients receive, and a novel Foundation Degree was developed to enhance their skills. Feedback on performance is a recognised educational tool that reinforces good practice, and gives insight into areas of weakness, but its use with this workforce has not been described. AIM: The aim of this qualitative study is to explore tutor and support workers' experiences of seeking and receiving feedback from patients and their families; focusing on its values and challenges. METHODS: Support workers enrolled onto the Foundation Degree in Palliative and Supportive Care, were asked to seek feedback from patients and/or their families about the care that they provided using a 'My Experience' questionnaire. Forms were returned anonymously to the course tutor who discussed results with the student as a formative education strategy. The students' experience of this was explored in focus group interviews at three time points. Two tutors' experiences were similarly explored. Results were analysed thematically. RESULTS: Students enjoyed receiving feedback. Positive feedback helped to increase confidence, and negative feedback allowed students to look critically at their practice and identify areas of weakness. Some experienced challenges in approaching patients/families due to having a small number of suitable patients/families; a reluctance to burden patients; high patient turnover and brevity of care relationships. The tutors enjoyed delivering feedback, recognising its benefits as an educational strategy. Some concern was expressed about how to balance delivering negative feedback while continuing to provide tutorial support throughout the Foundation Degree. CONCLUSIONS: User feedback is considered a key formative educational strategy. Its use in health and social support workers is not established. The experiences of students and tutors in this Foundation Degree demonstrate some of the benefits and challenges of this as an educational strategy.